Table 2 - uploaded by Enrico Nobile
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Thrust coefficients for the non cavitating case
Source publication
In this work we simulate the non-cavitating and cavitating flow around the PPTC (Potsdam Propeller Test Case) model scale propeller. The calculations are carried out using the commercial CFD solver ANSYS CFX 12, and for the prediction of the cavitating behaviour three different mass transfer models, previously calibrated, are employed.
Contexts in source publication
Context 1
... the simulations were carried out on mesh B using three different mass transfer models. In Table 2 and 3 the predicted values of the thrust coefficients for the non cavitating and cavitating flow regimes are collected. In Table 2, the experimental K T,EXP at the smallest advance coefficient J, corresponds, for the reasons given before, to a J value of 1.019. ...
Context 2
... Table 2 and 3 the predicted values of the thrust coefficients for the non cavitating and cavitating flow regimes are collected. In Table 2, the experimental K T,EXP at the smallest advance coefficient J, corresponds, for the reasons given before, to a J value of 1.019. From the results collected in Table 2 it is possible to point out that for the non cavitating conditions the predicted values of the thrust differed less than 2% from the experimental ones. ...
Context 3
... Table 2, the experimental K T,EXP at the smallest advance coefficient J, corresponds, for the reasons given before, to a J value of 1.019. From the results collected in Table 2 it is possible to point out that for the non cavitating conditions the predicted values of the thrust differed less than 2% from the experimental ones. Table 3 shows that the propeller's cavitating performances predicted with the three different mass transfer models were in line with each other. ...
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Citations
... Vaporization begins at nucleation sites and, as the vapor volume fraction increases, the nucleation site density decreases accordingly. Thus, in the expression for vaporization, r v is replaced by r nuc (1 − r v ), where r nuc is the volume fraction of the nucleation sites [35]. Finally, [36] proposed a modification that leads to Equation (30), where F c is dimensionless empirical coefficient for both the condensation and vaporization processes. ...
Diffuser technology placed around hydrokinetic rotors may improve the conversion of the fluid’s kinetic energy into shaft power. However, rotor blades are susceptible to the phenomenon of cavitation, which can impact the overall power efficiency. This paper presents the development of a new optimization model applied to hydrokinetic blades shrouded by a diffuser. The proposed geometry optimization takes into account the effect of cavitation inception. The main contribution of this work to the state of the art is the development of an optimization procedure that takes into account the effects of diffuser efficiency, ηd, and thrust, CTd. The authors are unaware of any other work available in the literature considering the effect of ηd and CTd on the cavitation of shrouded hydrokinetic blades. The model uses the Blade Element Momentum Theory to seek optimized blade geometry in order to minimize or even avoid the occurrence of cavitation. The minimum pressure coefficient is used as a criterion to avoid cavitation inception. Additionally, a Computational Fluid Dynamics investigation was carried out to validate the model based on the Reynolds-Averaged Navier–Stokes formulation, using the κ−ω Shear-Stress Transport turbulence and Rayleigh–Plesset models, to estimate cavitation by means of water vapor production. The methodology was applied to the design of a 10 m diameter hydrokinetic rotor, rated at 250 kW of output power at a flow velocity of 2.5 m/s. An analysis of the proposed model with and without a diffuser was carried out to evaluate the changes in the optimized geometry in terms of chord and twist angle distribution. It was found that the flow around a diffuser-augmented hydrokinetic blade doubles the cavitation inception relative to the unshrouded case. Additionally, the proposed optimization model can completely remove the cavitation occurrence, making it a good alternative for the design of diffuser-augmented hydrokinetic blades free of cavitation.
... In this paper, a model of propeller, as shown in Figure 1 also known as Potsdam Propeller Test Case (PPTC) is used [5]. PPTC is a standard propeller with right hand rotation orientation and five blades which are moderately skewed with a high design pitch. ...
... The homogeneous (mixture) model was employed in combination with three different mass transfer models. More precisely, the models originally proposed by Zwart et al. [25], Singhal et al. (known as Full Cavitation Model, FCM for brevity) [20] and Kunz et al. [10] were employed, tuned according to [13,16]. The turbulence effect was modelled using the standard RANS approach in combination with the Shear Stress Transport (SST) turbulence model [12]. ...
... In this study three previously calibrated mass transfer models were used. In particular the models originally proposed by Zwart et al. [25], Singhal et al. [20], and Kunz et al. [10] with the empirical coefficients tuned according to [13,16], were employed. At this stage, it is worth clarifying that in the case of RANS simulations additional transport equations equation have to be solved according to the selected turbulence model. ...
The numerical predictions of a cavitating model scale propeller working in uniform and oblique flow
conditions are presented. The cavitating phenomena are numerically reproduced using a homogeneous
(mixture) model where three previously calibrated mass transfer models are alternatively used to model
the mass transfer rate. The turbulence effect is modelled using the Reynolds Averaged Navier Stokes
(RANS) approach. The simulations are performed using an open source solver. The numerical results are
compared with available experimental data. For a quantitative comparison the propeller thrust is considered,
while for a qualitative comparison, snapshots of cavitation patterns are shown. The thrust values
obtained with the three different mass transfer models are very close to each other, however differences
in the predicted cavitation patterns are observed. Moreover, some discrepancies between the numerical
results and experimental data are reported.
... Besides these experimental studies, the E779A propeller had been the subject of numerous simulations studies by using CFD methods and comparisons with the experimental results as a benchmark propeller. For example, Morgut and Nobile performed CFD simulations using the three mass transfer models of Zwart, Full Cavitation Model (FCM) and Kunz for the E779A as well as for the Potsdam Propeller Test Case (PPTC) including inclined shaft conditions (Morgut and Nobile, 2012). Vaz et al. (2015) used RANS and RANS-BEM coupled approaches in non-cavitating and cavitating conditions to predict propeller performance, pressure distributions and cavitation volume for the latter condition. ...
This paper presents the improvements of cavitation modelling for marine propellers particularly developing tip vortex cavitation. The main purpose of the study is to devise a new approach for modelling tip vortex cavitation using Computational Fluid Dynamics (CFD) methods with commercial software, STAR-CCM+. The INSEAN E779A model propeller was used for this study as a benchmark propeller. Utilizing this propeller, firstly, validation studies were conducted in non-cavitating conditions together with grid and time step uncertainty studies. Then, the cavitation was simulated on the propeller using a numerical cavitation model, which is known as the Schnerr-Sauer model, based on the Rayleigh-Plesset equation. While a Reynolds Averaged Navier Stokes (RANS) model was used for open water simulations, Detached Eddy Simulations (DES) and Large Eddy Simulations (LES) models were preferred for cavitation simulations to capture the cavitation and evaluate its effect on propeller performance accurately. Although the comparison with the benchmark experimental data showed good agreement for the thrust and torque coefficients as well as sheet cavitation pattern, tip vortex cavitation could not be adequately simulated using the existing method. After an evaluation of the interaction between cavitation modelling and generated meshes, two techniques, which involved volumetric control and adaptive mesh refinement , were used in combination on the region where the tip vortex cavitation is likely to occur. The first technique, which is called a 'volumetric control method', was developed using spiral geometry around the propeller tip region to generate a finer mesh for capturing tip vortex cavitation. Although this method gave better tip vortex cavitation extension than the method without any mesh refinement or with tube refinement, it still required to be improved to extend the tip vortices further into the propeller slipstream. The second method, which is called 'adaptive mesh refinement', was introduced using the pressure distribution data from the results of the 'volumetric control method'. This improved approach, which is called "Mesh Adaption and Refinement for Cavitation Simulation (MARCS)", has been successfully applied to simulate the tip vortices trailing from the blades of the INSEAN E779A propeller as demonstrated in the paper. The results of the simulations showed an excellent agreement with the experiments in the open literature by tracking the tip vortex cavitation along this propeller's slipstream.
... The current results were obtained using the homogeneous mixture model along with two different cavitation (mass transfer) models. More precisely, the models originally proposed by Kunz et al. [1] and Zwart et al. [2], and modified according to [3,4] were used. The turbulence effect was modelled using the standard RANS approach in combination with the Shear Stress Transport (SST) turbulence model [5]. ...
The numerical predictions of a model scale propeller working in uniform
and oblique flow are presented. Both non-cavitating and cavitating flow conditions
are numerically investigated using homogeneous (mixture) model. Two previously
calibrated mass transfer models are alternatively used to model the mass transfer
rate due to cavitation. The turbulence effect is modelled using the Reynolds Averaged
Navier Stokes (RANS) approach. The simulations are performed using an
open source solver. The numerical results are compared with the available experimental
data. For a quantitative comparison the propeller thrust is considered, while
for a qualitative comparison, snapshots of cavitation patterns are shown. From the
overall results it seems that, with the current simulation approach it is possible to
predict with a reasonable accuracy the propeller performances. Nevertheless, for
detailed reproduction of complex cavitation phenomena, such as bubble cavitation
for instance, a more sophisticated modelling approach is probably required.
... P is the flow ambient pressure; I is the moment of inertia of the body about an axis parallel to the y0 axis and passing through its center of mass; The cavity shape is assumed to be an ellipse (actually, it is an ellipsoid in 3D) (see [8,13,14]). The shape and side of the elliptic cavity are characterized by its maximum diameter and its length (see Fig.3) ...
... The geometry of the cavity is given by the following formula (see [8,13,14]): ...
... C 1ε , C 2ε , C µ , σ k , σ ε are the constant parameters (see [11]). The vapor volume fraction equation is (see [13,14]) ...
On the imperfect water entry, a high-speed slender body moving in the forward direction, rotates inside the cavity. The body's motion makes super cavity phenomena in the water flow. The water velocity and pressure fields interact during the body's motion. In this paper, the coupling simulation model is a combination of two sub-models: In the first sub-model, the motion of slender body running very fast underwater is simulated. The equation system of this sub-model is solved by Runge-Kutta method; In the second sub-model, the water flow and pressure field under reaction of very fast slender body motion are simulated by CFD model. The simulation results of this coupled model are compared with experiments based on magnitudes of velocity U by x0 direction and error percents for cavity diameter and length.
... In the specific case of marine propellers and hydraulic turbines, CFD analysis can be effectively used to predict the overall machine performances as well as to investigate the effect of specific flow phenomena such as cavitation for instance [1] to [6]. ...
Cavitating phenomena, which may occur in many industrial systems, can be modelled using several approaches. In this study a homogeneous multiphase model, used in combination with three previously calibrated mass transfer models, is evaluated for the numerical prediction of cavitating flow around a marine propeller and a Kaplan turbine runner. The simulations are performed using a commercial computational fluid dynamics (CFD) solver and the turbulence effects are modelled using, alternatively, the Reynolds averaged Navier Stokes (RANS) and scale adaptive simulation (SAS) approaches. The numerical results are compared with available experimental data. In the case of the propeller the thrust coefficient and the sketches of cavitation patterns are considered. In the case of the turbine the efficiency and draft tube losses, along with the cavitation pattern sketches, are compared. From the overall results it seems that, for the considered systems, the three different mass transfer models can guarantee similar levels of accuracy for the performance prediction. For a very detailed investigation of the fluid field, slight differences in the predicted shapes of the cavitation patterns can be observed. In addition, in the case of the propeller, the SAS simulation seems to guarantee a more accurate resolution of the cavitating tip vortex flow, while for the turbine, SAS simulations can significantly improve the predictions of the draft tube turbulent flow.
... Vaporization begins at nucleation sites and, as the vapor volume fraction increases, the nucleation site density decreases. Thus, only for vaporization, r v is replaced by r nuc ð1 À r v Þ, where r nuc is the vol- ume fraction of the nucleation sites [28]. Barkir et al. [29] propose a heuristic modification that, together with nucleation accounting, leads to Eq. (17), where F c is an empirical constant used to discrim- inate condensation and vaporization. ...
... It is important to clarify that both mesh arrangements used here proved to guarantee mesh independent results in former studies [33,34], and the average value of y + measured on blade surfaces was approximatively equal to 38 for E779A propeller and 32 for PPTC propeller. Figure 10 illustrates the blade surface meshes of both propellers. ...
The numerical predictions of the cavitating flow around two model scale propellers in uniform inflow are presented and discussed. The simulations are carried out using a commercial CFD solver. The homogeneous model is used and the influence of three widespread mass transfer models, on the accuracy of the numerical predictions, is evaluated. The mass transfer models in question share the common feature of employing empirical coefficients to adjust mass transfer rate from water to vapour and back, which can affect the stability and accuracy of the predictions. Thus, for a fair and congruent comparison, the empirical coefficients of the different mass transfer models are first properly calibrated using an optimization strategy. The numerical results obtained, with the three different calibrated mass transfer models, are very similar to each other for two selected model scale propellers. Nevertheless, a tendency to overestimate the cavity extension is observed, and consequently the thrust, in the most severe operational conditions, is not properly predicted.
In this paper, we present our analysis of the non-cavitating and cavitating unsteady performances of the Potsdam Propeller Test Case (PPTC) in oblique flow. For our calculations, we used the Reynolds-averaged Navier-Stokes equation (RANSE) solver from the open-source OpenFOAM libraries. We selected the homogeneous mixture approach to solve for multiphase flow with phase change, using the volume of fluid (VoF) approach to solve the multiphase flow and modeling the mass transfer between vapor and water with the Schnerr-Sauer model. Comparing the model results with the experimental measurements collected during the Second Workshop on Cavitation and Propeller Performance – SMP’15 enabled our assessment of the reliability of the open-source calculations. Comparisons with the numerical data collected during the workshop enabled further analysis of the reliability of different flow solvers from which we produced an overview of recommended guidelines (mesh arrangements and solver setups) for accurate numerical prediction even in off-design conditions. Lastly, we propose a number of calculations using the boundary element method developed at the University of Genoa for assessing the reliability of this dated but still widely adopted approach for design and optimization in the preliminary stages of very demanding test cases.
