Turbulence Model Research Articles

Numerical study of a low power hydrokinetic turbine

ABSTRACT In a hydrokinetic turbine, the flow completely surrounds the turbine allowing it to convert the kinetic energy of the water to mechanical power. The general objective of this work is the numerical study of a low power axial flow hydroelectric turbine using CFD (Computational Fluid Dynamics). The scope of this work includes a CFD analysis of a hydroelectric turbine, including the rotor, hub and casing, a comparison between results of steady and transient solvers, and the turbine performance in design and off-design conditions. Three-dimensional simulations were carried out using ANSYS Fluent software, with the aim of estimating the design loads and determining the nominal operating conditions, including results of steady and transient simulations. Results were obtained with the k-ω SST turbulence model and the SIMPLEC calculation algorithm, in structured and unstructured meshes, which involve stationary and rotating domains.

A comparative study of hydrodynamic performance between ducted and non-ducted Archimedes spiral hydrokinetic turbines

The Archimedes spiral hydrokinetic turbine (ASHT), as a novel type of horizontal-axis hydrokinetic turbine, is well suited for deployment in the low-speed ocean current environment. Besides, integrating hydrokinetic turbines within a duct stands out as a prospective approach to enhance the efficiency of energy harvesting. In this study, a duct is implemented with the aim of enhancing the performance of ASHT. Using the commercial code program ANSYS-FLUENT, the Reynolds-averaged Navier-Stokes (RANS) equations are solved along with the SST k-ω turbulence model to elucidate the distinctive hydrodynamic characteristics of ASHT and its ducted configuration (DASHT). The findings revealed a consistent outperformance of the DASHT over the ASHT, achieving a notable maximum improvement of 122% in the power coefficient (CP). The ASHT exhibits turbulence near the blade tips, generating large spiral tip vortex, while the DASHT, with its duct, induces significant turbulence, resulting in a wider range of vortex structures. Furthermore, the DASHT shows better energy harvesting due to enhanced diffusion under yawed flow. The wake asymmetry and increased turbulence are observed as the yaw angle increases, affecting vortex structures differently in ASHT and DASHT. At higher yaw angle, the DASHT vortex splits into two parts, contributing to a more complex wake structure.

Effect of buoyancy force on buoyancy waterwheel efficiency using numerical flow simulation

In this work, the performance of a buoyant waterwheel to produce hydrokinetic power is investigated through analytical theory and computational fluid dynamics simulation. The impact of the buoyancy wheel is investigated by establishing the performance parameters through the use of a moving mesh approach and a realizable k-ε turbulence model. Transient simulation is required to comprehend the flow of physical processes. Using moving mesh as a transient methodology of the buoyancy waterwheel, numerical flow simulations and theoretical analytical methods are used in this study to assess the effect of buoyant force generated on the performance of the buoyancy wheel. The buoyancy waterwheel that will be put to the test has eight straight blades and a diameter of one meter. The pinwheel force and torque created in the numerical flow simulation (CFD) are 414.96 N and 207.48 Nm, respectively, whereas in the theoretical calculation they are 449.06 N and 224.53 Nm, according to the research findings. It is possible to compute the buoyancy wheel's power output and efficiency mathematically, yielding values of 1619.35 W and 68.07%. The buoyancy wheel's power output and efficiency, as determined by numerical flow simulation, are 1495.95 W and 62.88%, respectively. Based on theoretical and CFD study results, the buoyancy wheel generates a standard deviation of 7.62%. Thus, for the buoyancy wheel, a temporary method that makes advantage of the moving mesh characteristic is advised. This method can also be applied as a future alternative energy source for the Piko hydro turbine

Exploring the similarity relationships from the nondimensionalization of atmospheric turbulence

AbstractNondimensionalization, a theoretical approach for establishing interconnections among parameters within a set of equations, has proven to be an effective tool for the analysis of atmospheric turbulence. By applying nondimensionalization to turbulence equations, a concise form of dimensionless turbulence functions can be obtained. This process also yields several dimensionless parameters, defined as combinations of characteristic scales. From the dimensionless tensor $${B}$$ B and vector $${{\varvec{\beta}}}_{\theta}$$ β θ introduced in this study, the characteristic length scale, $${z}^{s}$$ z s , can be defined as an alternative of length scale in similarity theories. Using the data from observational station in Horqin Sandy Land, quantified verifications of similarity relationships are carried out. The dimensionless parameters derived from nondimensionalization is not only in accordance with traditional turbulence theories but also facilitate the derivation of relationships among other dimensionless parameters. This reveals new similarity relationships that supplement the Monin–Obukhov theory. Under conditions of flat terrain and steady motions, the new length scale gives rise to similarity relationships exhibiting “4/3” exponential and near-linear patterns, which are associated with turbulent transport. These results make it possible to obtain the turbulent fluxes directly from the statistics of meteorological elements, even in stable stratifications. Consequently, the method of nondimensionalization can be taken as a reference in parameterization schemes of turbulence and climate models, and is fruitful in prospect of further study on atmospheric turbulence.

An accurate and robust method for intensification of wastewater sludge pipe flow

Globally, environmental impacts and population growth are driving the process intensification of wastewater treatment plants (WWTPs) via transition from conventional (2–3 wt% solids) to highly concentrated (4–6 wt% solids) wastewater sludges (HCWS). This presents an industrial challenge as HCWS are complex, non-Newtonian materials whose viscosity increases nonlinearly with solids concentration. This viscosity increase is particularly relevant for sludge pipe flow as it leads to considerable pumping pressure that ultimately limits the feasibility of pipe flow transportation. Hence, process intensification demands accurate prediction of HCWS turbulent pipe flow to design and optimise pumping infrastructure and piping systems. Such prediction requires accurate rheological characterisation of HCWS and numerical prediction of HCWS turbulent pipe flow, neither of which has been achieved to date due to respective limitations associated with benchtop rheometry and numerical turbulence models. We address these challenges by first developing accurate methods for rheological characterisation of HCWS via laminar flow of digested sludge at various solids concentrations (2–5 %) in a fully instrumented pipe loop facility at a large-scale WWTP. These rheological parameters are used in direct numerical simulation (DNS) computations (that avoid turbulence models) of turbulent pipe flow of HCWS. These predictions are then validated against turbulent flow pipe loop data. This method yields accurate (2–15 % error) predictions of HCWS turbulent pipe flow, compared with up to ∼75 % error for conventional pipe flow correlations. This validation highlights the need for accurate rheological characterisation and numerical simulation to predict HCWS pipe flow and provides a sound basis for the intensification and optimisation of WWTP pipeline systems.

Numerical simulation of dust deposition characteristics of photovoltaic arrays taking into account the effect of the row spacing of photovoltaic modules

Dust deposition on the surfaces of Photovoltaic (PV) arrays during their operation markedly affects their power generation efficiency. Previous research has overlooked the impact of the row spacing of PV modules on the actual dust deposition on PV arrays. This study investigates the dust deposition process and its behavior on PV arrays considering variations in row spacings, inlet wind speeds, dust particle sizes, and dust particle counts. By employing commercial Computational Fluid Dynamics (CFD) software, incorporating the SST k-ω turbulence model and discrete particle model, numerical simulations were performed to analyze the airflow field, dust particle trajectories, dust deposition patterns, and deposition rates on the PV array through grid-independent verification and numerical validation. At the same time, we performed a comparative analysis of the deposition rate considering the rebound of dust particles on the PV module surface versus the case where rebound is not considered. Results revealed that the maximum dust deposition rates at different inlet wind speeds were 6.84 %, 8.84 %, 11.0 %, and 14.6 %, corresponding to dust sizes of 50 μm, 100 μm, 120 μm, and 300 μm, respectively. Smaller dust particles exhibited lower deposition rates, while larger particles were influenced more by mass inertia and gravity, leading to predominant deposition on the front row of PV modules. Larger dust particles are more likely to deposit primarily on the front row of PV modules in a PV array. The tilt angles of 30°, 45°, and 60° were chosen to study the effects of different tilt angles on the dust deposition of PV arrays, and the results show that the dust deposition rate decreases as the tilt angle increases, and it is worth noting that the larger the tilt angle, the larger the dust deposition rate is when the dust particles are especially small as 5 μm. When wind speeds are low and dust particles are small, the dust deposition rate gradually rises as the row spacing increases. However, at higher wind speeds with small dust particles, the row spacing has minimal impact on the dust deposition rate. Conversely, with larger dust particles, increasing the row spacing results in a lower dust deposition rate. These findings underscore the significance of optimizing PV array design for enhanced power generation efficiency.

Effect and optimization of geometric parameters and arrangement on film cooling performance of fan-shaped holes based on generalized regression neural network

Inadequate design of film cooling holes can significantly reduce film cooling effectiveness of turbine blades, compromising high temperature resistance. By comparing experimental data, the most suitable turbulence model is selected to calculate film cooling effectiveness on the leading edge of turbine blades. A high-precision nonlinear mapping relationship between the geometric parameters and arrangement of fan-shaped holes, and film cooling effectiveness is established by using machine learning which is trained by 1200 cases. The genetic algorithm is employed to search for optimal parameters. Sensitivity and correlation analyses are conducted to assess the influence degree of the geometric parameters and arrangement on film cooling effectiveness and these mechanisms are analyzed in depth. Findings reveal that the injection angle exerts the most significant effect on film cooling effectiveness, with significant effects observed for the forward expansion angle and the angle with respect to stagnation line. Interactions among parameters play a crucial role in influencing film cooling effectiveness and cannot be disregarded. In the design space, the optimal configuration comprises the injection angle of 30°, the forward expansion angle of 10°, the streamwise torsion angle of 10°, the pitch of holes of 12 mm and the angle with respect to stagnation line of 30°.

Effect of Process Parameters on the Substrate Surface in Cold Spray Coating

In this work, we used the cold spray process to coat a surface and investigated to understand the influence of various process parameters on the substrate surface temperature. The parameters we varied included the pressure, temperature, particle size, and particle speed of the titanium powder that we used in the cold spray coating process. It is a unique finding in the field of cold spray coating. For the substrate material, we chose steel and simulated the spray geometry using a two-dimensional axisymmetric model. This model employed a k-ɛ turbulence model with an implicit pressure-based solver of second-order precision. Our observations revealed that the surface temperature of the substrate reached its maximum value when the length of the injector was 15 mm. We also found that the most compatible length for the nozzle barrel was equal to the length of the particle injector.

Aerodynamic discrepancies of high-speed trains meeting within two types noise barriers: considering modeling scale ratio

Purpose Sustainable urban rail transit requires noise barriers. However, these barriers’ durability varies due to the differing aerodynamic impacts they experience. The purpose of this paper is to investigate the aerodynamic discrepancies of trains when they meet within two types of rectangular noise barriers: fully enclosed (FERNB) and semi-enclosed with vertical plates (SERNBVB). The research also considers the sensitivity of the scale ratio in these scenarios. Design/methodology/approach A 1:16 scaled moving model test analyzed spatiotemporal patterns and discrepancies in aerodynamic pressures during train meetings. Three-dimensional computational fluid dynamics models, with scale ratios of 1:1, 1:8 and 1:16, used the improved delayed detached eddy simulation turbulence model and slip grid technique. Comparing scale ratios on aerodynamic pressure discrepancies between the two types of noise barriers and revealing the flow field mechanism were done. The goal is to establish the relationship between aerodynamic pressure at scale and in full scale. Findings The aerodynamic pressure on SERNBVB is influenced by the train’s head and tail waves, whereas for FERNB, it is affected by pressure wave and head-tail waves. Notably, SERNBVB's aerodynamic pressure is more sensitive to changes in scale ratio. As the scale ratio decreases, the aerodynamic pressure on the noise barrier gradually increases. Originality/value A train-meeting moving model test is conducted within the noise barrier. Comparison of aerodynamic discrepancies during train meets between two types of rectangular noise barriers and the relationship between the scale and the full scale are established considering the modeling scale ratio.

Investigation of a Modified Wells Turbine for Wave Energy Extraction

The Oscillating Water Column (OWC) is the most promising self-rectifying device for power generation from ocean waves; over the past decade, its importance has been rekindled. The bidirectional airflow inside the OWC drives the Wells turbine connected to a generator to harness energy. This study evaluated the aerodynamic performance of two hybrid airfoil (NACA0015 and NACA0025) blade designs with variable chord distribution along the span of a Wells turbine. The present work examines the aerodynamic impact of the variable chord turbine and compares it with one with a constant chord. Ideally, Wells rotor blades with variable chords perform better since they have an even axial velocity distribution on their leading edge. The variable chord rotor blade configurations differ from hub to tip with taper ratios (Chord at Tip/Chord at Hub) of 1.58 and 0.63. The computation is performed in ANSYS™ CFX 2023 R2 by solving three-dimensional, steady-state, incompressible Reynolds Averaged Navier–Stokes (RANS) equations coupled with a k-ω Shear Stress Transport (SST) turbulence model in a non-inertial reference frame rotating with the turbine. The accuracy of the numerical results was achieved by performing a grid independence study. A refined mesh showed good agreement with the available experimental and numerical data in terms of efficiency, torque, and pressure drop at different flow coefficients. A variable chord Wells turbine with a taper ratio of 1.58 had a peak efficiency of 59.6%, as opposed to the one with a taper ratio of 0.63, which had a peak efficiency of 58.2%; the constant chord Wells turbine only had a peak efficiency of 58.5%. Furthermore, the variable chord rotor with the higher taper ratio had a larger operating range than others. There are significant improvements in the aerodynamic performance of the modified Wells turbine, compared to the conventional Wells turbine, which makes it suitable for wave energy harvesting. The flow field investigation around the turbine blades was conducted and analyzed.

Investigation on Cryogenic Cavitation Characteristics of an Inducer Considering Thermodynamic Effects

An inducer is a key component in a cryogenic pump to improve its cavitation performance. The thermodynamic effects of the cryogenic medium make the cryogenic cavitation flow extremely complicated. For this reason, it is crucial to investigate the cryogenic cavitation flow of the inducer which is equipped upstream of the cryogenic pump. In this paper, the isothermal cavitation model is modified based on the law of heat conduction, and the cryogenic cavitation model of the inducer is developed by considering thermodynamic effects. The turbulence model is also modified to account for the compressibility of cryogenic cavitation flow. The methods of numerical calculations are performed to investigate the influence of thermodynamic effects on cryogenic cavitation of the inducer. The law of the spatio-temporal evolution of cryogen cavitation in the inducer is clarified. The initial position, development and collapse phenomenon of cavitation are obtained. The relationship between the generation and collapse of the cavitation and the work capacity of the inducer’s blade, the relationship between thermodynamic effects and the influence of the inducer’s blade tip leakage vortex and thermodynamic on cryogenic cavitation of the inducer are revealed.

Turbulence Closure Modeling with Machine Learning: A Foundational Physics Perspective

Abstract Turbulence closure modeling using machine learning is at an early crossroads. The extraordinary success of machine learning (ML) in a variety of challenging fields had given rise to an expectation of similar transformative advances in the area of turbulence closure modeling. However, by most accounts, the current rate of progress toward accurate and predictive ML-RANS (Reynolds Averaged Navier-Stokes) closure models has been very slow. Upon retrospection, the absence of rapid transformative progress can be attributed to two factors: the
underestimation of the intricacies of turbulence modeling and the overestimation of ML’s ability to capture all features without employing targeted strategies. To pave the way for more
meaningful ML closures tailored to address the nuances of turbulence, this article seeks to
review the foundational flow physics to assess the challenges in the context of data-driven
approaches. Revisiting analogies with statistical mechanics and stochastic systems, the key
physical complexities and mathematical limitations are explicated. It is noted that the current
ML approaches do not systematically address the inherent limitations of a statistical approach
or the inadequacies of the mathematical forms of closure expressions. The study underscores
the drawbacks of supervised learning-based closures and stresses the importance of a more
discerning ML modeling framework. As ML methods evolve (which is happening at a rapid
pace) and our understanding of the turbulence phenomenon improves, the inferences expressed
here should be suitably modified.

Analysis on cause of erosion of guide vane of high‐head Francis turbine in sandy river

AbstractThe Kizilsu River Basin in China is located in the desert Gobi area with high sediment content and high hardness. After 4798h operation, the maintenance of a high‐head Francis turbine in this basin found that the guide vane was seriously worn, and even most of the top and lower skirts of the front of the guide vane were worn off. In this study, the k‐ε turbulence model, ZGB cavitation model and sediment erosion prediction model were used to simulate the solid‐liquid two‐phase flow and cavitation of guide vane. The research results show that the guide vane of a high‐head Francis turbine in a sandy river has a high sediment velocity and serious surface erosion, with the maximum erosion rate of 1.0 × 10−6 kg/(m2·s), while the area near the skirt of the guide vane is a low‐pressure area lower than the saturated steam pressure, and cavitation is very easy to occur, with the maximum vapor volume fraction of 0.9. Serious cavitation erosion occurs near the skirt of the guide vane, and the combined effect of sand erosion and cavitation erosion on the surface of the skirt of the guide vane aggravates the damage of the skirt structure. The research results provide a technical basis for the antiabrasion design of the guide mechanism of the high‐head Francis turbine and the operation and maintenance of the hydropower station in the sandy river.

Performance of dual‐chamber oscillating water column device under irregular incident waves using Reynolds averaged Navier–Stokes model

AbstractThe purpose of this study is to analyze the hydrodynamic performance and efficiency of a dual‐chamber oscillating water column (OWC) device. For the Joint North Sea Wave Project (JONSWAP) incident waves spectrum, a two dimensional numerical wave tank is employed with nonlinear Reynolds averaged Navier–Stokes equations model along with the standard turbulence model. The free surface elevation is measured using the volume of fluid method. The numerical simulation demonstrates the streamline and velocity vector profiles throughout an entire pressure fluctuation cycle inside the chambers of the given OWC device. Further, investigation is carried out to analyze the impact of pressure drop and air flow rate through the orifice of the dual‐chamber OWC device on the power generation. Moreover, the power spectral density analysis of the free surface elevation is provided to know the variation of the parameters in the frequency domain. These results demonstrate that the effectiveness of the dual‐chamber OWC device is more near the significant wave height m.

Computational Fluid Dynamics Simulation on Blade Geometry of Novel Axial FlowTurbine for Wave Energy Extraction

Wave energy converters (WECs) utilizing the Oscillating Water Column (OWC) principle have gained prominence for harnessing kinetic energy from ocean waves. This study explores an innovative approach by transforming the pivoting Denniss–Auld turbine blades into a fixed configuration, offering a simplified alternative. The fixed-blade design emulates the maximum pivot points during the OWC’s exhalation and inhalation phases. Traditional Denniss–Auld turbines rely on complex hub systems to enable controllable blade rotation for performance optimization. This research examines the turbine’s efficiency without mechanical actuation. The simulations were conducted using ANSYS™ CFX 2023 R2 to solve the three-dimensional, incompressible, steady-state Reynolds-Averaged Navier–Stokes (RANS) equations, employing the k-ω SST turbulence model to close the system of equations. A grid convergence study was performed, and the numerical results were validated against available experimental and numerical data. An in-depth analysis of the intricate flow field around the turbine blades was also conducted. The modified Denniss–Auld turbine demonstrated a broad operating range, avoiding stalling at high flow coefficients and exhibiting performance characteristics like an impulse turbine. However, the peak efficiency was 12%, significantly lower than that of conventional Denniss–Auld and impulse turbines. Future research should focus on expanding the design space through parametric studies to enhance turbine efficiency and power output.

Effects of Angle of Attack on Flow-Induced Vibration of a D-Section Prism

The VIVACE device, which utilizes flow-induced vibration for harvesting ocean current energy, has been a research hotspot in the field of renewable energy. In this study, the flow-induced vibration characteristics and energy conversion efficiency of a D-section prism were investigated using the k-ω SST turbulence model and Newmark-β method. The vibration amplitude, frequency, equilibrium position offset, and energy conversion efficiency of the two-degree-of-freedom cylinder were systematically analyzed at seven angles of attack between 0 and 180 degrees. The Reynolds number ranged from 368 to 14,742, corresponding to equivalent speeds of 2 to 20. The results indicate that the angle of attack has a significant influence on the flow-induced vibration response of the D-section prism. As the angle of attack changes, the vibration amplitude of the cylinder continuously increases, and the cylinder sequentially enters the vortex-induced vibration, vortex-induced vibration-galloping, and fully galloping branches. The change in the angle of attack disrupts the symmetry of the cylinder’s vibration in the streamwise direction, leading to a shift in the equilibrium position of the cylinder’s vibration. When the angle of attack is 0°, the energy conversion efficiency of the column reaches a maximum of 11.75%. Additionally, at high Reynolds numbers, the vibration of the cylinder is not self-limiting, making it more advantageous for energy conversion devices compared to cylinders with circular cross-sections.

URANS Prediction of the Hydrodynamic Interactions of Two Ship-like Floating Structures in Regular Waves

A side-by-side configuration of floating structures is commonly used in ocean exploration practices, such as offshore vessels for loading and offloading, floating cranes, and offshore floating wind turbines. Computational Fluid Dynamics (CFD) method is current practice for the analysis of hydrodynamic interactions of the side-by-side vessels. The purpose of this study is yo carry out a benchmark study of CFD method applied for the above analysis. URANS CFD method was applied utilizing a k-ε turbulence model and a volume of fluid (VOF) method to capture the free surface. Different ratios of wave length to vessel’s length and different gaps between between the vessels were considered in the study. Simulation results show that the wave length to vessel’s length ratio /L affects significantly the wave pattern around the vessels and inside the gap. For the shorter waves, the gap influences the wave pattern both inside and outside the gap. Further, the pressure distribution on the keel surface of the vessels is asymmetric about the vertical center plane along the vessel, which resulted in roll motion eventhough the vessel is in head seas. Roll motion was observed in all gap variations considered. Amplitude modulation was observed in the heave and pitch motions, while generation of side-band frequency components were observed in the roll motion, which indicate a non-linear fluid-structure interaction.

CFD and RSM Assist in Reducing the LPG Consumption of Burners for Agarwood Oil Production in Thailand

ABSTRACT This research aimed to optimize LPG consumption in Thai commercial burners used in agarwood oil production, specifically focusing on the KB-10, S-10, and EB-10 burners. Enhancing burner efficiency is crucial due to rising energy costs and environmental concerns. A dual approach using Response Surface Methodology (RSM) and Computational Fluid Dynamics (CFD) was employed in order to achieve the best burner. Central Composite Design (CCD) within the RSM framework determined the optimal swirl and inclination angles combinations. Modified burners with variant combination angles, as suggested by RSM, were numerically investigated. CFD simulations with Ansys Fluent, utilizing the k-ε turbulence and discrete ordinates (DO) radiation models, provided detailed insights into the combustion and heat transfer processes of those modified burners. The modified burners, SB10–1, SS10–3, and SEB10–7, demonstrated significant improvements. Laboratory and field tests indicated energy savings of 16.15%, 23.74%, and 20.75%, respectively. Statistical analysis confirmed these savings with p-values < .05. The 95% confidence intervals for LPG savings were 31.31 ± 0.8%, 33.42 ± 0.7%, and 31.84 ± 0.6%, corresponding to payback periods of approximately 2.99, 4.21, and 8.95 months. Additionally, CO and NOx emissions were kept below 350 ppm and 100 ppm, respectively. The novelty of this study lies in the combined use of RSM and CFD to optimize burner performance, leading to significant energy savings and emission reductions. These findings highlight the potential of these methods for burner optimization, offering both economic and environmental benefits. This research underscores the importance of integrating advanced modeling techniques to achieve sustainable and cost-effective industrial processes.

On the Generalization Capability of a Data-Driven Turbulence Model by Field Inversion and Machine Learning

This paper discusses the generalizability of a data-augmented turbulence model with a focus on the field inversion and machine learning approach. It is highlighted that the augmented model based on two-dimensional (2D) separated airfoil flows gives poor predictive capability for a different class of separated flows (NASA wall-mounted hump) compared to the baseline model due to extrapolation. We demonstrate a sensor-based approach to localize the data-driven model correction to tackle this generalizability issue. Furthermore, the applicability of the augmented model to a more complex aeronautical three-dimensional case, the NASA Common Research Model configuration, is studied. Observations on the pressure coefficient predictions and the model correction field suggest that the present 2D-based augmentation is to some extent applicable to a three-dimensional aircraft flow.

Evolution of underwater noise emission prediction technology for ship-propulsor combinations in an industry environment

ABSTRACT The prediction of underwater noise emissions by marine vessels has evolved significantly over the last decade as the interest shifted from exclusive military to civil use as a result of environmental concerns. Among different research groups, the best practices for the estimation with high-fidelity simulation methods based on hydrodynamic sound emissions are developed considering the complete vessel and propulsor. Here the current state-of-the-art computational fluid dynamics (CFD) approach, centered around propulsion units, is worked out in steps leading to the application for vessels. This consists of incompressible finite volume method flow simulations with large eddy turbulence modelling and volume-of-fluid phase capturing with a Schnerr-Sauer cavitation model in combination with an added permeable surface Ffowcs-Williams-Hawkings method for far-field acoustics. Many mechanistic arguments support it and the final validation cases lead to acceptable accuracy and enrich simulation data acquisition, however, few technical limitations reveal weaknesses compared to traditional approaches.