High-fidelity Large-eddy Simulation Research Articles

High-fidelity numerical simulation of longitudinal thermoacoustic instability in a high-pressure subscale rocket combustor

A detailed analysis of thermoacoustic combustion instability in a subscale rocket combustor at high pressure is reported in this paper using the high-fidelity large-eddy simulation (LES). Self-sustained longitudinal combustion instability is observed in the experiments for this combustor configuration. The computational setup follows the past experimental study of a rig called the Continuously Variable Resonance Combustor (CVRC). In this combustor, both stable combustion and unstable combustion dynamics have been observed by varying the oxidizer injector length. A combustor configuration with an oxidizer injector length of 12 cm is chosen for this study based on the experimental evidence of longitudinal combustion instability. An autonomous meshing using the modified cut-cell Cartesian grid generation approach, coupled with on-the-fly Adaptive Mesh Refinement (AMR) is employed in this study. Chemical reactions during turbulent combustion in this configuration are modeled by solving the species transport equations with a detailed chemistry solver using a kinetic mechanism with 21 species and 84 steps. Similar to the findings of the experiments, we observe a self-sustained combustion instability in the present study, which is characterized by a limit cycle behavior of the acoustic fluctuations. The spectral analysis of these acoustic fluctuations shows good agreement with experimental data for the frequency of the three dominant modes. We further analyze the features of time-averaged and instantaneous reacting flow to study the effects of combustion instability on the flame holding dynamics, vortex shedding, mixing, and combustion regime due to flame movement along the longitudinal direction of the combustor during a limit cycle. These phenomena are effectively captured through the integration of AMR with complex chemistry in the present study. A particular focus of the study is on understanding the role of minor species (OH, HO2, and CH2O) in the physical and state-space in sustaining the flame during the combustion instability. Additionally, the physical mechanisms responsible for the production and dissipation of enstrophy are examined to demonstrate that their contribution can create significant fluctuations in the reacting flow field, which can assist in sustaining the combustion instability.

Large-scale Multiphysics Simulations of Small Modular Reactors Operating in Natural Circulation

Thanks to the advancements in high-performance computing, advanced modeling and simulation have become crucial in driving the development and deployment of next-generation nuclear reactors, such as small modular reactors (SMRs). SMRs offer the promise of cost-effective baseload electricity production and improved safety, while addressing some of the challenges associated with large reactor designs, such as high capital costs and extended construction timelines. As part of the Exascale Computing Project, the large-scale multiphysics simulation of an entire SMR primary system has been achieved by combining computational fluid dynamics and neutronics. In addition to the successful demonstration of full-core SMR simulations, the current study integrated the impact of natural circulation into the system. Natural circulation is the primary mechanism driving coolant circulation in SMRs. The mass flow rate in the core depends on the core power, and a numerical model has been developed to predict it. The pressure drop caused by the helical coil steam generator was also accounted for by developing a pressure drop correlation based on high-fidelity large eddy simulation results, further improving prediction accuracy. The results of the study demonstrate that the implemented natural circulation model is effective in predicting the responses of SMR full-core multiphysics simulations.

Large-eddy simulation of vortex-induced vibration of a circular cylinder at Reynolds number 10 000

The canonical scenario of cross-flow vortex-induced vibration (VIV) of a circular cylinder in the turbulent regime, which has been studied by several physical experiments in the literature, is reexamined in this study through high-fidelity large-eddy simulations (LES) at a Reynolds number 104. The VIV response (including vibration amplitude and frequency) and hydrodynamic coefficients predicted by the present LES agree with the experimental results better than previous numerical attempts. In addition, several phenomena reported by previous experimental studies are confirmed numerically for the first time. After validating against the experiments, new VIV characteristics and physical mechanisms are explored with confidence. First, a collective analysis on the frequency spectra of the displacement, lift, and velocity signals provides a complete picture of the frequency response of the system. In contrast, the use of a single signal may miss certain aspects of the frequency response, so that caution should be exercised. Second, spanwise correlation of primary vortex shedding is examined, where relatively low correlations in the upper and lower branches are likely because the vortex shedding patterns involve complex vortex generation and interaction. Third, the effect of mass ratio (m*) of the cylinder on the VIV response is analyzed with a range of m* (=1.4–3.4) relevant to cylindrical structures used in offshore engineering (such as subsea pipelines). The variations in the amplitude response, frequency response, and hydrodynamic coefficients with m* and reduced velocity are examined in detail. The present results suggest that a lighter pipeline is more susceptible to the onset of VIV.

Wind farm structural response and wake dynamics for an evolving stable boundary layer: computational and experimental comparisons

Abstract. The wind turbine design process requires performing thousands of simulations for a wide range of inflow and control conditions, which necessitates computationally efficient yet time-accurate models, especially when considering wind farm settings. To this end, FAST.Farm is a dynamic-wake-meandering-based mid-fidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. This work is an extension of a study that addressed constructing a diurnal cycle evolution based on experimental data (Quon, 2024). Here, this inflow is used to validate the turbine structural and wake-meandering response between experimental data, FAST.Farm simulation results, and high-fidelity large-eddy simulation results from the coupled Simulator fOr Wind Farm Applications (SOWFA)–OpenFAST tool. The validation occurs within the nocturnal stable boundary layer when corresponding meteorological and turbine data are available. To this end, we compared the load results from FAST.Farm and SOWFA–OpenFAST to multi-turbine measurements from a subset of a full-scale wind farm. Computational predictions of blade-root and tower-base bending loads are compared to 10 min statistics of strain gauge measurements during 3.5 h of the evolving stable boundary layer, generally with good agreement. This time period coincided with an active wake-steering campaign of an upstream turbine, resulting in time-varying yaw positions of all turbines. Wake meandering was also compared between the computational solutions, generally with excellent agreement. Simulations were based on a high-fidelity precursor constructed from inflow measurements and using state-of-the-art mesoscale-to-microscale coupling.

Investigation of hydrogen/air co-flow jet flame propagation mechanism in supersonic crossflow

The design of fuel injection schemes is crucial for improving the combustion performance of high-Mach number scramjet. To clarify the feasibility of the coaxial jet injection scheme, high fidelity Large Eddy Simulation of the supersonic coaxial jet flame is conducted. The simulations are in good agreement with the experimental results in terms of time-averaged velocity, temperature, and species distribution. Auto-ignition phenomenon and the characteristics of partially premixed flame are well captured. The introduction of co-flow air increases the vorticity magnitude close to the injection port and downstream near-wall region, which results in a 400 K rise in the time-averaged temperature on the downstream near-wall region and a 4% increase in the proportion of premixed combustion near the injection port. Moreover, the instantaneous distribution of hydroxy radical indicates that the spanwise width of the windward reaction shear layer is reduced utilizing the coaxial jet scheme. Chemical kinetic analysis is applied to reveal the propagation mechanism of partially premixed flames. Thermal explosion is the chemical explosion mode for all coaxial jet flame front, which are dominated by a high-temperature reaction path. The low-temperature reaction path mainly exists in the transverse jet injection port, downstream near-wall region of the single transverse jet and co-flow lifted flame base. These significant findings provide valuable insights for the potential engineering application of the coaxial jet injection scheme to a high Mach number scramjet.

Usage of high-fidelity large eddy simulation to improve the turbulence modeling of Reynolds averaged navier stokes simulation in film cooling applications via a neural network

In this study, high-Fidelity Large eddy simulation (LES) data was used to create a surrogate turbulence model to enhance the estimation of turbulent heat flux in a Reynolds averaged Navier Stokes (RANS) solver for film cooling applications. The LES simulation (A flat plate film cooling application with a Reynolds number of 17,382, a blowing ratio of 1 and a density ratio of 2) was validated by comparison with experimental data. A correlation analysis was performed to identify the most influential parameters, and temperature gradient, velocity gradient, turbulent dissipation rate, shear strain rate, and turbulent viscosity ratio were selected as the most effective parameters. A second model was developed to create a Galilean-invariant model that remains unaffected by changes in the coordinate system. Neural network was applied to the LES training data to propose a modified surrogate dynamic turbulent Prandtl number to be applied to the k − ε realizable RANS simulation. The first surrogate model was implemented to two different geometries, one geometry was a flat plate film cooling similar to the training data but with different flow conditions, and another one was a more complex geometry with pressure gradient. The second model was only implemented on the second geometry and produced similar results. The surrogate models predicted a more accurate thermal field near the cooling wall (up-to 58 % error reduction) with a computational time complexity similar to the base RANS solver.

Three-dimensional stochastic dynamical modeling for wind farm flow estimation

Modifying turbine blade pitch, generator torque, and nacelle direction (yaw) are conventional approaches for enhancing energy output and alleviating structural loads. However, the efficacy of such methods is challenged by the lag in adjusting such settings after atmospheric variations are detected. Without reliable short-term wind forecasting tools, current practice, which mostly relies on data collected at or just behind turbines, can result in sub-optimal performance. Data-assimilation strategies can achieve real-time wind forecasting capabilities by correcting model-based predictions of the incoming wind using various field measurements. In this paper, we revisit the development of a class of prior models for real-time estimation via Kalman filtering algorithms that track atmospheric variations using ground-level pressure sensors. This class of models is given by the stochastically forced linearized Navier-Stokes equations around the three-dimensional waked velocity profile defined by a curled wake model. The stochastic input to these models is devised using convex optimization to achieve statistical consistency with high-fidelity large-eddy simulations. We demonstrate the ability of such models in reproducing the second-order statistical signatures of the turbulent velocity field. In support of assimilating ground-level pressure measurements with the predictions of said models, we also highlight the significance of the wall-normal dimension in enhancing two-point correlations of the pressure field between the ground and the computational domain.

Toward ultra-efficient high-fidelity predictions of wind turbine wakes: Augmenting the accuracy of engineering models with machine learning

This study proposes a novel machine learning (ML) methodology for the efficient and cost-effective prediction of high-fidelity three-dimensional velocity fields in the wake of utility-scale turbines. The model consists of an autoencoder convolutional neural network with U-Net skipped connections, fine-tuned using high-fidelity data from large-eddy simulations (LES). The trained model takes the low-fidelity velocity field cost-effectively generated from the analytical engineering wake model as input and produces the high-fidelity velocity fields. The accuracy of the proposed ML model is demonstrated in a utility-scale wind farm for which datasets of wake flow fields were previously generated using LES under various wind speeds, wind directions, and yaw angles. Comparing the ML model results with those of LES, the ML model was shown to reduce the error in the prediction from 20% obtained from the Gauss Curl hybrid (GCH) model to less than 5%. In addition, the ML model captured the non-symmetric wake deflection observed for opposing yaw angles for wake steering cases, demonstrating a greater accuracy than the GCH model. The computational cost of the ML model is on par with that of the analytical wake model while generating numerical outcomes nearly as accurate as those of the high-fidelity LES.

Numerical insights into turbulent penetrative convection over localized heat sources

The turbulent penetrative convection into a stable convective boundary layer represents an important phenomenon in environmental engineering and atmospheric science. In the present study, we present a series of numerical simulations performed by two modeling approaches: the high-fidelity Large-Eddy Simulations (LES), and the less computationally demanding transient Reynolds-Averaged Approach (TRANS), but with an advanced sub-scale turbulent heat flux model. By simulating different localized heat sources over the ground, and by performing a direct comparative assessment of results obtained by LES and TRANS, we confirmed an overall good agreement in predicting the time evolution of the horizontally averaged temperature profiles. Similarly, the morphology of instantaneous thermal plumes and large convective structures predicted by TRANS were in reasonable agreement with the referent LES predictions.

Wall-modeled large eddy simulation of a tandem wing configuration in transonic flow

In this study, the interaction between a turbulent wake and the boundary layer of a horizontal tail plane (HTP) in the transonic flow regime is investigated. The setup considered corresponds to a generic tandem wing configuration with an OAT15A airfoil as the main wing and a National Advisory Committee for Aeronautics (NACA) 64A-110 as an HTP. Due to the transonic flow, the suction side of the OAT15A exhibits buffet. The numerical approach consists of a two-stage procedure in which a detached eddy simulation (DES) provides unsteady inflow conditions for a subsequent zonal high-fidelity large eddy simulation (LES) performed for the HTP region only; the turbulent boundary layer is modeled using scale-resolved wall-modeled LES (WMLES). The study mainly pursues two objectives: first, to discuss the influence of wake turbulence on the flow characteristics of the NACA airfoil; and second, to evaluate the capability of WMLES as a low-cost but high-resolution numerical approach in challenging flow conditions. Essentially, the study confirms the expected result that the outer part of the HTP's boundary layer is dominated by the wake of the main wing. Mainly based on a discussion of turbulence spectra, the study further demonstrates the advantage of WMLES over DES, proving that WMLES is able to capture the effects of wake turbulence on boundary layer dynamics, and thus validates the WMLES approach as a cost-effective, high-resolution turbulence modeling approach. On a superordinate level, the study further sketches a possible way on how a flow problem with such a strongly unsteady behavior could be systematically evaluated.

On the efficacy of facial masks to suppress the spreading of pathogen-carrying saliva particles during human respiratory events: Insights gained via high-fidelity numerical modeling.

Respiratory fluid dynamics is integral to comprehending the transmission of infectious diseases and the effectiveness of interventions such as face masks and social distancing. In this research, we present our recent studies that investigate respiratory particle transport via high-fidelity large eddy simulation coupled with the Lagrangian particle tracking method. Based on our numerical simulation results for human respiratory events with and without face masks, we demonstrate that facial masks could significantly suppress particle spreading. The studied respiratory events include coughing and normal breathing through mouth and nose. Using the Lagrangian particle tracking simulation results, we elucidated the transport pathways of saliva particles during inhalation and exhalation of breathing cycles, contributing to our understanding of respiratory physiology and potential disease transmission routes. Our findings underscore the importance of respiratory fluid dynamics research in informing public health strategies to reduce the spread of respiratory infections. Combining advanced mathematical modeling techniques with experimental data will help future research on airborne disease transmission dynamics and the effectiveness of preventive measures such as face masks.

Effect of temporal increase in equivalence ratio on combustion instability of a lean-premixed swirling hydrogen flame

The effect of temporal increase in the equivalence ratio on the combustion instability of a lean-premixed low-swirl hydrogen jet flame in a low-swirl combustor (LSC) is investigated in detail using a high-fidelity Large-Eddy Simulation (LES). The equivalence ratio is linearly increased from 0.3 to 0.5 over a duration of 0.4 s. The results show that the pressure oscillation amplitude in the combustor increases significantly when the equivalence ratio at the combustor inlet (ERCI) exceeds 0.42, and the maximum pressure amplitude and the combustion instability mode exhibit trends consistent with those in a previous experiment and numerical simulation conducted with the same LSC setup at a fixed equivalence ratio of 0.39. Temporal variations in the equivalence ratio and consequently the temperature inside the combustor cause the drastic amplification of pressure oscillation (when the ERCI exceeds 0.42) whose amplitude is larger than that at the fixed equivalence ratio (= 0.39). Prior to the onset of this exceptionally strong combustion instability, a transient irregular oscillation phenomenon comprising instantaneous changes in the pressure oscillation frequency is observed. While the pressure oscillations in the combustor and in the injector channel are in phase after the onset of strong combustion instability, they are in opposite phases during the occurrence of the irregular oscillation phenomenon prior to the onset of strong combustion instability. This irregular oscillation phenomenon predicted by the LES may play a crucial role in the mechanism of transition from stable combustion to combustion instability.

Large-eddy simulation of upwind-hill effects on wind-turbine wakes and power performance

The present study utilizes high-fidelity large-eddy simulation (LES) to examine the upwind-hill impacts on wind-turbine wakes and power performance. Both the LES and Reynolds-Averaged Navier–Stokes (RANS) show good agreement with the experimental results of average velocity, whereas the LES exhibits great improvements in predicting turbulence characteristics. In turbine simulations, the wake half-width shows different behaviors in the hill and flat cases. The Gaussian and cosine distributions are good representations of the unskewed profiles of velocity deficit, although some discrepancies are seen around the wake edges. However, the spanwise profiles of velocity deficit become skewed in some hill cases. The non-zero pressure gradient (NZPG) model is employed to predict the velocity deficit in the wakes of a hilltop-sited turbine, and a generalized condition is proposed so that the NZPG model can work in the scenario where the pressure gradients at the turbine location or in its near wakes are not zero. Appropriately assigning initial values for the NZPG model is important for its successful use. The presence of the upwind hill has an adverse influence on the power output of the hilltop-sited turbine. The installation of wind turbines in the valley region near upwind hills is not recommended due to the limited wind-energy resources and intense turbulence levels.

Heat transfer enhancement with additively manufactured rough surfaces: Insights from large-eddy simulations

To study the impact of additively manufactured (AM) roughness on fluid flow and heat transfer, we performed a series of high-fidelity large-eddy simulations on turbulent heat transfer over a three-dimensional AM rough surface with varying bulk Reynolds number and average roughness height values. We considered rough surfaces created using AM techniques at Siemens based on Nickel Alloy IN939 material with four different mean roughness heights, ks= 1.594, 1.992, 2.630, and 3.984 mm, and the simulations were performed at five bulk Reynolds numbers of 1000, 3000, 6000, 11 700, and 18 000. The temperature was treated as a passive scalar with a Prandtl number of 0.71. To better understand the effect of wall roughness on the momentum and heat transfer mechanism, mean temperature and velocity profiles as well as heat fluxes are presented. The wall-normal Reynolds stress, ⟨ux′ur′⟩, and heat flux, ⟨ur′Θ′⟩, decrease for larger wall roughness heights, Ra, and their respective magnitudes remain very similar for different Ra. A similarity rule for friction factor and heat transfer is used to correlate and interpret the numerical results and compare them with previously existing results, both theoretical and experimental. The assessment of the thermal performance factor illuminates the improvement in heat transfer with the existing surface roughness. By studying the probability density functions of the instantaneous Stanton number, the recirculation zones, which are the result of an adverse pressure gradient, were found to have a profound effect on heat transfer. This is important as it leads to the wall-scaled mean temperature profiles being of larger magnitude than the mean velocity profiles both inside and outside the roughness layer. This means that the temperature wall roughness function, ΔΘ+, differs from the momentum wall roughness function, ΔU+.

A priori analysis for high-fidelity large-eddy simulation of wall-bounded transcritical turbulent flows

Transcritical turbulent flows are governed by the compressible Navier–Stokes equations along with a real-gas equation of state. Their computation is strongly susceptible to numerical instabilities and requires kinetic-energy- and pressure-equilibrium-preserving schemes to yield stable and non-dissipative scale-resolving simulations. Building upon a recently developed kinetic-energy- and pressure-equilibrium-preserving discretization framework based on transporting a pressure equation, the objectives of this paper are to (i) derive a filtered set of equations suitable for large-eddy simulation, and (ii) characterize the properties of the resulting subfilter-scale terms by performing a priori analyses of transcritical wall-bounded turbulence direct numerical simulation data. The filtering operation leads to three unconventional subfilter-scale terms that emerge from the pressure equation and require dedicated modeling. The subfilter-scale stress tensor is dissected in terms of magnitude, shape and orientation based on an eigendecomposition analysis, and compared with existing subfilter-scale models. A priori analyses confirm that models of eddy-viscosity type are favorable for this framework, although the tensor shape is not fully captured. Closure expressions are finally proposed and tested for the novel subfilter terms, showing acceptable performances.

Field-data-based validation of an aero-servo-elastic solver for high-fidelity large-eddy simulations of industrial wind turbines

Abstract. To design the next generations of wind turbines, engineers from the wind energy industry must now have access to new numerical tools, allowing the high-fidelity simulation of complex physical phenomena and thus a further calibration of lower-order models. For instance, the rotors of offshore wind turbines, whose diameters can now exceed 200 m, are highly flexible and fluid–structure interactions cannot be neglected any longer. Accordingly, this paper presents a new aero-servo-elastic solver designed to perform high-fidelity large-eddy simulation (LES) of wind turbines, as well as of rotor–wake interactions classically occurring in wind farms. In this framework, the turbine blades are modeled as flexible actuator lines. In terms of operating parameters (rotation speed and pitch angles) and power output, the solver is first validated against field data from the Westermost Rough offshore wind farm, for three different operation points. A very good agreement between the numerical results and field data is obtained. To push the validation further, additional results are compared to those given by a certified aero-servo-elastic solver used in the industry, which relies on a blade element momentum (BEM) method. The internal loads throughout the first blade and the deflections at the tip are studied in detail, and some discrepancies are observed. Of a reasonable amplitude overall, those are legitimately related to intrinsic modeling differences between the two solvers.

Numerical analysis of the performance of a composite marine propeller blade subject to structural blade oscillations

High-fidelity Large Eddy Simulations (LES) are conducted over the oscillating marine propeller blades to investigate the effects of blade oscillation on the unsteady flow behaviour as well as to analyse the performance of the composite marine propeller blades. The accuracy of the results is first verified against the reference experimental results. A nonlinear frequency-domain solution or harmonic solution method is also applied to this study, based on a high-fidelity LES model, in addition to the traditional time-domain solution method to investigate the capabilities of the frequency-domain method in predicting the unsteady flow parameters, vortex generation, and hydrodynamic damping to determine the stability of the propeller blades. Results obtained reveal that the oscillation of the blade has a great impact on the vortex generation process which could impose implications on the performance and structural integrity of the composite marine propeller blades.

High-Fidelity Simulations of Shield Assembly Mixed-Convection Flows with Applications Toward Reduced-Resolution Modeling

Flow circulation and heat removal through shield and reflector assemblies can have major impacts on safety in long transients for sodium fast reactors (SFRs). These transients are typically categorized by reduced flow rates and large-scale organized flow patterns, including potential intra-assembly circulation. Such low-flow cases can provide challenges for experiments because of complications in measuring the flow rates and temperatures with high accuracy in different areas. This consequently also raises the uncertainty of many modeling approaches for these phenomena. In an effort to address some of these issues, high-fidelity large eddy simulations are performed using the highly parallel solver NekRS. A 19-pin configuration of a tight-lattice wire-wrapped hexagonal bundle (pitch-to-diameter ratio = 1.07), representing a prototypical internal configuration of a shield assembly, was investigated. The sodium flow was set at a bundle Reynolds number of 2000, with simulations being performed for modified Richardson numbers of 0.0 (i.e., no buoyancy), 0.01, and 0.04, where mixed-convection effects are anticipated. The flow and temperature fields for these cases are discussed in detail. The high-fidelity data should prove useful as reference data for expanding and improving on various reduced-resolution approaches. A basic framework for combining subchannel and computational fluid dynamics methodologies in SFRs is also presented, with preliminary results from simulations of light water reactor bundles and a discussion of changes that need to be made for potential application to SFRs.

Evaluation of Turbulence Models in Unsteady Separation

Unsteady separation is a phenomenon that occurs in many flows and results in increased drag, decreased lift, noise emission, and loss of efficiency or failure in flow devices. Turbulence models for the steady or unsteady Reynolds-averaged Navier–Stokes equations (RANS and URANS, respectively) are commonly used in industry; however, their performance is often unsatisfactory. The comparison of RANS results with experimental data does not clearly isolate the modeling errors, since differences with the data may be due to a combination of modeling and numerical errors, and also to possible differences in the boundary conditions. In the present study, we use high-fidelity large-eddy simulation (LES) results to carry out a consistent evaluation of the turbulence models. By using the same numerical scheme and boundary conditions as the LES, and a grid on which grid convergence was achieved, we can isolate modeling errors. The calculations (both LES and RANS) are carried out using a well-validated, second-order-accurate code. Separation is generated by imposing a freestream velocity distribution, that is modulated in time. We examined three frequencies (a rapid, flutter-like oscillation, an intermediate one in which the forcing and the flow have the same timescales, and a quasi-steady one). We also considered three different pressure distributions, one with alternating favorable and adverse pressure gradients (FPGs and APGs, respectively), one oscillating between an APG and a zero-pressure gradient (ZPG), and one with an oscillating APG. All turbulence models capture the general features of this complex unsteady flow as well or better than in similar steady cases. The presence, during the cycle, of times in which the freestream pressure-gradient is close to zero affects significantly the model performance. Comparing our results with those in the literature indicates that numerical errors due to the type of discretization and the grid resolution are as significant as those due to the turbulence model.

Computational Fluid Dynamics Turbulence Model and Experimental Study for a Fontan Cavopulmonary Assist Device.

Head-flow HQ curves for a Fontan cavopulmonary assist device (CPAD) were measured using a blood surrogate in a mock circulatory loop and simulated with various computational fluid dynamics (CFD) models. The tests benchmarked the CFD tools for further enhancement of the CPAD design. Recommended Reynolds-Averaged Navier-Stokes (RANS) CFD approaches for the development of conventional ventricular assist devices (VAD) were found to have shortcomings when applied to the Fontan CPAD, which is designed to neutralize off-condition obstruction risks that could contribute to a major adverse event. The no-obstruction condition is achieved with a von Karman pump, utilizing large clearances and small blade heights, which challenge conventional VAD RANS-based CFD hemodynamic simulations. High-fidelity large eddy simulation (LES) is always recommended; however, this may be cost-inhibitive for optimization studies in commercial settings, thus the reliance on RANS models. This study compares head and power predictions of various RANS turbulence models, employing experimental measurements and LES results as a basis for comparison. The models include standard k-ϵ, re-normalization group k-ϵ, realizable k-ϵ, shear stress transport (SST) k-ω, SST with transitional turbulence, and Generalized k-ω. For the pressure head predictions, it was observed that the standard k-ϵ model provided far better agreement with experiment. For the rotor torque, k-ϵ predictions were 30% lower than LES, while the SST and LES torque values were near identical. For the Fontan CPAD, the findings support using LES for the final design simulations, k-ϵ model for head and general flow simulation, and SST for power, shear stress, hemolysis, and thrombogenicity predictions.