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CFD Simulation of Liquid Rocket Engine Injectors

Detailed design issues associated with liquid rocket engine injectors and combustion chamber operation require CFD methodology which simulates highly three-dimensional, turbulent, vaporizing, and combusting flows. The primary utility of such simulations involves predicting multi-dimensional effects caused by specific injector configurations. SECA, Inc. and Engineering Sciences, Inc. have been developing appropriate computational methodology for NASA/MSFC for the past decade. CFD tools and computers have improved dramatically during this time period; however, the physical submodels used in these analyses must still remain relatively simple in order to produce useful results. Simulations of clustered coaxial and impinger injector elements for hydrogen and hydrocarbon fuels, which account for real fluid properties, is the immediate goal of this research. The spray combustion codes are based on the FDNS CFD code' and are structured to represent homogeneous and heterogeneous spray combustion. The homogeneous spray model treats the flow as a continuum of multi-phase, multicomponent fluids which move without thermal or velocity lags between the phases. Two heterogeneous models were developed: (1) a volume-of-fluid (VOF) model which represents the liquid core of coaxial or impinger jets and their atomization and vaporization, and (2) a Blob model which represents the injected streams as a cloud of droplets the size of the injector orifice which subsequently exhibit particle interaction, vaporization, and combustion. All of these spray models are computationally intensive, but this is unavoidable to accurately account for the complex physics and combustion which is to be predicted, Work is currently in progress to parallelize these codes to improve their computational efficiency. These spray combustion codes were used to simulate the three test cases which are the subject of the 2nd International Workshop on-Rocket Combustion Modeling. Such test cases are considered by these investigators to be very valuable for code validation because combustion kinetics, turbulence models and atomization models based on low pressure experiments of hydrogen air combustion do not adequately verify analytical or CFD submodels which are necessary to simulate rocket engine combustion. We wish to emphasize that the simulations which we prepared for this meeting are meant to test the accuracy of the approximations used in our general purpose spray combustion models, rather than represent a definitive analysis of each of the experiments which were conducted. Our goal is to accurately predict local temperatures and mixture ratios in rocket engines; hence predicting individual experiments is used only for code validation. To replace the conventional JANNAF standard axisymmetric finite-rate (TDK) computer code 2 for performance prediction with CFD cases, such codes must posses two features. Firstly, they must be as easy to use and of comparable run times for conventional performance predictions. Secondly, they must provide more detailed predictions of the flowfields near the injector face. Specifically, they must accurately predict the convective mixing of injected liquid propellants in terms of the injector element configurations.

Farmer, Richard↗

Machine Learning Assisted Safety Modeling and Analysis of Advanced Reactors

With the advances in computational power and numerical methods, analysts can now rely on first-principle simulations to predict ultra-fine details in a variety of applications. Advances in machine learning (ML) have produced algorithms that can now learn high-level abstractions via hierarchical models. This project aims to leverage advances in ML techniques and the available high-resolution simulation data to develop a novel modeling and simulation (M\&S) methodology for reactor safety analysis. While application-agnostic ML techniques are available, complex physics constraints need to be incorporated into ML techniques to build ML-based closures for computationally efficient predictive simulations. This project intends to develop a physics-guided data-driven multi-scale methodology for M\&S of advanced reactors. The project focuses on thermal fluid (T/F) phenomena, which play major roles in advanced reactor safety. Specifically, we propose a data-driven coarse-mesh turbulence model based on local flow features for the transient analysis of thermal mixing and stratification in a sodium-cooled fast reactor (SFR). The model has a coarse-mesh setup to ensure computational efficiency, while it is trained by fine-mesh computational fluid dynamics (CFD) data with Reynolds-averaged Navier-Stokes (RANS) turbulence model to ensure accuracy. Three different neural networks are developed and tested for loss-of-flow transients in the hot pool of SFR, i.e. the densely connected convolutional neural network (DCNN), long-short-term-memory network based on proper orthogonal decomposition (POD-LSTM), and the DCNN informed by LSTM (DCNN-LSTM). The performances of these three neural networks are evaluated based on baseline models. The DCNN-LSTM model has been chosen for further hyperparameter optimization. Furthermore, based on a simplified two-dimensional case, uncertainty quantification (UQ) of the developed ML-based closure are investigated with three methods, i.e. Monte Carlo dropout, deep ensemble, and Bayesian neural network. The developed ML-based turbulent viscosity closure relation based on deep ensemble is then integrated into the system analysis module SAM and serves as a term in the conservation equations. Such a SAM-ML based procedure guarantees that the obtained results are consistent with the physical constraints of the thermal-fluid system. The SAM-ML simulation on the same loss-of-flow transient showed comparable accuracy with the CFD simulation but with a much coarser mesh setup. Last but not least, the ML-based closure improvement with the support of higher-fidelity data from large eddy simulation (LES) is discussed. As a first step towards this direction, a baseline LES simulation is performed to obtain comparable data with RANS results. Based on the early results, future investigation on further improving the ML-based closure is discussed. We believe the developed approach that combines scientific machine learning with nuclear system analysis code can benefit the advanced reactor community as more accurate safety analyses will better characterize reactor safety margins and reduce licensing efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

CFD prediction of the reacting flow field inside a subscale scramjet combustor

A three-dimensional, Reynolds-averaged Navier-Stokes CFD code has been used to calculate the reacting flowfield inside a hydrogen-fueled, subscale scramjet combustor. Pilot fuel was injected transversely upstream of the combustor and the primary fuel was injected transversely downstream of a backward facing step. A finite rate combustion model with two-step kinetics was used. The CFD code used the explicit MacCormack algorithm with point-implicit treatment of the chemistry source terms. Turbulent mixing of the jets with the airstream was simulated by a simple mixing length scheme, whereas near wall turbulence was accounted for by the Baldwin-Lomax model. Computed results were compared with experimental wall pressure measurements.

Chitsomboon, T.↗

Development of a Comprehensive Two-Phase Flow Database for the Validation of NEK-2P

Three-dimensional (3-D) two-phase Computational Fluid Dynamics (CFD) codes are emerging as a powerful and potentially practical tool for applications in which detailed local flow information is needed. However, two-phase flow models and associated closure relations are not well established for CFD applications, which is partly due to the lack of high-quality validation data. The main objective of this work is to develop a comprehensive database of two-phase flows that can be used to validate two-phase CFD codes such as NEK-2P. In this project, four advanced local measurement systems, including Particle Image Velocimetry and Planar Laser-Induced Fluorescence (PIV-PLIF), high-speed imaging, x-ray densitometry, and multi-sensor conductivity probe are employed to measure the local two-phase flow parameters of both gas and liquid phases. By combining these techniques, the local void fraction, bubble velocity, interfacial area concentration, bubble frequency, liquid velocity, turbulence intensity, etc., in various two-phase flow regimes can be obtained. These local measurement techniques are first used in a 25.4 mm circular pipe test section. Seven air-water two-phase flow conditions spanning the bubbly, slug, churn-turbulent, and annular flow regimes are measured in this facility. The obtained database contains the radial profiles of both gas- and liquid-phase parameters at three axial locations along the test section. The second facility used in this work contains a 30 mm × 10 mm rectangular test section, in which three two-phase flow and two single-phase flow conditions are measured. Two-dimensional distributions of local two-phase flow parameters in the cross-sectional plane are measured in this facility at three axial locations as well. A facility featuring a 3×3 electrically heated rod bundle is also designed and being constructed in this project. This facility is specially designed for optical measurements and is expected to provide high-quality boiling data in the future. Preliminary analyses have been performed for the data taken in the 25.4 mm circular pipe. Both center-peaked and wall-peaked void fraction profiles have been observed in the data depending on the two-phase flow conditions and/or developing lengths. The 1-D drift-flux model was evaluated with the newly obtained datasets, in which both gas- and liquid-phases data were directly measured. The distribution parameter model has been optimized based on a new void-profile classification method proposed in this study. The optimized drift-flux model shows a significant improvement in predicting both gas velocity and void fraction. The measured liquid-phase turbulence was used to benchmark Sato’s turbulence model considering the bubble-induced shear stress for the three tested bubbly flows. The benchmark results showed good agreement between the PIV measurements and model predictions. In the bubbly flows tested that have low void fractions less than 3%, the effect of the bubble-induced turbulence was found not significant. However, the bubble-induced shear stress becomes important with the increase of the void fraction. The Conjugate Heat Transfer (CHT) model was developed and implemented in NEK-2P. This model allows the coupled simulation of the solid domain and two-phase fluid domain, allowing the specification of realistic boundary conditions. The CHT implementation was verified first with non-boiling simulations. The predicted temperatures in the fluid domain were shown to be identical in simulations with or without the CHT model. The CHT model was then validated through simulations of three Becker benchmark CHF tests performed under both Dryout (DO) and Departure from Nucleate Boiling (DNB) conditions. Reasonably good agreement was obtained between calculated wall temperatures and corresponding experimental data.

42 ENGINEERING↗

Development of an Axisymmetric Afterbody Test Case for Turbulent Flow Separation Validation

As identified in the CFD Vision 2030 Study commissioned by NASA, validation of advanced RANS models and scale-resolving methods for computing turbulent flows must be supported by improvements in high-quality experiments designed specifically for CFD implementation. A new test platform referred to as the Axisymmetric Afterbody allows for a range of flow behaviors to be studied on interchangeable afterbodies while facilitating access to higher Reynolds number facilities. A priori RANS computations are reported for a risk-reduction configuration to demonstrate critical variation among turbulence model results for a given afterbody, ranging from barely-attached to mild separated flow. The effects of body nose geometry and tunnel-wall boundary condition on the computed afterbody flow are explored to inform the design of an experimental test program.

Disotell, Kevin J.↗

Aeroheating Predictions for a Hypersonic, Turbulent Near-Wake

The accuracy of heating predictions using various turbulence models is examined for an axisymmetric near-wake at Mach 6. The CFD predictions are compared with experimental data collected under AGARD Working Group 18 on the wake of a 70-degree sphere-cone. The impact of grid resolution and discretization error is estimated, which allows a comparison of stacked-block and conventional structured meshes. The accuracy of steady Reynolds-averaged Navier-Stokes (RANS) models is contrasted with that of a hybrid RANS/Large-Eddy Simulation model. The predictions are made with three different CFD codes (LAURA, FUN3D, and HyperSolve), to demonstrate the code-to-code variation in the results. Steady SST models capture the qualitative nature of the heating in the wake, including the increasing peak heating with increasing Reynolds number. Spalart-Allmaras models, including SA-Catris, under-predicted the peak heating in the wake. Hybrid RANS/LES models improve upon the SA results but have their own modeling difficulties near the shear layer impingement. These results are generally consistent across solvers and grid topologies.

RANS↗

Aeroheating Predictions for a Hypersonic, Turbulent Near-Wake

The accuracy of heating predictions using various turbulence models is examined for an axisymmetric near-wake at Mach 6. The CFD predictions are compared with experimental data collected under AGARD Working Group 18 on the wake of a 70-degree sphere-cone. The impact of grid resolution and discretization error is estimated, which allows a comparison of stacked-block and conventional structured meshes. The accuracy of steady Reynolds-averaged Navier-Stokes (RANS) models is contrasted with that of a hybrid RANS/Large-Eddy Simulation model. The predictions are made with three different CFD codes (LAURA, FUN3D, and HyperSolve), to demonstrate the code-to-code variation in the results. Steady SST models capture the qualitative nature of the heating in the wake, including the increasing peak heating with increasing Reynolds number. Spalart-Allmaras models, including SA-Catris, under-predicted the peak heating in the wake. Hybrid RANS/LES models improve upon the SA results but have their own modeling difficulties near the shear layer impingement. These results are generally consistent across solvers and grid topologies.

RANS↗

Effects of Different Types of Entrances on Natural Ventilation in a Subway Station

In this study, the natural ventilation of a horizontal entrance of a typical subway station is investigated based on numerical simulations and experiments. In addition, a renormalization group k-e model (RNG k-e model) is applied to compute both the internal and external airflow patterns. Computational fluid dynamics (CFD) simulations are validated based on the experimental results. Furthermore, a multiple variable regression model is employed to study how the different parameters affect the internal airflow rates of the subway station statistically, according to the experimental results. For this typical model, the parameter importance can be ranked as follows: (1) outdoor wind speed; (2) flow resistance of the subway station; (3) height of the wind catcher; and (4) length of the wind catcher. To understand the detailed pressure distribution of the horizontal entrance of the subway station with and without the wind catcher, 3D numerical simulations are conducted for different scenarios. We attempt to alter the size of the wind catcher (including the length and height) to study the characteristics of the pressure on the horizontal entrance of the subway station under outdoor wind-driven conditions. The pressure distributions for the entrance for different scenarios are compared and analyzed. Finally, the interactions between the internal and external flows are investigated by changing the resistance of the subway station. When the internal flow resistance is changed, the pressure coefficient (Cp) of the entrance is different as well. Hence, the Cp is not only affected by the outdoor environment, but is also influenced by the internal airflows.

CFD↗

CFD-Guided Combustion System Optimization of a Gasoline Range Fuel in a Heavy-Duty Compression Ignition Engine Using Automatic Piston Geometry Generation and a Supercomputer

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty diesel engine running with a gasoline fuel that has a research octane number (RON) of 80. The goal was to optimize the gasoline compression ignition (GCI) combustion recipe (piston bowl geometry, injector spray pattern, in-cylinder swirl motion, and thermal boundary conditions) for improved fuel efficiency while maintaining engine-out NO x within a 1-1.5 g/kW-hr window. The numerical model was developed using the multi-dimensional CFD software CONVERGE. A two-stage design of experiments (DoE) approach was employed with the first stage focusing on the piston bowl shape optimization and the second addressing refinement of the combustion recipe. For optimizing the piston bowl geometry, a software tool, CAESES, was utilized to automatically perturb key bowl design parameters. This led to the generation of 256 combustion chamber designs evaluated at several engine operating conditions. The second DoE campaign was conducted to optimize injector spray patterns, fuel injection strategies and in-cylinder swirl motion for the best performing piston bowl designs from the first DoE campaign. This comprehensive optimization study was performed on a supercomputer, Mira, to accelerate the development of an optimized fuel-efficiency focused design. Compared to the production combustion system in the baseline engine, the new combustion recipe from this study showed significantly improved closed-cycle fuel efficiency across key engine operating points while meeting the engine-out NO x targets. Optimized piston bowl designs and injector spray patterns were predicted to provide enhanced in-cylinder air utilization and more rapid mixing-controlled combustion, thereby leading to a fuel efficiency improvement. In addition, shifting the engine thermal boundary conditions toward leaner operation was also key to the improved fuel efficiency.

33 ADVANCED PROPULSION SYSTEMS↗

Liquid rocket combustion instability analysis by CFD methods

Combustion instability in liquid rocket engines is simulated computationally by using a simple two-parameter model for the combustion response function. The objectives of the study are to assess the capabilities of CFD algorithms for instability studies and to investigate the response to parametric effects such as bombs and distributed combustion. Results indicate that numerical solutions of high accuracy can be obtained if a sufficient number of grid points are used per wavelength of the disturbance. The short-term response to bombs or pulses triggers a large number of modes in the combustor whose faithful resolution requires highly dense grids, although there is evidence that correct long-term solutions can be obtained even if all the short-term frequencies are not resolved. Long-term responses to pulses are shown to decay to the most unstable mode in small amplitude cases, and to exhibit limit cycles in large amplitude cases. Comparison of distributed with concentrated heat release indicates the former is more stable for given values of the combustion response parameters, and that the distributed heat release gives rise to higher frequency disturbances. Wave steepening is observed in the solutions, but its effect is less pronounced in multidimensional waves than in one-dimensional waves.

Grenda, J. M.↗

Numerical simulation of involute-plate research reactor flow behavior using RANS, LES and DNS

This paper investigates the flow behavior of involute-plate research reactors by performing Reynolds-Averaged Navier Stokes simulation (RANS), Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) of the channel flow between fuel plates. By modeling turbulence with different numerical approaches, this study provides data with three levels of fidelity. For the RANS simulation, three widely used turbulence models, i.e., k-ε, k-ω, Reynolds Stress Turbulence model (RST) are applied by using the commercial CFD code STAR-CCM +. For LES and DNS, the open-source CFD code, Nek5000, is used given its outstanding scalability on High Performance Computer (HPC) and high-order technique. The results from RANS simulations are compared with that from LES and DNS for benchmarking. Both macroscale parameters and turbulence statistics, such as velocity magnitude, lateral velocity and turbulence kinetic energy, are presented and analyzed. The results from RANS simulation achieve good agreement with LES and DNS on velocity and turbulence kinetic energy prediction. The RST turbulence model predicts the most similar flow pattern of lateral velocity as compared to LES and DNS. The Lambda-2 (λ2) criterion with a reasonable threshold is used to demonstrate the instantaneous vortices distribution in the involute channel from both LES and DNS calculation. The DNS simulation captures more detailed turbulence especially near the corner, which explains the discrepancy between LES and DNS results near the corner. The normalized RMS error are defined and calculated to assess the performance of those turbulence models. The RST model captures the anisotropic feature of turbulence, which enable it to outperform other turbulence models for predicting the flow behavior in an involute channel. Although some discrepancies are found between LES and DNS results in the corner, the overall deviations between LES and DNS are found to be small. In conclusion, given that the computational cost of DNS calculation is an order of magnitude higher, using LES data for benchmarking RANS model is a cost-effective approach.

DNS↗

Study of non-equilibrium transport phenomena

Nonequilibrium phenomena due to real gas effects are very important features of low density hypersonic flows. The shock shape and emitted nonequilibrium radiation are identified as the bulk flow behavior parameters which are very sensitive to the nonequilibrium phenomena. These parameters can be measured in shock tubes, shock tunnels, and ballistic ranges and used to test the accuracy of computational fluid dynamic (CFD) codes. Since the CDF codes, by necessity, are based on multi-temperature models, it is also desirable to measure various temperatures, most importantly, the vibrational temperature. The CFD codes would require high temperature rate constants, which are not available at present. Experiments conducted at the NASA Electric Arc-driven Shock Tube (EAST) facility reveal that radiation from steel contaminants overwhelm the radiation from the test gas. For the measurement of radiation and the chemical parameters, further investigation and then appropriate modifications of the EAST facility are required.

Sharma, Surendra P.↗

Evaluation of Fish-Related Properties of Kaplan Turbines at the Design Phase: Simulation-based outcomes vs. Experimental Data

The development of turbine technology faces growing demands to maximize the survival of migratory fish passing through turbine flows. In this context, two strategies have emerged for quantifying hazardous hydraulic conditions: computer-based evaluations at design stage and recordings with autonomous sensors deployed in prototypes. The former is a desktop evaluation with many modelling assumptions (idealization) and the latter is a field technique that introduces various unknown and uncontrollable factors (uncertainty.) The present work introduces and implements a third method based on test rig measurements and the corresponding computer-based predictions of conditions that negatively affect fish survivability. The experimental work was conducted in a five-bladed Kaplan turbine model in which miniaturized autonomous sensors (SF Mini, developed at the Pacific Northwest National Laboratory, U.S.) measured fish-relevant hydraulic features. The modelling work involved flow simulations according to industry practices and the representation of fish trajectories through the simulated flow conditions. We compared both the experimental measurements and CFD outcomes and discussed the challenges and advantages of the modelling strategies, as well as the benefits for turbine engineers in need of incorporating effective design concepts to mitigate fish mortality through turbines.

Romero-Gomez, Pedro↗

CFD Simulations of the Supersonic Inflatable Aerodynamic Decelerator (SIAD) Ballistic Range Tests

A series of ballistic range tests were performed on a scaled model of the Supersonic Flight Demonstration Test (SFDT) intended to test the Supersonic Inflatable Aerodynamic Decelerator (SIAD) geometry. The purpose of these experiments were to provide aerodynamic coefficients of the vehicle to aid in mission and vehicle design. The experimental data spans the moderate Mach number range, $3.8-2.0$, with a total angle of attack ($alpha_T$) range, $10o-20o$. These conditions are intended to span the Mach-$alpha$ space for the majority of the SFDT experiment. In an effort to validate the predictive capabilities of Computational Fluid Dynamics (CFD) for free-flight aerodynamic behavior, numerical simulations of the ballistic range experiment are performed using the unstructured finite volume Navier-Stokes solver, US3D. Comparisons to raw vehicle attitude, and post-processed aerodynamic coefficients are made between simulated results and experimental data. The resulting comparisons for both raw model attitude and derived aerodynamic coefficients show good agreement with experimental results. Additionally, near body pressure field values for each trajectory simulated are investigated. Extracted surface and wake pressure data gives further insights into dynamic flow coupling leading to a potential mechanism for dynamic instability.

CFD modeling↗

UPDATES FROM THE INVOLUTE WORKING GROUP

The HFIR, RHF, and FRM II reactors represent a particular class of Research and Test Reactors that provide some of the most intense and continuous neutron fluxes for science, industry, and medical applications. These high-performance reactors have achieved compact cores by operating with Highly Enriched Uranium fuel (HEU, 235U/U ≥ 20 wt. %) and utilizing fuel plates curved as an involute. Due to the proliferation risks, the international community aims to reduce or eliminate, when possible, the use of HEU fuel in civilian facilities by converting them to a Low-Enriched Uranium fuel (LEU, 235U/U < 20 wt. %). Conversion of these reactors without significantly compromising their performance or safety is a challenging endeavor that can tremendously benefit from advanced computational tools and thus, eliminate unnecessary conservatism to ensure sufficient thermal margins. Therefore, models are being developed using modern Computational Fluid Dynamics (CFD) and Computational Structural Mechanics (CSM) software to evaluate the steady-state safety margins of various LEU designs instead of being reliant on the more traditional, conservative methods. To gain the confidence and acceptance of high-fidelity modeling by the nuclear regulators, Argonne National Laboratory (ANL) and the involute reactors have formed an informal scientific group, the Involute Working Group (IWG). The IWG facilitates inter-organizational collaboration on experimental benchmarking, code-to-code comparisons, and Verification and Validation (V&V). This paper describes some of the recent IWG efforts in validating software against the existing experimental data, as well as code-to-code comparisons of different software used by the IWG members.

Bergeron, Aurelien↗

Multi-Physics Simulations of Molten Chloride Fast Reactor using Nek5000 and PROTEUS-NODAL

This report documents the FY20 work to demonstrate a specific multi-physics capability within NEAMS tools to model molten chloride fast reactors (MCFR). Specifically, the CFD code Nek5000 and the neutronics code PROTEUS-NODAL were coupled off-line to calculate the delayed neutron precursor distribution within the flowing fuel salts in an MCFR core. An MCFR benchmark problem and a 3D test problem based on a conceptual MSR design were successfully solved through the coupled simulation of Nek5000 and PROTEUS-NODAL. In the coupled simulations for these test problems, Nek5000 provided high-quality flow field information, and PROTEUS-NODAL performed the neutron diffusion calculation along with the precursor drift model. The impact of precursor drift on the core status was also investigated. Additionally, the precursor drift model implemented in PROTEUS-NODAL was verified by making use of the reference precursor distribution generated from Nek5000. Results of these test problems suggest that the multi-physics capability of Nek5000 and PROTEUS-NODAL was properly developed for tracking delayed neutron precursor drift.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Validation of RANS Models for Predicting Bypass Flow in Prismatic VHTRs

In prismatic Very-High Temperature Reactors (VHTRs), gaps occur between neighboring fuel assemblies referred to as bypass gaps. This work aims to measure the flow distribution between the bypass gaps between neighboring assemblies and the coolant channels within the assemblies. Computational fluid dynamics (CFD) was done using Reynolds-Averaged Navier Stokes (RANS) modeling in STAR-CCM+ to assess the ability of RANS models to accurately capture this phenomena. The RANS results were compared to experimental worked performed by Seoul National University (SNU) and Korea Atomic Energy Research Institute (KAERI) for validation. The CFD results showed good comparison with the experimental data available from SNU and flow split was characterized for multiple configurations, inlet mass flow rates, and bypass gap sizes.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

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