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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

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↗
DOE OSTI2024

An Investigation of LES Wall Modeling for Rayleigh–Bénard Convection via Interpretable and Physics-Aware Feedforward Neural Networks with DNS

Abstract The traditional approach of using the Monin–Obukhov similarity theory (MOST) to model near-surface processes in large-eddy simulations (LESs) can lead to significant errors in natural convection. In this study, we propose an alternative approach based on feedforward neural networks (FNNs) trained on output from direct numerical simulation (DNS). To evaluate the performance, we conduct both a priori and a posteriori tests. In the a priori (offline) tests, we compare the statistics of the surface shear stress and heat flux, computed from filtered DNS input variables, to the stress and flux obtained from the filtered DNS. Additionally, we investigate the importance of various input features using the Shapley additive explanations value and the conditional average of the filter grid cells. In the a posteriori (online) tests, we implement the trained models in the System for Atmospheric Modeling (SAM) LES and compare the LES-generated surface shear stress and heat flux with those in the DNS. Our findings reveal that vertical velocity, a traditionally overlooked flow quantity, is one of the most important input features for determining the wall fluxes. Increasing the number of input features improves the a priori test results but does not always improve the model performance in the a posteriori tests because of the differences in input variables between the LES and DNS. Last, we show that physics-aware FNN models trained with logarithmic and scaled parameters can well extrapolate to more intense convection scenarios than in the training dataset, whereas those trained with primitive flow quantities cannot. Significance Statement The traditional near-surface turbulence model, based on a shear-dominated boundary layer flow, does not represent near-surface turbulence in natural convection. Using a feedforward neural network (FNN), we can construct a more accurate model that better represents the near-surface turbulence in various flows and reveals previously overlooked controlling factors and process interactions. Our study shows that the FNN-generated models outperform the traditional model and highlight the importance of the near-surface vertical velocity. Furthermore, the physics-aware FNN models exhibit the potential to extrapolate to convective flows of various intensities beyond the range of the training dataset, suggesting their broader applicability for more accurate modeling of near-surface turbulence.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Emulator of PR‐DNS: Accelerating Dynamical Fields With Neural Operators in Particle‐Resolved Direct Numerical Simulation

Abstract Particle‐resolved direct numerical simulations (PR‐DNS) play an increasing role in investigating aerosol‐cloud‐turbulence interactions at the most fundamental level of processes. However, the high computational cost associated with high resolution simulations poses considerable challenges for large domain or long duration simulation using PR‐DNS. To address these issues, here we present an emulator of the complex physics‐based PR‐DNS developed by use of the data‐driven Fourier Neural Operator (FNO) method. The effectiveness of the method is showcased by presenting turbulence and temperature fields in a two‐dimensional space. The results demonstrate high accuracy at various resolutions and the emulator is two orders of magnitude cheaper in terms of computational demand compared to the physics‐based PR‐DNS model. Furthermore, the FNO emulator exhibits strong generalization capabilities for different initial conditions and ultra‐high‐resolution without the need to retrain models. These findings highlight the potential of the FNO method as a promising tool to simulate complex fluid dynamics problems with high accuracy, computational efficiency, and generalization capabilities, enhancing our understanding of the aerosol‐cloud‐precipitation system.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

DNS Of the ignition process of n-heptane/air premixed combustion with low-temperature chemistry in turbulent boundary layer

In the present work, three-dimensional direct numerical simulation (DNS) of n-heptane/air premixed combustion in turbulent boundary layer was performed to explore the near-wall ignition process with low -temperature chemistry. A reduced chemical mechanism with 58 species and 387 elementary reactions for n-heptane combustion was used in the DNS. The general characteristics of the ignition process near the wall were examined. Here, it was found that low-temperature ignition (LTI) dominates the upstream region, and high -temperature ignition (HTI) appears in the downstream region. The ignition process and the low-temperature chemistry pathways of the DNS are compared with those of a corresponding laminar case. It was found that the ignition process was affected by turbulence, which results in thickened reaction zones. However, the carbon flow analysis of low-temperature chemistry showed that turbulence rarely affects the low-temperature chemistry pathway. The combustion modes of various regions were scrutinized based on the budget terms of species transport equations and the chemical explosion mode analysis (CEMA). It was shown that the reaction term of RO 2 is significant during the LTI process of the upstream region, and the reaction terms of CH 2 O and CO 2 are evident in the downstream region, indicating the occurrence of HTI. It was also shown that auto-ignition is dominant in the upstream region. With increasing streamwise distance, the contribution of flame propagation increases, which takes over that of auto-ignition in the near-wall region.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

(Towards) DNS of a Laboratory Lean CH4/H2 Low-Swirl Flame Impinging on an Inclined Wall

Due to downsizing trends, flame-wall interaction (FWI) is increasingly prominent in gas turbines (GTs). FWI has direct consequences on flame stabilization and pollutant emissions, but it is not well understood in turbulent flows representative of GTs. We present results from a direct numerical simulation (DNS) of a turbulent CH4/H2 model GT low-swirl laboratory-scale flame interacting with an inclined wall. The results from the laboratory flame include simultaneous measurements of velocity using stereo particle imaging velocimetry and OHxCH2O planar laser induced fluorescence. The adaptive-mesh refinement solver PeleLMeX is used, with 24-species, 105-reaction reduced Aramco chemical kinetics mechanism. The premixed fuel-air mixture consists of hydrogen-enriched methane with 70% hydrogen volume fraction and 0.4 equivalence ratio. The inflow is prescribed to match experimental measurements at the burner exit. Karlovitz and turbulent Reynolds numbers are 300 and 400, respectively. The simulation and experimental results show excellent agreement. The flame features a bowl-shape stabilization, with a corrugated, continuous flame front at the leading edge, followed by fragmented reaction zones downstream. A large diffuse cloud of CH2O is formed downstream of the quenching point. The simulation results indicate that the cloud of CH2O is the result of incomplete methane combustion, with CH2O "leaking" from the locally quenched reaction zones.The DNS provides fine-grain resolution of turbulence-flame-wall interaction that cannot be captured with experimental measurements. With access to the entire solution vector at each cell of the computational domain, the local quenching.

flame-wall interactions↗
DOE OSTI2024

DNS of ignition and flame stabilization in a simplified gas turbine premixer

With the increasing need for fuel flexibility, mitigation of auto-ignition (AI) inside gas turbine (GT) premixers becomes crucial. They must be designed to yield a sufficiently homogeneous fuel-air mixture to achieve low emissions while at the same time avoiding the occurrence of AI and subsequent flame stabilization. This challenge requires a detailed understanding of turbulent mixing and chemistry interactions. In the present work, a direct numerical simulation (DNS) of an array of jets in crossflow (JICF), representative of an industrial GT premixer, is reported to shed light on these complex phenomena. It is found that AI kernels form in the aft part of the premixer and coalesce into a flame front that then propagates upstream, mainly through the boundary layer, and successively engulfs the jets. This, therefore, suggests a significant role of the jet array pattern on the flame stabilization. It is noted that AI kernels continue to form independently during the whole time of the simulation. To clarify the contribution of AI and diffusion in the ignition kernels and the main flame, chemical explosive mode analysis (CEMA) is employed jointly with a kernel tracking algorithm. It is found that during the initial formation of the flame, many ignition kernels form in mixtures with low scalar dissipation rate and large contribution from AI mode. As they quickly grow, they merge into a single flame front that becomes increasingly more diffusion-assisted over time, balancing the AI mode. Turbulence is shown to have a significant enhancing effect in lean premixed flames, but further analysis is required to fully characterize it. These findings are relevant for the industrial premixer studied, and also for novel micromix concepts that may be used in the next generation of GT combustion systems.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Improving transition to IPv6-only via RFC8925 and IPv4 DNS Interventions

Nine years have passed since the American Registry for Internet Numbers exhausted its allocation of Internet Protocol version 4 (IPv4) addresses, and four years have passed since the United States Government mandated federal agencies to complete the transition to Internet Protocol version 6 (IPv6). Despite the IPv4 address shortage and IPv6 mandate, Federally Funded Research and Development Centers (FFRDCs) are still struggling to sunset IPv4. As demonstrated on SC23’s SC23v6 wireless network, newer tooling such as RFC8925 allows clients to disable their IPv4 protocol stack while retaining legacy IP connectivity via the RFC6145 translation algorithm. However, SC23v6 wireless clients without RFC8925 support or a disabled IPv6 stack would continue to receive internet access via legacy IPv4. This paper introduces a method of using poisoned IPv4 Domain Name System (DNS) records to gracefully inform IPv4-only clients at SC24’s SC24v6 wireless network about their inability to use the current version of internet protocol, with a goal of minimal impact to RFC8925 and dual-stack clients. When implemented as designed, this method may improve supportability and user experience of IPv6-only deployments at FFRDCs.

Costello, Thomas M↗
DOE OSTI2024

DNS of Flame Stabilization Dynamics of a Swirl-Stabilized Spray Burner Using Sustainable Aviation Fuels

Concern for emission reduction has motivated the development of new cost-effective alternative sustainable aviation fuels (SAFs). Drop-in SAFs with blends of the certified and the alternative fuels are beneficial because they do not require engine modifications for use in current aviation engines. Combustion characteristics are of particular concern when comparing a new fuel with Jet-A. Lean blow-off and flame stabilization have been identified to be governed by the fuel propensity to autoignition, i.e. derived cetane number. However, fundamental investigation is required to identify the impact of derived cetane number on the combustion mode of flame stabilization in a realistic combustor. The combustion mode has also a direct impact on turbulent combustion modeling closures. DNS simulations are performed in the low-Mach solver of the Pele Suite called PeleLMeX. Lagrangian multi-phase modeling is used to capture the liquid spray injection of Jet-A (reference fuel) and C1 as a representative of a low cetane number SAF. Adaptive Mesh Refinement (AMR) is used to enable a more efficient simulation of a more realistic domain size and embedded boundary treatment is used to model a bluff-body geometry. Local extinction and edge flame propagation were observed for both fuels. The edge flame propagation mode was quantified in terms of a Damkohler number defined as the ratio between progress variable reaction rate and its diffusive flux. Initial analysis suggests that a mixed mode combustion occurs for the edge flame propagation, with flame propagation assisted by ignition and autoignition co-existing for both Jet-A and C1 flames. The analysis of the extinction region shows a larger progress variable for Jet-A which can further increase the local displacement speed and present a faster reignition of the stoichiometric mixture fraction.

adaptive mesh refinement↗
DOE OSTI2022

DNS of Hydrodynamic Instabilities of Laminar H2/O2/N2 Flames at Elevated Pressure

The atypical combustion properties of hydrogen have long provided an interest for hydrogen-enriched combustion, emphasized in recent years by increasingly stringent emission regulations. Significant work has been focused on the small hydrocarbon(C1-C3)/hydrogen blends, but much less is known about the effect of hydrogen on heavier hydrocarbon combustion, of interest for the aviation and automotive industry. In this work, we perform direct numerical simulations (DNS) of spherically expanding laminar n-dodecane/H2 flames in a constant-volume vessel at elevated pressure and a range of hydrogen seeding levels. A low Mach number model is used to represent the gas and flame dynamics allowing for a temporally varying, spatially homogeneous pressure field, while also enabling numerical evolution of the system numerically at time step sizes governed by the advective CFL limit rather than acoustic processes. We use an adaptive mesh refinement (AMR) approach to tackle the large separation of scales associated with high pressure premixed flame surfaces propagating in a laboratory-scale closed domain. We incorporate detailed chemistry and transport models for the reacting flow and focus the analysis on the effects of the pressure rise on the flame propagation characteristics and morphology as the hydrogen content is increased. The presence of fast diffusive H2 and the pressure rise results in dramatic thinning of the flame and the potential onset of hydrodyanmic and theromdiffusive instabilities. We assess the potential role of these instabilities on the ability to accurately measure laminar burning speed experimentally based on the mean flame surface propagation speed.

high pressure↗
DOE OSTI2022

PARTICLE RESOLVED DNS STUDY OF TURBULENCE EFFECTS ON HYPORHEIC MIXING IN RANDOMLY PACKED SEDIMENT BEDS

Pore-resolved direct numerical simulations (DNS) are used to investigate the interactions between stream-water flow turbulence and groundwater flow through a porous sediment bed in the hyporheic zone. Two permeability Reynolds numbers (2.56 and 5.17), representative of aquatic systems and representing ratio of permeability to viscous length scales, were simulated to understand its influence on the momentum exchange at the sediment-water interface (SWI). A doubleaveraging methodology is used to compute the Reynolds stresses, form-induced stresses, and pressure fluctuations. It is observed that both shear layer and turbulent shear stress penetration increases with ReK. Reynolds and form-induced bed-normal stresses increase with ReK. The peak values of the form-induced stresses for the lower (2.56) and higher (5.17) ReK happen within the top layer of the sediment bed. The sum of turbulent and form-induced pressure fluctuations, analyzed at their respective zero-displacement planes, are statistically similar and can be well approximated by a t location-scale distribution fit providing with a model that could potentially be used to impose boundary conditions at the SWI in reach scale simulations.

Karra, Shashank↗
DOE OSTI2023

DNS of a Simplified Gas Turbine Premixer: Auto-Ignition and Flame Stabilization

With the increasing need for fuel-flexibility, an understanding of auto-ignition inside gas turbine premixers is crucial. Direct numerical simulation (DNS) is a great tool to reveal the fine grain details of physics inside the premixer and guide the choice of the models to use for less expensive simulations. We present numerical simulations of a simplified and downscaled premixer, with multiple air jets in rich fuel crossflow. The simulations show intense fuel-air mixing and flame-turbulence interaction. We examine flow acceleration by the incoming jets, and the combustion within the device. We observe low-temperature and high-temperature combustion signatures, and compute the flame index to quantify local stabilization modes.

combustion↗
DOE OSTI2022

GPU-accelerated DNS of compressible turbulent flows

Here, this paper explores strategies to transform an existing CPU-based high-performance computational fluid dynamics solver, HyPar, for compressible flow simulations on emerging exascale heterogeneous (CPU+GPU) computing platforms. The scientific motivation for developing a GPU-enhanced version of HyPar is to simulate canonical turbulent flows at the highest resolution possible on such platforms. We show that optimizing memory operations and thread blocks results in 200x speedup of computationally intensive kernels compared with a CPU core. Using multiple GPUs and CUDA-aware MPI communication, we demonstrate both strong and weak scaling of our GPU-based HyPar implementation on the NVIDIA Volta V100 GPUs. We simulate the decay of homogeneous isotropic turbulence in a triply periodic box on grids with up to 1024 3 points (5.3 billion degrees of freedom) and on up to 1,024 GPUs. We compare the wall times for CPU-only and CPU+GPU simulations. The results presented in the paper are obtained on the Summit and Lassen supercomputers at Oak Ridge and Lawrence Livermore National Laboratories, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Computation of Richardson number and entrainment in a turbulent plume using DNS

This presentation will be presented by Pierre Carlotti (French foreign national) at the 1st European Fluid Dynamics Conference (EFDC1) in Aachen, Germany in mid-September. The work focuses on fundamental questions pertaining to entrainment processes in plumes. I am included as a co-author because Pierre used my previously published data to further develop theoretical estimates.

Carlotti, Pierre↗