Open RAN Security -Current Progress and Next Steps
5G Open RAN security talk given to the IEEE Open RAN Security Working Group.
5G↗
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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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A robust spectral element implementation of the $k - τ$ RANS model in Nek5000/NekRS
The $k - ω$ Reynolds Averaged Navier Stokes (RANS) model is one of the industry standard approaches for modeling of turbulent flows. It performs better than the $k - ϵ$ model for low Reynolds number flows and is also more suitable for boundary layers with adverse pressure gradients. Major drawback of the model, however, is that the asymptotic value of $ω$ at the walls is singular, necessitating the use of a contrived “sufficiently” large value for $ω$ as the boundary condition for its transport equation. Here, this invariably leads to the solution being sensitive to near wall grid spacing. While an acceptable solution for low order (finite volume) methods, the excessive near wall gradients lead to persistent numerical stability issues in high order codes. To alleviate the problem, specifically in the context of the high order spectral element code Nek5000, a regularized $k - ω$ approach was formulated in our prior work (Tomboulides et al., 2018). The formulation, however, relies on the use of wall distance and its gradients for modeling the closure terms and can pose problems for simulations in complex geometries. This work presents a novel implementation of the $k - τ$ RANS model in Nek5000, where $τ = 1/ω$, eliminating the need for regularization, owing to the asymptotically bounded behavior of the source terms in the $τ$ transport equation, and also eliminating dependence on wall distance. Robustness and stability of the $k - τ$ model is ensured through implicit treatment of the source terms and their careful numerical implementation and demonstrated through several cases aimed at verification and validation. Studies include both canonical and engineering relevant problems, viz., turbulent channel flow, pipe flow, backward facing step, flow over NACA 0012 airfoil and flow in a T-junction. Results from the $k - τ$ model are shown to be consistent with regularized $k - ω$ model and also with the $k - ω$ SST model in OpenFOAM (for select studies). Comparison with experimental data is also shown, where available, to bolster validation efforts for the $k - τ$ model implementation through prediction of key turbulent quantities of interest.
Nek5000↗
Data-Driven RANS Turbulence Closures for Forced Convection Flow in Reactor Downcomer Geometry
Recent progress in data-driven turbulence modeling has shown its potential to enhance or replace traditional equation-based Reynolds-averaged Navier-Stokes (RANS) turbulence models. Here, this work utilizes invariant neural network (NN) architectures to model Reynolds stresses and turbulent heat fluxes in forced convection flows (when the models can be decoupled). As the considered flow is statistically one dimensional, the invariant NN architecture for the Reynolds stress model reduces to the linear eddy viscosity model. To develop the data-driven models, direct numerical and RANS simulations in vertical planar channel geometry mimicking a part of the reactor downcomer are performed. Different conditions and fluids relevant to advanced reactors (sodium, lead, unitary-Prandtl-number fluid, and molten salt) constitute the training database. The models enabled accurate predictions of velocity and temperature, and compared to the baseline k–τ turbulence model with the simple gradient diffusion hypothesis, do not require tuning of the turbulent Prandtl number. The data-driven framework is implemented in the open-source graphics processing unit–accelerated spectral element solver nekRS and has shown the potential for future developments and consideration of more complex mixed convection flows.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Toward Verification of RANS Simulations of the T-Tube Modular Divertor Using Large Eddy Simulations of Impinging Turbulent Plane Jets
Turbulent impinging jets have been proposed to cool high heat flux plasma-facing components such as the solid tungsten target plates of the divertor in long-pulse magnetic fusion energy reactors. In particular, the T-tube modular divertor, originally developed by the ARIES Team, consists of two concentric cylindrical tubes where helium flows through a slot in the inner tube, forming an approximately planar jet that impinges upon and cools the inner surface of the pressure boundary (namely, the outer tube) and the ~15-cm 2 plasma-facing W target. The objective of this work is to demonstrate that large eddy simulations (LESs) accurately simulate the thermal transport in canonical flows that comprise the cooling flow in the T-tube, as well as validate temperatures from LES with experimental measurements in a simplified T-tube geometry. Wall‑resolved LESs, validated by experimental data and verified by direct numerical simulations (DNSs), provide benchmark data for two canonical flows in the T‑tube, namely, planar impinging and wall jets, for Reynolds numbers Re B = 4 × 10 3 to 2 × 10 4 . Our LES results are within 4% to 12% root-mean-square error (RMSE) of surface Nusselt number distributions (Nu) from experiments and DNSs. The validated LES results are then used as the ground truth to evaluate four Reynolds‑averaged Navier-Stokes (RANS) turbulence closures, namely, the k‑ω SST, realizable k‑ε, GEKO, and γ‑SST models. The k‑ω SST model has the best overall performance in terms of heat transfer, giving surface Nu within 12% RMSE of the LES results for high‑ReB impinging jets and reduced overprediction in the wall‑jet region. The GEKO model with default constants has the next best performance, providing slightly better Nu predictions for low ReB impinging jets (versus k-ω SST) but worse overall performance over the full range of ReB studied here. The realizable k‑ε turbulence model significantly overestimates turbulence near the stagnation point, while the γ‑SST model suppresses near‑wall production, biasing the simulations toward simulating laminar surface heat transfer. Simulations of the simplified T‑tube show that LES and RANS simulations with the k‑ω SST model give nearly identical average heat transfer coefficients (HTCs) over the impingement surface. The realizable k‑ε model predicts significantly lower wall temperatures due to overestimation of HTC in the outlet flow.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Eucalyptus grandis MYB‐Like and RAN‐Like Zinc Finger Proteins Display Dual Roles in Regulating Plant Immunity and Symbiosis Pathways
Plant roots live in constant contact with diverse microbes in the soil. Plant fitness, therefore, relies on signaling pathways that mount an effective immune response against pathogens while fostering mutualistic symbioses. Plant pathways, and specifically immune genes that may act as "switches," discriminating between pathogenic or mutualistic fungi, remain largely unknown. Using Eucalyptus grandis as a model system, we investigate alterations to the root transcriptomic landscape during pre-symbiosis with either the pathogen Armillaria luteobubalina or the mutualistic fungus Pisolithus microcarpus. Comparative analyses identified three strongly counter-regulated genes that may act as immune switches to accommodate or to repress fungal colonization. We characterized two of these, a MYB-like and RAN-like zinc finger protein, using a transgenic approach and demonstrated that they have bifunctional roles in the regulation of cell death and a hypersensitive-like response, depending on the lifestyle of the associated fungus. Using co-expression network analysis, we identified hypothetical pathways correlated to these genes. We functionally validated these predictions using plants with transgenic roots with increased or decreased transcription of these genes, thereby showing the power of co-expression networks as an a priori approach to identify key immune response pathways in plants. Overall, our results demonstrate that prior to physical contact with microbes, MYB-like and RAN-like zinc finger proteins are key regulators of plant immune signaling that respond to fungal signals and enable or repress symbiotic establishment.
mycorrhizal fungi↗
Demonstration of RANS models with wall functions in the spectral element code Nek5000
The spectral element based computational fluid dynamics (CFD) code Nek5000 has been traditionally used for high-fidelity applications, such as direct numerical simulation (DNS) and large eddy simulation (LES). These techniques require very fine numerical resolution to accurately capture turbulent fluctuations which can be prohibitively expensive for users without access to leadership class computing facilities. For broader application and adoption, significant effort has been invested to develop Reynolds-averaged Navier–Stokes (RANS) capabilities in Nek5000. Here, this work presents details of the implementation and demonstration of the standard wall functions for the κ–τ model in Nek5000. Results using the wall-modeled approach are compared to a wall-resolved approach for cases with negligible pressure gradient, viz., channel flow, pipe flow and flow in a reactor subchannel. Results show reasonably good agreement between the two approaches for friction factor and Nusselt number. Some expected differences are identified near the wall. These cases demonstrate the potential for significant computational savings by using much coarser meshes for the wall-modeled approach, with only minor differences between the predicted result. Additionally, several Reynolds numbers up to 1,000,000 are demonstrated for pipe flow and predicted friction factors and Nusselt numbers compared well to available correlations, with the worst below 10%. As the Reynolds number is increased, better agreement is observed between the correlations and the wall-modeled approach. In addition, flow in a molten salt fast reactor (MSFR) core is considered which features an adverse pressure gradient and flow separation. It showcases the inability of standard wall functions to accurately predict flows with adverse pressure gradients. The results, however, match reasonably well in trend in regions of the flow where the boundary layer is attached. Ongoing research is dedicated to include a pressure gradient correction to wall functions to improve the accuracy of flows with separation or reattachment and adverse or favorable pressure gradients.
42 ENGINEERING↗
Machine Learning–Guided Boolean Matrix Inference for Real-Time O-RAN Conflict Detection
Open Radio Access Networks (O-RAN) are emerging, software-driven cellular architectures that promote flexibility by enabling components from different vendors to interoperate. Multiple control applications called xApps can independently adjust network parameters in near real time, often without awareness of each other's actions. This creates a system highly prone to unintended conflicts and performance degradation due to the inherent complexity of such openness. To model such systems and ultimately prevent or mitigate xApp conflicts, it is essential to understand the dynamic relationships between xApps (A), the control parameters they adjust (P), and the resulting KPI responses (K). While the mappings from A to P and from K to A can often be derived from xApp specifications, the relationship from P to K is typically hidden within the system’s dynamics and must be inferred from observed data. We propose a novel data-driven Boolean inference framework that uncovers the hidden P?K dependencies using machine learning and interpretable rule induction. Continuous parameters and KPIs are first binarized using decision tree classifiers, and a binary influence matrix L is then inferred by solving Boolean matrix equations over time. This compact representation improves interpretability and enables real-time tracking of dynamically evolving parameter-KPI dependencies. We demonstrate the effectiveness of our method in a realistic mobile handover scenario, where it accurately recovers the underlying logic and enables proactive conflict detection.
42 - ENGINEERING↗
Conflict Detection in Open Radio Access Network (O-RAN) Control
A brief overview of the O-RAN approach to 5G cellular networking, discussion of the problem of conflicts among control functions under this paradigm, and research toward an approach detecting these conflicts using machine learning. This talk provides a high-level overview of academic research associated with an ongoing LDRD.
5G↗
Nek5000: improvements in the available RANS models, meshing, tutorials, and training
This year, the Nuclear Energy Advanced Modeling Simulation program (NEAMS) thermal-hydraulics report for Nek5000 NRC- and verification and validation (V&V)-driven development focuses on following areas of code application and improvement. First we have continued improvements of RANS modeling capabilities in Nek5000 including improved k-tau model focusing mostly on wallfunction initial implementation with spectral element method (SEM) and initiating investigation of an alternative approach XSEM that greatly reduces discretization errors.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Updates to Nek5000: RANS wall functions, NRC support, and documentation
As a key part of the U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program (NEAMS), the next generation of tools for nuclear reactor design are being developed. A primary metric for success of this program is the adoption of those tools by industry stakeholders. To help meet this metric for Nek5000, development efforts this year have focused on the expansion of the available Reynolds-averaged Navier-Stokes (RANS) turbulence models to include wall function models, continued support of the U.S. Nuclear Regulatory Commission in simulating a hydrogen mitigation benchmark experiment, and expansion of the Nek5000 documentation to enhance the code’s usability. The implementation of wall functions is intended to significantly decrease time to-solution for a wide range of problems and it has been identified as an important feature by stakeholders across the nuclear community. The initial implementation of standard and pressure corrected wall functions has been tested in Nek5000 on the classical problems of channel flow and a backward facing step. It has also been tested on a 2D molten salt fast reactor core and a T-junction. The recommended formulation of choosing y + = 30 as a boundary value combined with a Neumann-Neumann formulation of the boundary condition for k and τ produces the most consistent results compared to a wall resolved approach. The collaboration with the NRC is a continuing exercise that has been ongoing for multiple years. This year we have concluded investigations into appropriate inlet conditions, showing that fully developed turbulent conditions are adequate for the full PANDA domain. We have also concluded simulations for an unobstructed jet and are now refocusing to the original obstructed jet case. The expansion of the code documentation has also been an ongoing effort over the past few years to address feedback from the various stakeholders. The documentation now more fully covers many of the available features and closes identified SQA gaps. Finally we report on three training sessions that were offered over the past year in an effort to expand the Nek5000 user base.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
RANS Simulation of Variable Density Turbulent Round Jets with Coflow using xRAGE Hydrodynamic Code and BHR Turbulence Models
This work for the fiscal year 2023 (FY23) is a continuation of previous efforts to evaluate the BHR turbulence models for their ability to accurately simulate variable density turbulent round jets with coflow. As before, RANS simulations are carried out using the xRAGE hydrodynamic code. The following are some of the previous findings. Israel showed that i) the symmetry boundary conditions for the BHR models in axisymmetric simulations were in error, ii) three grids of different resolutions did not lead to converging solutions, and iii) BHR 3.1 simulation exhibited instabilities and did not reach a steady state. Saenz and Rauenzahn derived and implemented into xRAGE the correct BHR boundary conditions at the symmetry axis. Cline conducted sensitivity studies with various parameters including the BHR models (versions 2, 3.1 and 4), gravity, material pressure, specific heat, initial turbulent kinetic energy and initial turbulent length scale, and found that the largest factor impacting on simulation results was the BHR model version, followed by the initial turbulent length scale. In addition, freeze boundary conditions at the exit and the side wall of the computational domain were used to remove anomalous flow behavior. Cline adjusted the inlet jet velocity, initial turbulent kinetic energy and initial turbulent length scale to obtain the best reasonable match with the experimental data of Charonko and Prestridge. It was found that the BHR 2 and 3.1 models performed in a similar manner, but the BHR 2 model produced much lower levels of density-specific-volume covariance and turbulent kinetic energy. The main focus for the FY23 is to study the effects of computational parameters related to the boundary conditions, mesh, domain size and timestep size. The reasoning behind this is that, unless simulation results can be shown to be reasonably independent from the aforementioned computational parameters, it would be difficult to attribute any discrepancies between simulation and experimental results to turbulence models. This important aspect has largely been overlooked in the previous years, and therefore will be studied comprehensively here. Additionally, effects of varying the initial turbulent length scale will be examined because it was previously identified as a major factor affecting the flow fields.
42 ENGINEERING↗
Determining Exact RANS Operators with the Macroscopic Forcing Method (Final Report)
This report contains a compilation of key results and findings from the ACT project “Determining Exact RANS Operators with the Macroscopic Forcing Method.” The Macroscopic Forcing Method (MFM), a numerical tool for determining closure operators, is used to measure eddy diffusivity moments in Rayleigh-Taylor (RT) instability. It is first applied to low-Atwood 2D RT instability; that work is then extended to 3D RT at different finite Atwood numbers. It is found that nonlocality is important for modeling the mean scalar transport closure operator in RT mixing. Additionally, work is done to improve the statistical convergence of MFM for chaotic problems like RT mixing.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Quantitative assessment of eddy viscosity rans models for turbulent mixed convection in a differentially heated plane channel
Turbulent mixed convection between two vertical, infinite parallel plates at different temperatures is studied using various two-equation turbulence models. The numerical simulations are performed at a turbulent Reynolds number of Re τ = 150 and a Grashof number of Gr = 9.6 × 10 5 . Comparisons are made against the highly trusted DNS results. Consistent with the DNS approach, the current simulations are performed using constant properties and the Boussinesq approximation to predict the influence of buoyancy. Previous studies have provided assessments of two-equation turbulence models for various scenarios, but often rely on a qualitative “eye” test in order to determine the most appropriate model to predict a given flow. This study aims to provide a new form of quantitative assessment that accounts for both the physics captured by the turbulence model as well as the magnitude of the system response quantities (SRQ) using a modified symmetric mean absolute percent error (SMAPE) method. This method is designed to be approachable to researchers at any level and can be applied to system response quantities from multiple research fields. Uncertainty quantification is also performed to determine the discretization error for each turbulence model. Recommendations are made as to which turbulence models best capture the physics – hydrodynamically and thermally – using both local and global validation metrics. Lastly, a sensitivity analysis is performed on the damping functions used in the most accurate models. This underpins the potential of model developments and adjustments most worth pursuing for buoyant flows. Finally, this framework provides a more physics-based comparative analysis of the selected turbulence models.
42 ENGINEERING↗
Pore-Scale Prediction of the oxygen effective diffusivity in porous battery electrodes using the ran
Explore the source record for details and available documents.
Wang, Fangzhou↗
RANS turbulence model development using CFD-driven machine learning
Not Available
Zhao, Yaomin (ORCID:0000000295975761)↗
A method for examining ensemble averaging forms during the transition to turbulence in HED systems for application to RANS models
This paper discusses a strategy to initialize a two-dimensional (2D) Reynolds-averaged Navier–Stokes model [LANL's Besnard–Harlow–Rauenzahn (BHR) model] in order to describe an unsteady transitional Richtmyer–Meshkov (RM)-induced flow observed in on-going high-energy-density ensemble experiments performed on the OMEGA-EP facility. The experiments consist of a nominal single-mode perturbation (initial amplitude a 0 ≈ 10 and wavelength $λ$ = 100μm) with target-to-target variations in the surface roughness subjected to the RM instability with delayed Rayleigh–Taylor in a heavy-to-light configuration. Our strategy leverages high-resolution three-dimensional (3D) implicit large eddy simulations (ILES) simulations to initialize BHR-relevant parameters and subsequently validate the 2D BHR results against the 3D ILES simulations. A suite of five 3D ILES simulations corresponding to five experimental target profiles is undertaken to generate an ensemble dataset. Using ensemble averages from the 3D simulations to initialize the turbulent kinetic energy in the BHR model ( K 0 ) demonstrates the ability of the model to predict the time evolution of the interface as well as the density-specific-volume covariance, b . To quantify the sensitivity of the BHR results to the choice of K 0 and the initial turbulent length scale, S 0 , we execute a parameter sweep spanning four orders of magnitude for both S 0 and K 0 , generating a parameter space consisting of 26 simulations. The Pearson's correlation coefficient is used as a measure of discrepancy between the 2D BHR and 3D ILES simulations and reveals that the ranges 8≲S 0 ≲20 μm and 10 9 ≲K 0 ≲10 10 cm 2 /s 2 produce predictions that agree best with the 3D ILES results.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Validation of RANS-Based Turbulence Models Against High-Resolution Experiments and DNS for Buoyancy-Driven Flow with Stratified Fronts
Not provided.
Nuclear Science & Technology↗