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2025 Advances in NekRS: Supporting improved performance for nuclear applications

This report presents several 2025 advancements in NekRS, a high-fidelity spectral element CFD code developed at Argonne National Laboratory to support the NEAMS thermal-hydraulics program. The forthcoming v25 release consolidates several of these advances, adding new features for portability across heterogeneous GPU architectures, real-time in situ visualization, improved turbulence modeling, and conjugate heat transfer coupling. Over the past year, NekRS has demonstrated strong scalability and performance on DOE’s leading exascale platforms, including Aurora and Frontier, confirming its readiness for some of the largest and most complex simulations attempted to date. These achievements provide a powerful new platform for high-fidelity data generation, which in turn supports the development and validation of advanced closure models critical for reactor safety and design. Significant algorithmic innovations have also been introduced. A new global runtime h-refinement capability simplifies workflows by reducing mesh preparation burdens and enabling coarse-to-fine restarts. Building on this, a novel multigrid strategy was implemented to accelerate pressure and transport solves at scale, addressing long-standing bottlenecks in exascale CFD. Together, these developments improve both the efficiency and accessibility of high-fidelity simulations for reactor-relevant problems. Collectively, these enhancements represent a major step forward in simulation technology, positioning NekRS as a cornerstone of NEAMS efforts to enable accurate, efficient, and scalable high-fidelity analysis of advanced nuclear systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Advanced Computing Annual Report 2025 [Slides]

In Fiscal Year (FY) 2025, the National Laboratory of the Rockies (NLR) continued to advance computing as a cornerstone of energy innovation, expanding the Kestrel high-performance computing (HPC) system to 56 peak petaflops. This growth strengthened Kestrel's role as a national asset for applied energy research, enabling larger, more complex simulations and accelerating the integration of artificial intelligence (AI) methods across the laboratory's computing portfolio. In FY 2025, AI was a component of most projects running on Kestrel, underscoring its central role in modern energy science and engineering. Kestrel supported a broad and diverse set of 507 modeling and simulation projects, engaging 855 researchers across the U.S. Department of Energy's (DOE's) Office of Critical Minerals and Energy Innovation (CMEI) portfolio and other offices, as well as partners from industry, academia, and utilities. These efforts span critical materials discovery, energy systems modeling, grid modernization, advanced manufacturing, and other areas essential to strengthening U.S. energy security and competitiveness. Together, these collaborations produced 708 technical outputs, including 293 peer-reviewed publications, reflecting both the depth and impact of the science enabled by NLR's computing capabilities. This year's report highlights the growing importance and benefit of AI throughout NLR's research programs and features work by early career researchers who are helping shape the future of computing-enabled energy innovation. Explore these sections and the many project successes captured in the pages that follow.

97 MATHEMATICS AND COMPUTING↗

Develop and verify soil/structure interaction for pile/foundation interaction

Phase II of the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) project was used to verify the implementation of a new soil-structure interaction (SSI) model for use within offshore wind turbine modeling software. The REDWIN Macro-element model implemented and verified in this study enables a computationally efficient way to model the linear and nonlinear SSI problem, including hysteretic damping, of a monopile structure. The modeling approach was integrated into several modeling tools and a series of increasingly complex simulations was conducted using the IEA 10MW reference turbine mounted on a monopile support structure to verify the coupling between the tools and the REDWIN Macro-element SSI model. This campaign includes only numerical verification between various software and modeling approaches so no experimental measurements are available. The load cases (LC) considered include: LC1 – static response of the tower and substructure LC2 – frequency and mode-shape analysis of the tower and substructure LC3 – response of the tower and substructure due to wind-only loading LC4 – response of the tower and substructure due to wave-only loading LC5 – response of the tower and substructure due to wind and wave loading. Detailed properties of the modeled system are found in the following reference, “Bergua, Roger, Amy Robertson, Jason Jonkman, and Andy Platt. 2021. "Specification Document for OC6 Phase II: Verification of an Advanced Soil-Structure Interaction Model for Offshore Wind Turbines.” Golden, CO: National Renewable Energy Laboratory. NREL/TP-5000-79938. https://www.nlr.gov/docs/fy21osti/79938.pdf. Details on the results from the OC6 Phase II project can be found in the following reference, “Bergua R, Robertson A, Jonkman J, et al. OC6 Phase II: Integration and verification of a new soil–structure interaction model for offshore wind design.” Wind Energy. 2022;25(5):793-810. doi:10.1002/we.2698

17 WIND ENERGY↗

Streamlining Ocean Dynamics Modeling with Fourier Neural Operators: A Multiobjective Hyperparameter and Architecture Optimization Approach

Training an effective deep learning model to learn ocean processes involves careful choices of various hyperparameters. We leverage DeepHyper’s advanced search algorithms for multiobjective optimization, streamlining the development of neural networks tailored for ocean modeling. The focus is on optimizing Fourier neural operators (FNOs), a data-driven model capable of simulating complex ocean behaviors. Selecting the correct model and tuning the hyperparameters are challenging tasks, requiring much effort to ensure model accuracy. DeepHyper allows efficient exploration of hyperparameters associated with data preprocessing, FNO architecture-related hyperparameters, and various model training strategies. We aim to obtain an optimal set of hyperparameters leading to the most performant model. Moreover, on top of the commonly used mean squared error for model training, we propose adopting the negative anomaly correlation coefficient as the additional loss term to improve model performance and investigate the potential trade-off between the two terms. The numerical experiments show that the optimal set of hyperparameters enhanced model performance in single timestepping forecasting and greatly exceeded the baseline configuration in the autoregressive rollout for long-horizon forecasting up to 30 days. Utilizing DeepHyper, we demonstrate an approach to enhance the use of FNO in ocean dynamics forecasting, offering a scalable solution with improved precision.

97 MATHEMATICS AND COMPUTING↗

Achieving ultrahigh accuracy with a body pointing CMG/RW control system.

The purpose of the Large Space Telescope (LST) program is to place a three-meter diffraction limited telescope in a 270-nautical mile orbit in order to perform astronomical observations that are not presently possible with earth bound telescopes due to atmospheric obscuration. In order to determine whether the stringent pointing requirements could be met, a complex simulation model was defined which consisted of detailed dynamic representations of control moment gyros (CMGs) and reaction wheels including their noise characteristics, dynamic sensor representations with sensor noise, shock mounts for the CMG actuators, and a detailed flexible body structural model with all significant vehicle and solar panel bending modes. On the basis of both stability and performance studies utilizing this model, it was determined that a body pointing system will meet LST requirements.

Rybak, S. C.↗

An ultrahigh-accuracy body pointing system for the Large Space Telescope

The Large Space Telescope (LST) program is aimed at placing a three-meter diffraction-limited telescope in a 270-nm orbit to perform astronomical observations that are not possible with earth-based telescopes. A complex simulation model is described which was developed to determine whether the stringent pointing stability requirements could be met. The model (programmed on a hybrid computer) included detailed dynamic representation of control moment gyros (CMGs) and reaction wheels (RWs), including their noise characteristics; dynamic sensor representation (including noise); shockmounts for the CMG actuators; detailed representation of an image motion compensation system; and a detailed flexible body vehicle model. Stability and performance studies based on the simulation model showed that the body pointing system will meet LST requirements in the presence of CMG vibrational disturbances and sensor noise. The recommended system consists of three orthogonally mounted RWs for primary short-term control, and a cluster of CMG actuators for continuous RW desaturation and vehicle maneuvering.

Rybak, S. C.↗

Ultrahigh-accuracy body-pointing system for the Large Space Telescope

The Large Space Telescope (LST) is a 3-m diffraction-limited telescope. Pointing stability requirements necessary to assure diffraction-limited images are plus or minus 0.005 arc-sec, over possible experiment observation times of several hours. In order to determine whether these stringent pointing requirements could be met, a complex simulation model was defined which consisted of detailed dynamic representations of control moment gyros (CMGs) and reaction wheels (RWs), including their noise characteristics, dynamic sensor representations with sensor noise, shock mounts for the CMG actuators, a detailed representation of an image motion compensation (IMC) system, and a detailed flexible body structural model with all significant vehicle and solar panel bending modes. On the basis of both stability and performance studies utilizing this model, it was determined that a body-pointing system will meet LST requirements in the presence of CMG vibrational disturbances and sensor noise. The recommended system consists of three orthogonally mounted RWs for primary short-term control, and a cluster of CMG actuators for continuous RW desaturation and vehicle maneuvering.

Rybak, S. C.↗

Numerical analysis of some supersonic viscous flows related to inlet and nozzle systems

A numerical method originally developed for three-dimensional supersonic inlet flow calculations is extended and applied to the study of two-dimensional and three-dimensional flows associated with arbitrary propulsion systems. The method is based on the forward spatial marching solution of a reduced form of the three-dimensional steady Navier-Stokes equations in which streamwise pressure gradients are retained in both the subsonic and supersonic regions. The present paper briefly describes the analysis and then shows three applications. In the first application, a wall transpiration study has been performed for the two-dimensional shock wave/turbulent boundary layer interaction flow field with application to an inlet configuration. The second application treats a rectangular high speed inlet with a swept sideplate including the effects of sideplate spillage. Finally, the method is utilized to analyze the interaction of an under-expanded supersonic jet with an ambient flow. Computed results are examined and compared with available experimental measurements. It is demonstrated that the present numerical method is capable of numerically simulating complex two- and three-dimensional flows relevant to hypersonic propulsion systems in a manner which both shows good agreement with data when such data is available, and which shows the complex flow features in the absence of data.

Kim, Y.-N.↗

Combustor-diffuser interaction program

A collection of empirical and analytical design methodology on combustor-diffuser systems was completed. A fully elliptic code was selected for analyzing the combustor-diffuser interaction. Analytical model predictions were obtained for all flow conditions at which Phase 2 tests will be conducted. These results will be compared with laser doppler velocimeter data. Furthermore, a generalized nonorthogonal grid system is being developed to accurately simulate complex wall shapes.

Srinivasan, R.↗

Integration of symbolic and algorithmic hardware and software for the automation of space station subsystems

Traditional expert systems, such as diagnostic and training systems, interact with users only through a keyboard and screen, and are usually symbolic in nature. Expert systems that require access to data bases, complex simulations and real-time instrumentation have both symbolic as well as algorithmic computing needs. These needs could both be met using a general purpose workstation running both symbolic and algorithmic code, or separate, specialized computers networked together. The latter approach was chosen to implement TEXSYS, the thermal expert system, developed by NASA Ames Research Center in conjunction with Johnson Space Center to demonstrate the ability of an expert system to autonomously monitor the thermal control system of the space station. TEXSYS has been implemented on a Symbolics workstation, and will be linked to a microVAX computer that will control a thermal test bed. This paper will explore the integration options, and present several possible solutions.

Gregg, Hugh↗

Integration of symbolic and algorithmic hardware and software for the automation of space station subsystems

Expert systems that require access to data bases, complex simulations and real time instrumentation have both symbolic as well as algorithmic computing needs. These needs could both be met using a general computing workstation running both symbolic and algorithmic code, or separate, specialized computers networked together. The later approach was chosen to implement TEXSYS, the thermal expert system, developed to demonstrate the ability of an expert system to autonomously control the thermal control system of the space station. TEXSYS has been implemented on a Symbolics workstation, and will be linked to a microVAX computer that will control a thermal test bed. Integration options are explored and several possible solutions are presented.

Gregg, Hugh↗

Integration of symbolic and algorithmic hardware and software for the automation of space station subsystems

Expert systems that require access to data bases, complex simulations and real time instrumentation have both symbolic and algorithmic needs. Both of these needs could be met using a general purpose workstation running both symbolic and algorithmic codes, or separate, specialized computers networked together. The later approach was chosen to implement TEXSYS, the thermal expert system, developed by the NASA Ames Research Center in conjunction with the Johnson Space Center to demonstrate the ability of an expert system to autonomously monitor the thermal control system of the space station. TEXSYS has been implemented on a Symbolics workstation, and will be linked to a microVAX computer that will control a thermal test bed. The integration options and several possible solutions are presented.

Gregg, Hugh↗

Three-dimensional multigrid Navier-Stokes computations for turbomachinery applications

The fully three-dimensional, time-dependent compressible Navier-Stokes equations in cylindrical coordinates are presently used, in conjunction with the multistage Runge-Kutta numerical integration scheme for solution of the governing flow equations, to simulate complex flowfields within turbomechanical components whose pertinent effects encompass those of viscosity, compressibility, blade rotation, and tip clearance. Computed results are presented for selected cascades, emphasizing the code's capabilities in the accurate prediction of such features as airfoil loadings, exit flow angles, shocks, and secondary flows. Computations for several test cases have been performed on a Cray-YMP, using nearly 90,000 grid points.

Subramanian, S. V.↗

Goddard Mission Analysis System (GMAS)

Written to simulate complex satellite orbits including attitude control and orbital maneuvers, GMAS also performs shadow and station coverage studies and graph-selected orbital parameters for two satellites. Written in FORTRAN and ASSEMBLER.

Mcgarry, F. E.↗

METCAN verification status

The status of the verification (comparisons of predictions with experimental data) of the METCAN (METal-matrix Composite ANalyzer) code at high temperature is summarized. Verification includes select available room temperature of W/Cu composites for different fiber volume ratios. It also includes high temperature properties for thermal expansion, moduli, strength and stress/strain behavior for SiC/Ti composites. Furthermore it includes limited cases for thermal fatigue strength degradation. The verification results summarized herein indicate that METCAN simulates complex high temperature metal matrix composite bahavior with reasonable accuracy and that it can be used with confidence to identify in-situ nonlinear behavior that influences composite properties.

Chamis, Christos C.↗

Development of comprehensive numerical schemes for predicting evaporating gas-droplets flow processes of a liquid-fueled combustor

An existing Computational Fluid Dynamics code for simulating complex turbulent flows inside a liquid rocket combustion chamber was validated and further developed. The Advanced Rocket Injector/Combustor Code (ARICC) is simplified and validated against benchmark flow situations for laminar and turbulent flows. The numerical method used in ARICC Code is re-examined for incompressible flow calculations. For turbulent flows, both the subgrid and the two equation k-epsilon turbulence models are studied. Cases tested include idealized Burger's equation in complex geometries and boundaries, a laminar pipe flow, a high Reynolds number turbulent flow, and a confined coaxial jet with recirculations. The accuracy of the algorithm is examined by comparing the numerical results with the analytical solutions as well as experimented data with different grid sizes.

Chen, C. P.↗

Radar signal categorization using a neural network

Neural networks were used to analyze a complex simulated radar environment which contains noisy radar pulses generated by many different emitters. The neural network used is an energy minimizing network (the BSB model) which forms energy minima - attractors in the network dynamical system - based on learned input data. The system first determines how many emitters are present (the deinterleaving problem). Pulses from individual simulated emitters give rise to separate stable attractors in the network. Once individual emitters are characterized, it is possible to make tentative identifications of them based on their observed parameters. As a test of this idea, a neural network was used to form a small data base that potentially could make emitter identifications.

Anderson, James A.↗

Development of a sensor coordinated kinematic model for neural network controller training

A robotic benchmark problem useful for evaluating alternative neural network controllers is presented. Specifically, it derives two camera models and the kinematic equations of a multiple degree of freedom manipulator whose end effector is under observation. The mapping developed include forward and inverse translations from binocular images to 3-D target position and the inverse kinematics of mapping point positions into manipulator commands in joint space. Implementation is detailed for a three degree of freedom manipulator with one revolute joint at the base and two prismatic joints on the arms. The example is restricted to operate within a unit cube with arm links of 0.6 and 0.4 units respectively. The development is presented in the context of more complex simulations and a logical path for extension of the benchmark to higher degree of freedom manipulators is presented.

Jorgensen, Charles C.↗