BSCW High-Angle of Attack Computations Using Kestrel and AEROM
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Walt Silva↗
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Computational Analysis of the X-57 Maxwell Airplane, the Landing Configuration with High-Lift Blowing and Aileron Deflections (Preliminary Fuselage)
The X-57 Maxwell is an all-electric airplane with a distributed electric propulsion system used for a high-lift system at takeoff and landing conditions. The Kestrel and USM3D flow solvers were used at NASA Langley to investigate the performance of the X-57 Maxwell in the development of an aerodynamic database. The configuration investigated in this paper had a 30° flap deflection, and in addition the pilot’s right aileron were deflected and undeflected in different cases. The solutions were computed at an airspeed of 58 KEAS, for an altitude of 6000 feet, and a flight Reynolds number of 0.588e+06 per foot. To evaluate the high-lift distributed electric propulsion system without aileron deflections, the solutions were computed for an angle-of-attack sweep from −2° to 20°, with the high-lift propellers blowing and the cruise propellers excluded from the simulation. To investigate the aileron effectiveness, the solutions were computed at angles of attack of −2° and 14°, for aileron deflections from −25° to 18° with the high-lift propellers blowing and the cruise propellers windmilling at idle-power. The high-lift propellers and the idle-power cruise propellers were modeled with an actuator disk. Results show negligible differences in lift, drag and pitching moment whether the idle-powered cruise propellers were included or excluded from the simulation. In general, the Kestrel and USM3D codes compared well for lift, drag and pitching moment for the landing configuration with no aileron control. The Kestrel code, using the Spalart-Allmaras turbulence model with the rotation corrections terms, predicted an increasing lift coefficient up to maximum lift coefficient of 4.65 at a 15° angle of attack. The USM3D code, using the Spalart-Allmaras turbulence model turbulence model with the Quadratic Constitutive Relation predicted an increasing lift coefficient up to maximum lift coefficient of 4.5 at a 12° angle of attack, with the lift remaining constant through a 14◦ angle of attack. A possible difference in lift coefficient between the codes for high angles of attack may result from the different available options used with the standard Spalart-Allmaras turbulence model. The Kestrel code predicted more drag across the range of angle of attack than the USM3D code. The codes compared well for pitching moment coefficient across the range of angle of attack. The Kestrel and USM3D codes compared well for aileron effectiveness at a 2° angle of attack. The Kestrel code predicts better aileron effectiveness than USM3D at a 14° angle of attack. There is more flow separation in the region outboard of the last high-lift nacelle for the USM3D solutions at a 14° angle of attack, which diminishes the ability of the aileron to be effective.
X-57 Maxwell Airplane↗
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↗
Cooperation Among Theorem Provers
This is a final report, which supports NASA's PECSEE (Persistent Cognizant Software Engineering Environment) effort and complements the Kestrel Institute project "Inference System Integration via Logic Morphism". The ultimate purpose of the project is to develop a superior logical inference mechanism by combining the diverse abilities of multiple cooperating theorem provers. In many years of research, a number of powerful theorem-proving systems have arisen with differing capabilities and strengths. Resolution theorem provers (such as Kestrel's KITP or SRI's, SNARK) deal with first-order logic with equality but not the principle of mathematical induction. The Boyer-Moore theorem prover excels at proof by induction but cannot deal with full first-order logic. Both are highly automated but cannot accept user guidance easily. The PVS system (from SRI) in only automatic within decidable theories, but it has well-designed interactive capabilities: furthermore, it includes higher-order logic, not just first-order logic. The NuPRL system from Cornell University and the STeP system from Stanford University have facilities for constructive logic and temporal logic, respectively - both are interactive. It is often suggested - for example, in the anonymous "QED Manifesto"-that we should pool the resources of all these theorem provers into a single system, so that the strengths of one can compensate for the weaknesses of others, and so that effort will not be duplicated. However, there is no straightforward way of doing this, because each system relies on its own language and logic for its success. Thus. SNARK uses ordinary first-order logic with equality, PVS uses higher-order logic. and NuPRL uses constructive logic. The purpose of this project, and the companion project at Kestrel, has been to use the category-theoretic notion of logic morphism to combine systems with different logics and languages. Kestrel's SPECWARE system has been the vehicle for the implementation.
Waldinger, Richard J.↗
Advanced Computing Annual Report 2024
In fiscal year (FY) 2024, the National Renewable Energy Laboratory (NREL) took a major leap forward with the completed full buildout of Kestrel, the Office of Energy Efficiency and Renewable Energy's newest high-performance computing (HPC) system. Kestrel is already supporting science across the portfolio, bringing roughly 44 petaflops of computing power, which is more than five times the capacity of our previous supercomputer, Eagle. By delivering greater GPU capacity, Kestrel enables faster progress in artificial intelligence (AI) and opens new avenues in energy research - from defining long-term planning scenarios to accommodate a growing power system to material discovery to improving energy efficiency in photovoltaics (PV). Across the portfolio, research is being accelerated by Kestrel's impressive power. During FY24, 427 projects and more than 700 researchers used NREL's HPC, supporting the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy across 13 funding areas. Through these collaborations, researchers produced more than 450 technical outputs, including 195 articles in peer-reviewed publications, pushing the boundaries of science and engineering. This year's report features new sections spotlighting the expanding roles of Artificial Intelligence and Accelerated Computing. We also introduce an early career section to celebrate the accomplishments of our up-and-coming researchers, whose pioneering work is shaping the future of energy. We hope you enjoy the new insights and discoveries highlighted in these pages.
97 MATHEMATICS AND COMPUTING↗
Microbiomes of frozen blood plasma samples reveal potential pathogens in wild birds and rodents
The lack of genomic data on pathogens from wildlife severely limits our ability to track transmission patterns and trace the origins of an outbreak. There are currently millions of wildlife samples in biobanks around the world, including blood samples. Blood has traditionally been viewed as a sterile environment in healthy individuals, but recent evidence suggests that this is not the case, especially for wild animals. Our goal was to determine whether frozen plasma samples can be surveyed using 16S sequencing to provide information about potential hosts for pathogens for a more complete understanding of disease systems. We sequenced blood plasma from wild North American deer mice ( Peromyscus maniculatus ) and American kestrels ( Falco sparverius ) that were cryogenically stored for 7 and 13 years, respectively, and compared two DNA extraction kits. The kestrel samples contained a very high number of reads that could not be identified to phylum compared to the mouse samples. The two kits differed in the phyla and genera that were detected, and the Zymo kit, which is optimized for plasma and serum, produced more high-quality reads for both kestrel and mouse samples. We identified several pathogenic genera, including Mycoplasma, Escherichia-Shigella , and Bartonella . Sequencing blood samples for pathogens could potentially have broad applications for identifying important reservoir hosts for pathogen transmission and provide a reduced set of species on which to follow up.
59 BASIC BIOLOGICAL SCIENCES↗
Advanced Computing Annual Report 2023
In 2023, advanced computing saw the arrival of Kestrel, the National Renewable Energy Laboratory's (NREL's) newest high-performance computing (HPC) system. Kestrel will accelerate clean energy research at a pace and scale more than five times greater than Eagle, with approximately 44 petaflops of computing power. Kestrel's heterogeneous architecture - which includes both CPU-only and GPU-accelerated nodes - is designed to bring a much greater GPU capacity to EERE workloads compared to Eagle, enabling rapidly advancing applications in artificial intelligence and expanding research in new directions for computing. In Fiscal Year (FY) 2023, 333 projects utilized NREL's HPC system, advancing the U.S. Department of Energy's (DOE's) Office of Energy Efficiency and Renewable Energy (EERE) mission across 13 funding areas. Cross-disciplinary collaboration among researchers yielded more than 800 technical outputs, including 177 peer-reviewed journal articles in FY 2023. All this great work continues to advance the science of energy efficiency and renewable energy. This report highlights research that utilized HPC resources in FY 2023.
advanced computing↗
Cooperation Among Theorem Provers
In many years of research, a number of powerful theorem-proving systems have arisen with differing capabilities and strengths. Resolution theorem provers (such as Kestrel's KITP or SRI's SNARK) deal with first-order logic with equality but not the principle of mathematical induction. The Boyer-Moore theorem prover excels at proof by induction but cannot deal with full first-order logic. Both are highly automated but cannot accept user guidance easily. The purpose of this project, and the companion project at Kestrel, has been to use the category-theoretic notion of logic morphism to combine systems with different logics and languages.
Waldinger, Richard J.↗
On-Orbit Software Analysis
The On-Orbit Software Analysis Research Infusion Project was done by Intrinsyx Technologies Corporation (Intrinsyx) at the National Aeronautics and Space Administration (NASA) Ames Research Center (ARC). The Project was a joint collaborative effort between NASA Codes IC and SL, Kestrel Technology (Kestrel), and Intrinsyx. The primary objectives of the Project were: Discovery and verification of software program properties and dependencies, Detection and isolation of software defects across different versions of software, and Compilation of historical data and technical expertise for future applications
Moran, Susanne I.↗
Computational Component Build-Up for the X-57 Distributed Electric Propulsion Aircraft
A computational study of the wing for the distributed electric propulsion X-57 Maxwell airplane configuration at cruise and takeoff/landing conditions was completed. Three unstructured-mesh, Navier-Stokes computational fluid dynamics methods, FUN3D, USM3D and Kestrel, were used to predict the performance buildup of components to the full X-57 configuration. The goal of the X-57 wing and distributed electric propulsion system design was to meet or exceed the required lift coefficient of 3.95 for a stall speed of 58 knots. The X-57 Maxwell airplane was designed with a small, high aspect ratio cruise wing that was designed for a high cruise lift coefficient of 0.75 at a cruise speed of 150 knots and altitude of 8,000 ft, with an angle of attack of approximately 0deg. The computational data indicates that the X-57 full aircraft drag would meet the cruise drag goal with a 25 count drag margin. The cruise configuration maximum lift coefficient is 2.07 and without including the stabilator is 1.86 at an angle of attack of 14 deg, predicted with the USM3D flow solver using the Spalart-Allmaras turbulence model. The maximum lift coefficient for the high-lift wing (with the 30deg flap deflection) without the stabilator contribution is 2.60 at an angle of attack of 13 deg. For high-lift blowing conditions with 13.7 hp/prop, the maximum lift coefficient excluding the stabilator is 4.426 at (alpha) = 13 deg. Therefore, the lift augmentation from the high-lift propellers is 1.7 and the total lift augmentation from the high-lift system (30 deg flap deflection and the high-lift blowing) is 2.38. The drag for the high-lift wing with 30 deg flap deflection is much higher than the cruise wing configuration, but the high-lift system is used only during a small portion of the flight envelope. The pitching moment is relatively constant for both blown and unblown conditions when the stabilator is excluded. Modeling the full geometry has indicated some adverse effects from the fuselage on the wing and stabilator. At high angles of attack, the solutions with the USM3D flow solver using the Spalart-Allmaras turbulence model indicates large flow separation on the wing upper surface between the two high-lift nacelles near the fuselage, and also a reduction in sectional lift on the stabilator in the first 50 percent of the stabilator semispan. However, the large flow separation near the fuselage is mostly eliminated in the solutions predicted with two codes, USM3D and Kestrel, using Hybrid Reynolds-averaged Navier Stokes/Large Eddy Simulation turbulence models.
Deere, Karen A.↗
Unstructured Grid Development for the Space Launch System Liftoff and Transition Lineloads Computational Analysis
Production of aerodynamic lineloads databases for the Space Launch System (SLS) vehicle at Liftoff and Transition (LOT) conditions has required the development of a Computational Fluid Dynamics (CFD) workflow capable of producing high-quality solutions for this unique phase of flight. Aerodynamic considerations included a wide range of flow angles (from 0°up to 90°total angle of attack), resulting leeside separation, and interaction effects between the three bodies of the integrated SLS vehicle, as well as the nearby launch tower. Computational mesh development for similar problems at the NASA Langley Research Center (such as for the Constellation/Ares launch vehicles) has primarily relied on in-house tools such as VGRID/POSTGRID, with grids designed for NASA-developed and maintained flow solvers such as USM3D and FUN3D. The workflow for such problems has evolved over the development of the various SLS configurations to incorporate new tools such as the Heldenpatch/Heldenmesh grid generator (Helden Aerospace) and CREATE-AV Kestrel (US Department of Defense) flow solver. This paper describes efforts to benchmark a grid generation approach for LOT problems using Heldenpatch/Heldenmesh and Kestrel, verified against prior best practices from VGRID/POSTGRID. Parameters studied include surface grid density, first-layer viscous cell height, and volume grid growth rate parameters. Resulting solutions are compared based on total force and moment values, sectional line loads, and surface pressures, all validated against existing wind tunnel aerodynamic databases where available for the SLS Block 1B Cargo configuration.
Space launch systems↗
Computational Techniques to Generate Space Launch System Aerodynamic Databases
This document describes the reasoning and trade studies used to evaluate tools for constructing the aerodynamic lineload databases for the liftoff and transition phases of flight for the Space Launch System. Three computational fluid dynamics codes (USM3D, FUN3D, Kestrel) were investigated with various turbulence models, as well as detached eddy simulation variants for the launch vehicle in free air and in proximity to the tower. Decisions were made mostly based on results from brief developmental studies performed in response to specific, unforeseen challenges that were encountered in the analysis of a given configuration. The need to develop databases in a timely manner, as well as accurately capture the expected leeward-wake flowfield characteristics, led to the selection of the Kestrel flow solver with its delayed detached eddy simulation method, the Spalart-Allmaras turbulence model, and the adaptive mesh refinement capability in the off-body Cartesian grid region.
Karen A. Deere↗
RANS Predictions of Inlet/Isolator Unstart at Mach 4
This paper describes several approaches to back pressuring an inlet/isolator model at Mach 4.0 and the differences in unstart predictions using common RANS simulation methods. The CFD codes OVERFLOW and CREATE-AV Kestrel were used for this work. Verification and validation was conducted on a relevant shock-wave-boundary-layer-interaction case with both solvers. Using aftmounted back pressure flaps did not produce a stable pre-combustion shock train. An unstart comparison between CFD codes OVERFLOW and CREATE-AV Kestrel as well as common 2-equation turbulence models was conducted with numerical back pressure. Unstart predictions using a novel louver back pressure mechanism was done with OVERFLOW. There is notable differences in shock train travel and predicted unstart limit due to turbulence modeling, temporal resolution, and use of the 2D simplification.
CFD↗
Transforming Energy Through Computational Excellence: NREL HPC Resources for High Performance Computing for Energy Innovation (HPC4EI) Program
NREL hosts computing facilities for the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). In 2024, NREL introduced Kestrel, the 3rd generation, EERE-sponsored supercomputer dedicated to renewable energy and energy efficiency research. Kestrel has already been used for hundreds of research projects by NREL, other national laboratories, and university partners. This includes HPC4EI-sponsored industrial partnerships.
high-performance computing↗
OptiBench: An Optimization Benchmark Tool for Renewable Energy Problems
We propose a benchmark framework and visualization tool, OptiBench, for analyzing the performance of state-of-the-art optimization solvers across a variety of optimization problems in renewable energy research. Our framework is designed from the ground up in the Julia programming language and enables analysis at scale on high performance computing (HPC) systems. Our visualization tool allows effortless evaluation of optimization solver performance, robustness, and accuracy through intuitive plots, e.g., performance profiles, heat maps, and distribution plots. We have tested three benchmark suites relevant to the modeling of renewable energy systems, viz., CUTEst, PGLib-OPF, and WaterTAP water treatment optimization problems. We illustrate benchmarking of CUTEst using OptiBench on the National Renewable Energy Laboratory's (NREL) HPC Kestrel. Our findings indicate that MA57 HSL linear solver demonstrated the best overall performance for an experimental IPOPT implementation. Our work is ongoing and we intend to add support for more optimization solvers and benchmark test suites in the future.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Accelerating Floating-Point Computations with Intel AMX
Intel AMX is a built-in component of recent Intel CPU architectures, first supported by the Intel Sapphire Rapids in 2023, that enables efficient dense matrix multiplications using mixed precision with low-precision data types. The popularity of mixed-precision algorithms has grown recently, primarily due to their use on GPUs to enhance the efficiency of HPC applications, particularly for the training of large language models. The availability of mixed precision on CPUs represents a cost-effective solution for applications where high speed is not critical. This report shows how to use the Intel AMX accelerator through examples in C++ and Python. The examples will focus on mixed-precision floating-point operations obtained by the use of bfloat16 (or BF16) to accelerate code in single precision. We employ a bottom-up methodology, starting from specific register instructions (TMUL operation) to higher-level applications in libraries such as Intel MKL, PyTorch, and TensorFlow, ensuring a comprehensive understanding of the accelerator's potential. Additionally, we provide insights into the expected performance gains when leveraging the accelerator on the Kestrel HPC machine at the National Renewable Energy Laboratory.
97 MATHEMATICS AND COMPUTING↗
OptiBench: An Optimization Benchmark Tool for Renewable Energy Problems
We propose a benchmark framework and visualization tool, OptiBench, for analyzing the performance of state-of-the-art optimization solvers across a variety of optimization problems in renewable energy research. Our framework is designed from the ground up in the Julia programming language and enables analysis at scale on high performance computing (HPC) systems. Our visualization tool allows effortless evaluation of optimization solver performance, robustness, and accuracy through intuitive plots, e.g., performance profiles, heat maps, and distribution plots. We have tested three benchmark suites relevant to the modeling of renewable energy systems, viz., CUTEst, PGLib-OPF, and WaterTAP water treatment optimization problems. We illustrate benchmarking of CUTEst using OptiBench on the National Laboratory of the Rockies's (NLR) HPC Kestrel. Our findings indicate that MA57 HSL linear solver demonstrated the best overall performance for an experimental IPOPT implementation. Our work is ongoing and we intend to add support for more optimization solvers and benchmark test suites in the future.
97 MATHEMATICS AND COMPUTING↗
Additive Manufactured Composite Phase-Change Material for Thermal Energy Storage Applications
Phase-change materials play a critical role in industrial energy storage applications to drive efficiency improvements, thermal energy management, and carbon emissions reductions. Recently, it has been shown that rapid solidification of alloys with metastable immiscibility in the liquid phase has the potential to form unique microstructures in which a low-melting phase is uniformly distributed in a high-melting matrix. This feature can be exploited using additive manufacturing to produce components with complex geometries containing such unique phase-change microstructures. Phase-field simulations utilizing high-performance computing were used to provide a detailed description of the evolution of the active phase during service in terms of their morphology and composition in different polycrystalline matrix grain morphologies that are typically produced during additive manufacturing. Phase field simulations were performed using, MEUMAPPS-SL (Microstructure Evolution Using Massively Parallel Phase-field Simulations – Solid Liquid) code that was developed in-house by the Oak Ridge National Laboratory. The simulations utilized the capabilities of the Kestrel supercomputer at the National Renewable Energy Laboratory. The simulation results were compared with experimental results generated at Siemens Energy, Inc. The results indicate that the kinetics of liquid spreading along grain boundaries is largely determined by the mobility of the triple line along the intersection of the grain boundary liquid and the grain boundary plane.
25 ENERGY STORAGE↗