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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

CFD Analysis in Advance of the NASA Juncture Flow Experiment

NASA through its Transformational Tools and Technologies Project (TTT) under the Advanced Air Vehicle Program, is supporting a substantial effort to investigate the formation and origin of separation bubbles found on wing-body juncture zones. The flow behavior in these regions is highly complex, difficult to measure experimentally, and challenging to model numerically. Multiple wing configurations were designed and evaluated using Computational Fluid Dynamics (CFD), and a series of wind tunnel risk reduction tests were performed to further down-select the candidates for the final experiment. This paper documents the CFD analysis done in conjunction with the 6 percent scale risk reduction experiment performed in NASA Langley's 14- by 22-Foot Subsonic Tunnel. The combined CFD and wind tunnel results ultimately helped the Juncture Flow committee select the wing configurations for the final experiment.

Flow Experiment↗
NASA NTRS2017

CFD Analysis in Advance of the NASA Juncture Flow Experiment

NASA through its Transformational Tools and Technologies Project (TTT) under the Advanced Air Vehicle Program, is supporting a substantial effort to further investigate the formation and origin of separation bubbles found on wing-body juncture zones. The flow behavior in these regions is highly complex, difficult to measure experimentally, and challenging to model numerically. Multiple wing configurations were designed and evaluated using Computational Fluid Dynamics (CFD), and a series of wind tunnel risk reduction tests were performed to further down-select the candidates for the final experiment. This paper documents the CFD analysis done in conjunction with the 6 percent scale risk reduction experiment performed in NASA Langley’s 14- by 22-Foot Subsonic Tunnel. The combined CFD and wind tunnel results ultimately help the Juncture Flow committee select the wing configurations for the final experiment.

Lee, H. C.↗
DOE OSTI2025

Developing ML/AI Methods for High-Throughput Characterization of Multiple-Sensor Streams of Tokamak Dynamics for High-Speed Control (Final Report)

This project evaluated and developed new mathematical and algorithmic techniques capable of handling (in real-time) the growing amounts of data generated by modern fusion research. While existing numerical linear algebra (NLA) methods provide the backbone to classical data analysis and algorithms, these methods fundamentally do not port to distributed architectures nor do they allow low-latency data reduction for control. Motivated by the needs for modern fusion reactors, this project explored and implemented new numerical methods to characterize plasma dynamics, respond in real-time to discharge evolution, and to process massive-scale data accurately and rapidly more fully. This project links expertise in multiple-sensor diagnostics of tokamak plasma dynamics from Columbia University’s Plasma Physics Laboratory with expertise in massive-scale data reduction and extreme data control algorithms at Columbia University’s Data Science Institute. This interdisciplinary project (i) applied machine learning methods, (ii) implemented a properly-trained neural-network for very fast processing of high-speed plasma videography, and (ii) developed the applied mathematical methods, based on randomized-NLA (rNLA) routines, for data analysis, reduction, and real-time control. The Columbia University High Beta Tokamak-Extended Pulse (HBT-EP) facility provided data to test new algorithms and partnership with Columbia University's Data Sciences Institute evaluated the broader use of new algorithms for many challenging control applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Breaking adsorption-energy scaling limitations of electrocatalytic nitrate reduction on intermetallic CuPd nanocubes by machine-learned insights

The electrochemical nitrate reduction reaction (NO 3 RR) to ammonia is an essential step toward restoring the globally disrupted nitrogen cycle. In search of highly efficient electrocatalysts, tailoring catalytic sites with ligand and strain effects in random alloys is a common approach but remains limited due to the ubiquitous energy-scaling relations. With interpretable machine learning, we unravel a mechanism of breaking adsorption-energy scaling relations through the site-specific Pauli repulsion interactions of the metal d-states with adsorbate frontier orbitals. The non-scaling behavior can be realized on (100)-type sites of ordered B2 intermetallics, in which the orbital overlap between the hollow *N and subsurface metal atoms is significant while the bridge-bidentate *NO 3 is not directly affected. Among those intermetallics predicted, we synthesize monodisperse ordered B2 CuPd nanocubes that demonstrate high performance for NO 3 RR to ammonia with a Faradaic efficiency of 92.5% at –0.5 V RHE and a yield rate of 6.25 mol h –1 g –1 at –0.6 V RHE . This study provides machine-learned design rules besides the d-band center metrics, paving the path toward data-driven discovery of catalytic materials beyond linear scaling limitations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1980

VCE early acoustic test results of General Electric's high-radius ratio coannular plug nozzle

Results of variable cycle engine (VCE) early acoustic engine and model scale tests are presented. A summary of an extensive series of far field acoustic, advanced acoustic, and exhaust plume velocity measurements with a laser velocimeter of inverted velocity and temperature profile, high radius ratio coannular plug nozzles on a YJ101 VCE static engine test vehicle are reviewed. Select model scale simulated flight acoustic measurements for an unsuppressed and a mechanical suppressed coannular plug nozzle are also discussed. The engine acoustic nozzle tests verify previous model scale noise reduction measurements. The engine measurements show 4 to 6 PNdB aft quadrant jet noise reduction and up to 7 PNdB forward quadrant shock noise reduction relative to a fully mixed conical nozzle at the same specific thrust and mixed pressure ratio. The influences of outer nozzle radius ratio, inner stream velocity ratio, and area ratio are discussed. Also, laser velocimeter measurements of mean velocity and turbulent velocity of the YJ101 engine are illustrated. Select model scale static and simulated flight acoustic measurements are shown which corroborate that coannular suppression is maintained in forward speed.

Knott, P. R.↗
NASA NTRS1982

Rotorcraft noise

This report is a compilation of papers presented at the NASA/U.S. Helicopter Industry Workshop on Aerodynamic Noise Prediction/Noise Reduction held at Langley Research Center, March 29-31, 1982. Included in the topics presented are papers on noise reduction techniques, scaling laws, empirical noise prediction, and methods for developing and validating noise prediction methods. The results of the working sessions are presented as findings, conclusions, and recommendations.

Helicopters↗
NASA NTRS2011

Aerodynamic Simulation of Ice Accretion on Airfoils

This report describes recent improvements in aerodynamic scaling and simulation of ice accretion on airfoils. Ice accretions were classified into four types on the basis of aerodynamic effects: roughness, horn, streamwise, and spanwise ridge. The NASA Icing Research Tunnel (IRT) was used to generate ice accretions within these four types using both subscale and full-scale models. Large-scale, pressurized windtunnel testing was performed using a 72-in.- (1.83-m-) chord, NACA 23012 airfoil model with high-fidelity, three-dimensional castings of the IRT ice accretions. Performance data were recorded over Reynolds numbers from 4.5 x 10(exp 6) to 15.9 x 10(exp 6) and Mach numbers from 0.10 to 0.28. Lower fidelity ice-accretion simulation methods were developed and tested on an 18-in.- (0.46-m-) chord NACA 23012 airfoil model in a small-scale wind tunnel at a lower Reynolds number. The aerodynamic accuracy of the lower fidelity, subscale ice simulations was validated against the full-scale results for a factor of 4 reduction in model scale and a factor of 8 reduction in Reynolds number. This research has defined the level of geometric fidelity required for artificial ice shapes to yield aerodynamic performance results to within a known level of uncertainty and has culminated in a proposed methodology for subscale iced-airfoil aerodynamic simulation.

Broeren, Andy P.↗
NASA NTRS1982

Pole placement and order reduction in two-time-scale control systems through Riccati iteration

A transformation of variables taken from singular perturbations may be applied to two-time-scale linear systems in state space form to reduce the system to block-diagonal form with slow and fast modes decoupled. The transformation is easily computed by applying the new Riccati iteration. The iteration yields a solution to the nonsymmetric algebraic Riccati equation obtained by partitioning the original system matrix A. The numerical procedure is initiated with the trivial iterate L(0) = 0, and is globally convergent to the desired unique time scale decoupling solution. After transformation, the decoupled system may be used in controller design to achieve exact closed loop pole placement in the slow subsystem without altering the poles of the fast subsystem. The decoupled form may also be used to reduce system order by wetting a small parameter to zero. Provided the fast subsystem is stable, the order reduction can be expected to yield a good approximation to the original system. These methods are demonstrated using the 16th order linear model of a turbofan engine.

Anderson, L. R.↗
NASA NTRS1976

Noise reduction tests of large-scale-model externally blown flap using trailing-edge blowing and partial flap slot covering

Noise data were obtained with a large-scale cold-flow model of a two-flap, under-the-wing, externally blown flap proposed for use on future STOL aircraft. The noise suppression effectiveness of locating a slot conical nozzle at the trailing edge of the second flap and of applying partial covers to the slots between the wing and flaps was evaluated. Overall-sound-pressure-level reductions of 5 db occurred below the wing in the flyover plane. Existing models of several noise sources were applied to the test results. The resulting analytical relation compares favorably with the test data. The noise source mechanisms were analyzed and are discussed.

Mckinzie, D. J., Jr.↗
DOE OSTI2024

A Review of Coupled Geochemical–Geomechanical Impacts in Subsurface CO 2 , H 2 , and Air Storage Systems

Increased demand for decarbonization and renewable energy has led to increasing interest in engineered subsurface storage systems for large-scale carbon reduction and energy storage. In these applications, a working fluid (CO 2 , H 2 , air, etc.) is injected into a deep formation for permanent sequestration or seasonal energy storage. The heterogeneous nature of the porous formation and the fluid–rock interactions introduce complexity and uncertainty in the fate of the injected component and host formations in these applications. Interactions between the working gas, native brine, and formation mineralogy must be adequately assessed to evaluate the efficiency, risk, and viability of a particular storage site and operational regime. This study reviews the current state of knowledge about coupled geochemical–geomechanical impacts in geologic carbon sequestration (GCS), underground hydrogen storage (UHS), and compressed air energy storage (CAES) systems involving the injection of CO 2 , H 2 , and air. Specific review topics include (1) existing injection induced geochemical reactions in these systems; (2) the impact of these reactions on the porosity and permeability of host formation; (3) the impact of these reactions on the mechanical properties of host formation; and (4) the investigation of geochemical-geomechanical process in pilot scale GCS. This study helps to facilitate an understanding of the potential geochemical–geomechanical risks involved in different subsurface energy storage systems and highlights future research needs.

08 HYDROGEN↗
DOE OSTI2022

A differentiable approach to the maximum independent set problem using dataless neural networks

The success of machine learning solutions for reasoning about discrete structures has brought attention to its adoption within combinatorial optimization algorithms. Such approaches generally rely on supervised learning by leveraging datasets of the combinatorial structures of interest drawn from some distribution of problem instances. Reinforcement learning has also been employed to find such structures. Here, in this paper, we propose a different approach in that no data is required for training the neural networks that produce the solution. In this sense, what we present is not a machine learning solution, but rather one that is dependent on neural networks and where backpropagation is applied to a loss function defined by the structure of the neural network architecture as opposed to a training dataset. In particular, we reduce the popular combinatorial optimization problem of finding a maximum independent set to a neural network and employ a dataless training scheme to refine the parameters of the network such that those parameters yield the structure of interest. Additionally, we propose a universal graph reduction procedure to handle large-scale graphs. The reduction exploits community detection for graph partitioning and is applicable to any graph type and/or density. Experimental results on both real and synthetic graphs demonstrate that our proposed method performs on par or outperforms state-of-the-art learning-based methods in terms of the size of the found set without requiring any training data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Tensor Hypercontraction of Cluster Perturbation Theory: Quartic Scaling Perturbation Series for the Coupled Cluster Singles and Doubles Ground-State Energies

Even though Cluster Perturbation has been shown to be a robust non-iterative alternative to Coupled Cluster Theory, it is still plagued by high order polynomial computational scaling and the storage of higher order tensors. Here we present a proof-of-concept strategy for implementing Cluster Perturbation Theory ground state energy series for the coupled cluster singles and doubles energy with N 4 computational scaling using Tensor Hypercontraction (THC). The reduction in computational scaling by two orders is achieved by decomposing two electron repulsion integrals, doubles amplitudes and multipliers, as well as selected doubles intermediates to Tensor Hypercontraction format. Using the outlined strategy, we showcase that the Tensor Hypercontraction pilot implementations retain numerical accuracy to within 1 kcal/mol relative to corresponding conventional and density fitting implementations and we empirically verify the N 4 scaling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Electronic and Electrochemical Control of Isostructural Ruthenium Hydricities and the Implications for Catalytic Overpotentials

Electronic tuning of metal hydrides enables precise control over potentials, mechanisms, selectivity, and rates of electrocatalytic reactions by regulating bond dissociation free energies such as the hydricity (Δ$G$ H- ° ) and $pK$ a of the catalyst. Here, we investigate a series of electronically tuned ruthenium hydrido complexes that are isostructural at the metal center: [Ru(4,4'-R 2 -bpy) 2 (CO)H] + (R = CF 3 , Cl, H, CH 3 , and CH 3 O; bpy = 2,2'-bipyridine) (denoted as (R)Ru-H+). A substantial 22 kcal mol -1 hydricity range is available across five complexes in three stable oxidation states: (R)Ru-H + , (R)Ru-H 0 , and (R)Ru-H - . Thermodynamic and mechanistic predictions of electrocatalytic proton reduction were tested experimentally by reducing protons from weak acids to H 2 . Two mechanisms are observed, depending on the acid strength and the catalyst hydricity. The rate constants for hydride transfer and protonation of the catalyst were, in some cases, extracted from the analysis of cyclic voltammetry data. A key finding is a 400 mV decrease in the catalytic overpotential for H 2 production by using a doubly reduced electron-poor metal hydride instead of a singly reduced electron-rich metal hydride. In conclusion, the former also exhibits a higher rate constant for hydride transfer, representing a strategy to disconnect rate and free energy relationships.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Towards Autonomous Experiments by Connecting High Performance Microscopy with High Performance Computing

The digitization of controls, data, and analysis in microscopy is bringing the idea of autonomous microscopes closer to reality than ever before. Automated transmission electron microscopy (TEM) is already fairly routine for some experiments the only require simple repetitive tasks such as imaging biological macromolecules for single particle cryoEM [1], tilt series for electron tomography [2], and movies for crystallography [3]. The vast majority of TEM experiments are conducted completely by human operators who choose the regions of interest, optimize experimental parameters, and make decisions about data quality visually during an experiment. The field is still a long way from having completely autonomous TEMs that can adapt to sample difficulties and tune experimental parameters based on data quality and desired experimental outcomes. Part of the issue is the lack of capability for feeding information learned from on-line, live data analysis back into the on-going experiment [4]. Furthermore, this presentation will discuss current capabilities for large scale data reduction and analysis using high performance computing (i.e. supercomputing) and progress towards developing a true feed-back loop that places data analysis and theory in the experimental loop.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

On-chip integrated laser-driven particle accelerator

Particle accelerators represent an indispensable tool in science and industry. However, the size and cost of conventional radio-frequency accelerators limit the utility and reach of this technology. Dielectric laser accelerators (DLAs) provide a compact and cost-effective solution to this problem by driving accelerator nanostructures with visible or near-infrared pulsed lasers, resulting in a 10 4 reduction of scale. Current implementations of DLAs rely on free-space lasers directly incident on the accelerating structures, limiting the scalability and integrability of this technology. In this article, we present an experimental demonstration of a waveguide-integrated DLA that was designed using a photonic inverse-design approach. By comparing the measured electron energy spectra with particle-tracking simulations, we infer a maximum energy gain of 0.915 kilo–electron volts over 30 micrometers, corresponding to an acceleration gradient of 30.5 mega–electron volts per meter. On-chip acceleration provides the possibility for a completely integrated mega–electron volt-scale DLA.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Processing Municipal Solid Waste for Conversion to Jet Fuel (Final Technical Report)

This final report describes the successful demonstration of AI‑assisted waste sorting and a novel pressurized solids feed system to enable conversion of non‑recyclable municipal solid waste to jet fuel under DOE Award DE‑EE0009265. Results include improved feedstock purity and variability reduction, lab‑scale testing, and technoeconomic and life‑cycle assessments.

09 BIOMASS FUELS↗