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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Aerodynamic Performance of Scale-Model Turbofan Outlet Guide Vanes Designed for Low Noise

The design of effective new technologies to reduce aircraft propulsion noise is dependent on an understanding of the noise sources and noise generation mechanisms in the modern turbofan engine. In order to more fully understand the physics of noise in a turbofan engine, a comprehensive aeroacoustic wind tunnel test programs was conducted called the 'Source Diagnostic Test.' The text was cooperative effort between NASA and General Electric Aircraft Engines, as part of the NASA Advanced Subsonic Technology Noise Reduction Program. A 1/5-scale model simulator representing the bypass stage of a current technology high bypass ratio turbofan engine was used in the test. The test article consisted of the bypass fan and outlet guide vanes in a flight-type nacelle. The fan used was a medium pressure ratio design with 22 individual, wide chord blades. Three outlet guide vane design configurations were investigated, representing a 54-vane radial Baseline configuration, a 26-vane radial, wide chord Low Count configuration and a 26-vane, wide chord Low Noise configuration with 30 deg of aft sweep. The test was conducted in the NASA Glenn Research Center 9 by 15-Foot Low Speed Wind Tunnel at velocities simulating the takeoff and approach phases of the aircraft flight envelope. The Source Diagnostic Test had several acoustic and aerodynamic technical objectives: (1) establish the performance of a scale model fan selected to represent the current technology turbofan product; (2) assess the performance of the fan stage with each of the three distinct outlet guide vane designs; (3) determine the effect of the outlet guide vane configuration on the fan baseline performance; and (4) conduct detailed flowfield diagnostic surveys, both acoustic and aerodynamic, to characterize and understand the noise generation mechanisms in a turbofan engine. This paper addresses the fan and stage aerodynamic performance results from the Source Diagnostic Test.

Hughes, Christopher E.↗
NASA NTRS2009

Modeling Joule Heating Effect on Lunar O2 Generation via Electrolytic Reduction.

Kennedy Space Center is leading research work on lunar O2 generation via electrolytic reduction of regolith; the metal oxide present in the regolith is dissociated in oxygen anions and metal cations leading to the generation of gaseous oxygen at the anode and liquid metal at the cathode. Electrical resistance of molten regolith is high, leading to heating of the melt when electrical current is applied between the electrodes (Joule heating). The authors have developed a 3D model using a rigorous approach for two coupled physics (thermal and electrical potential) to not only study the effect of Joule heating on temperature distribution throughout the molten regolith but also to evaluate and optimize the design of the electrolytic cells. This paper presents the results of the thermal analysis performed on the model and used to validate the design of the electrolytic cell.

Dominquez, Jesus↗
DOE OSTI2025

Many-body expansion based machine learning models for octahedral transition metal complexes

Abstract Graph-based machine learning (ML) models for material properties show great potential to accelerate virtual high-throughput screening of large chemical spaces. However, in their simplest forms, graph-based models do not include any 3D information and are unable to distinguish stereoisomers such as those arising from different orderings of ligands around a metal center in coordination complexes. In this work we present a modification to revised autocorrelation descriptors, a molecular graph featurization method, for predicting spin state dependent properties of octahedral transition metal complexes (TMCs). Inspired by analytical semi-empirical models for TMCs, the new modeling strategy is based on the many-body expansion (MBE) and allows one to tune the captured stereoisomer information by changing the truncation order of the MBE. We present the necessary modifications to include this approach in two commonly used ML methods, kernel ridge regression and feed-forward neural networks. On a test set composed of all possible isomers of binary TMCs, the best MBE models achieve mean absolute errors (MAEs) of 2.75 kcal mol −1 on spin-splitting energies and 0.26 eV on frontier orbital energy gaps, a 30%–40% reduction in error compared to models based on our previous approach. We also observe improved generalization to previously unseen ligands where the best-performing models exhibit MAEs of 4.00 kcal mol −1 (i.e. a 0.73 kcal mol −1 reduction) on the spin-splitting energies and 0.53 eV (i.e. a 0.10 eV reduction) on the frontier orbital energy gaps. Because the new approach incorporates insights from electronic structure theory, such as ligand additivity relationships, these models exhibit systematic generalization from homoleptic to heteroleptic complexes, allowing for efficient screening of TMC search spaces.

Meyer, Ralf (ORCID:0000000322360261)↗
DOE OSTI2025

Moltensaltpropnet

MoltenSaltPropnet is a physics-informed machine learning framework that aims to predict the thermophysical properties of molten fluoride and chloride salt mixtures, which are crucial for the design and safety of Generation IV molten salt reactors. The code processes data from the Molten-Salt Thermal Properties Database (MSTDB-TP) and the Janz compendium, converting critically evaluated correlations into fast, differentiable surrogate models for density, viscosity, thermal conductivity, and heat capacity across 448 distinct salt systems. The implementation consists of several key components: 1. Data Curation: The code parses and cleans the raw data, normalizing elemental mole fractions and extracting relevant regression coefficients for various thermophysical properties. 2. Feature Engineering: It generates fixed-length numerical descriptors that encapsulate the composition and temperature, incorporating polynomial interaction terms and dimensionality-reduction techniques to optimize model performance. 3. Coefficient Learning: Four different machine learning architectures are employed: a deep residual network (ResNet), a Kolmogorov–Arnold network (KAN), a sparsity-inducing neural network (SNN), and classical regression models. Each model learns to predict coefficients that define the temperature-dependent correlations for the thermophysical properties. 4. Property Reconstruction: The predicted coefficients are used to compute temperature-dependent property values, ensuring positivity and monotonic trends through a composite loss function that enforces physical constraints. 5. User Interface: An open-source web application enables users to filter the database, train task-specific models, and visualize the results, allowing for rapid exploration of candidate salt mixtures. MoltenSaltPropnet bridges the gap between limited experimental data and high-fidelity reactor simulations, providing a powerful tool for researchers in the field of molten salt reactors and advanced nuclear energy systems.

Retamales, Mauricio Eduardo Tano [Idaho National L↗
NASA NTRS2001

An Experimental Study of the Ground Transportation System (GTS) Model in the NASA Ames 7- by 10-Ft Wind Tunnel

The 1/8-scale Ground Transportation System (GTS) model was studied experimentally in the NASA Ames 7- by 10-Ft Wind Tunnel. Designed for validation of computational fluid dynamics (CFD), the GTS model has a simplified geometry with a cab-over-engine design and no tractor-trailer gap. As a further simplification, all measurements of the GTS model were made without wheels. Aerodynamic boattail plates were also tested on the rear of the trailer to provide a simple geometry modification for computation. The experimental measurements include body-axis drag, surface pressures, surface hot-film anemometry, oil-film interferometry, and 3-D particle image velocimetry (PIV). The wind-averaged drag coefficient with and without boattail plates was 0.225 and 0.277, respectively. PIV measurements behind the model reveal a significant reduction in the wake size due to the flow turning provided by the boattail plates. Hot-film measurements on the side of the cab indicate laminar separation with turbulent reattachment within 0.08 trailer width for zero and +/- 10 degrees yaw. Oil film interferometry provided quantitative measurements of skin friction and qualitative oil flow images. A complete set of the experimental data and the surface definition of the model are included on a CD-ROM for further analysis and comparison.

Storms, Bruce L.↗
NASA NTRS1991

BVI impulsive noise reduction by higher harmonic pitch control - Results of a scaled model rotor experiment in the DNW

Results are presented of a model rotor acoustics test performed to examine the benefit of higher harmonic control (HHC) of blade pitch to reduce blade-vortex interaction (BVI) impulsive noise. A dynamically scaled, four-bladed, rigid rotor model, a 40-percent replica of the B0-105 main rotor, was tested in the German Dutch Wind Tunnel. Noise characteristics and noise directivity patterns as well as vibratory loads were measured and used to demonstrate the changes when different HHC schedules were applied. Dramatic changes of the acoustic signatures and the noise radiation directivity with the HHC phase variations are found. Compared to the baseline conditions (without HHC), significant mid-frequency noise reductions of locally 6 dB are obtained for low-speed descent conditions where GVI is most intense. For other rotor operating conditions with less intense BVI there is less or no benefit from the use of HHC. LF noise and vibratory loads, especially at optimum noise reduction control settings, are found to increase.

Splettstoesser, Wolf R.↗
NASA NTRS2000

Advanced Subsonic Technology (AST) Separate-Flow High-Bypass Ratio Nozzle Noise Reduction Program Test Report

NASA s model-scale nozzle noise tests show that it is possible to achieve a 3 EPNdB jet noise reduction with inwardfacing chevrons and flipper-tabs installed on the primary nozzle and fan nozzle chevrons. These chevrons and tabs are simple devices and are easy to be incorporated into existing short duct separate-flow nonmixed nozzle exhaust systems. However, these devices are expected to cause some small amount of thrust loss relative to the axisymmetric baseline nozzle system. Thus, it is important to have these devices further tested in a calibrated nozzle performance test facility to quantify the thrust performances of these devices. The choice of chevrons or tabs for jet noise suppression would most likely be based on the results of thrust loss performance tests to be conducted by Aero System Engineering (ASE) Inc. It is anticipated that the most promising concepts identified from this program will be validated in full scale engine tests at both Pratt & Whitney and Allied-Signal, under funding from NASA s Engine Validation of Noise Reduction Concepts (EVNRC) programs. This will bring the technology readiness level to the point where the jet noise suppression concepts could be incorporated with high confidence into either new or existing turbofan engines having short-duct, separate-flow nacelles.

Low, John K. C.↗
NASA NTRS1977

The application of remote sensing to the development and formulation of hydrologic planning models: Executive summary

Methods for the reduction of remotely sensed data and its application in hydrologic land use assessment, surface water inventory, and soil property studies are presented. LANDSAT data is used to provide quantitative parameters and coefficients to construct watershed transfer functions for a hydrologic planning model aimed at estimating peak outflow from rainfall inputs.

Castruccio, P. A.↗
NASA NTRS1972

Reduction of Skylab 2 ground winds

A dampometer was designed and fabricated for measuring the amount of damping in the wind tunnel test model. The ground winds data reduction system (GWDRS) was taken to Langley Research Center in support of wind tunnel tests on the Skylab 2 program. Final data reduction of the test results was accomplished by the GWDRS.

Rolfes, M. J.↗
NASA NTRS1954

Summary of Free-Flight Zero-Lift Drag Results from Tests of 1/5-Scale Models of the Convair YF-102 and F-102A Airplanes and Several Related Small Equivalent Bodies at Mach Numbers from 0.70 to 1.46

One-fifth-scale rocket-propelled models of the Convair YF-102 and F-102A airplanes were tested to determine free-flight zero-lift drag coefficients through the transonic speed range at Reynolds numbers near those to be encountered by the full-scale airplane. Trim and duct characteristics were obtained along with measurements of total-, internal-, and base-drag coefficients. Additional zero-lift drag tests involved a series of small equivalent-body-of-revolution models which were launched to low supersonic speeds by means of a helium gun. The several small models tested corresponded to the following full-scale airplanes: basic, YF-102, 2-foot (full-scale) fuselage extension, F-102A, F-102A (relocated inlets), F-102A (faired nose), and F-102A (parabolic nose) . Equivalent-body models corresponding to the normal area distribution (derived for Mach number 1.0) of each of these airplane shapes were flown and, in addition, equivalent-body models designed to represent the YF-102 and F-102A airplanes at Mach number 1.2 were tested. External-drag coefficients obtained from the 115-scale tests ranged from 0.0094 to 0.0273 for the YF-102 model and from 0.0100 to 0.0255 for the F-102A model. Forebody external-pressure-drag coefficients (drag rise) at Mach number 1.05 of 0.0183 and 0.0134 were obtained from the 115-scale models of the YF-102 and F-102A, respectively, a 16-percent reduction for the F-102A model. Values of drag rise at Mach number 1.05 from the small equivalent-body tests were nearly the same for the basic, YF-102, and 2-foot-fuselage-extension airplane shapes. Equivalent-body tests of the YF-102 and F-102A shapes showed the latter to have about 25 percent less drag rise as compared with a 16-percent reduction illustrated by the 1/5-scale tests. Additional equivalent-body tests illustrating effects of modifications to the F-102A airplane shape shared that relocating the inlets on the fuselage or altering the nose shape to provide a smoother cross-sectional area progression reduced the drag rise by approximately 16 percent. Replacing a major portion of the nose of the F-102A equivalent-body model with one of parabolic shape resulted in about a 21-percent reduction in drag rise. The drag-rise data from the equivalent-body tests include base drag.

Wallskog, Harvey A.↗
NASA NTRS1990

Energy management analysis of lunar oxygen production

Energy load models in the process of hydrogen reduction of ilmenite for lunar oxygen production are being developed. The load models will be used as a first step to ultimately determine the optimal energy system needed to supply the power requirements for the process. The goal is to determine the energy requirements in the process of hydrogen reduction of ilmenite to produce oxygen. The general approach is shown, and the objectives are to determine the energy loads of the processes in the system. Subsequent energy management studies will be made to minimize the system losses (irreversibilities) and to design optimal energy system power requirements. A number of processes are being proposed as possible candidates for lunar application and some detailed experimental efforts are being conducted within this project at the University of Arizona. Priorities are directed toward developing the energy models for each of the proposed processes being considered. The immediate goals are to identify the variables that would impact energy requirements and energy sources of supply.

Fazzolari, R.↗
NASA NTRS2017

A Comparative Study of Simulated and Measured Main Landing Gear Noise for Large Civil Transports

Computational results for the NASA 26%-scale model of a six-wheel main landing gear with and without a toboggan-shaped noise reduction fairing are presented. The model is a high-fidelity representation of a Boeing 777-200 aircraft main landing gear. A lattice Boltzmann method was used to simulate the unsteady flow around the model in isolation. The computations were conducted in free-air at a Mach number of 0.17, matching a recent acoustic test of the same gear model in the Virginia Tech Stability Wind Tunnel in its anechoic configuration. Results obtained on a set of grids with successively finer spatial resolution demonstrate the challenge in resolving/capturing the flow field for the smaller components of the gear and their associated interactions, and the resulting effects on the high-frequency segment of the farfield noise spectrum. Farfield noise spectra were computed based on an FWH integral approach, with simulated pressures on the model solid surfaces or flow-field data extracted on a set of permeable surfaces enclosing the model as input. Comparison of these spectra with microphone array measurements obtained in the tunnel indicated that, for the present complex gear model, the permeable surfaces provide a more accurate representation of farfield noise, suggesting that volumetric effects are not negligible. The present study also demonstrates that good agreement between simulated and measured farfield noise can be achieved if consistent post-processing is applied to both physical and synthetic pressure records at array microphone locations.

Konig, Benedikt↗
DOE OSTI2025

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗
NASA NTRS2022

Automatic variable selection in ecological niche modeling: A case study using Cassin’s Sparrow (Peucaea cassinii)

MERRA/Max provides a feature selection approach to dimensionality reduction that enables direct use of global climate model outputs in ecological niche modeling. The system accomplishes this reduction through a Monte Carlo optimization in which many independent MaxEnt runs, operating on a species occurrence file and a small set of randomly selected variables in a large collection of variables, converge on an estimate of the top contributing predictors in the larger collection. These top predictors can be viewed as potential candidates in the variable selection step of the ecological niche modeling process. MERRA/Max’s Monte Carlo algorithm operates on files stored in the underlying filesystem, making it scalable to large data sets. Its software components can run as parallel processes in a high-performance cloud computing environment to yield near real-time performance. In tests using Cassin’s Sparrow (Peucaea cassinii) as the target species, MERRA/Max selected a set of predictors from Worldclim’s Bioclim collection of 19 environmental variables that have been shown to be important determinants of the species’ bioclimatic niche. It also selected biologically and ecologically plausible predictors from a more diverse set of 86 environmental variables derived from NASA’s Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) reanalysis, an output product of the Goddard Earth Observing System Version 5 (GEOS-5) modeling system. We believe these results point to a technological approach that could expand the use global climate model outputs in ecological niche modeling, foster exploratory experimentation with otherwise difficult-to-use climate data sets, streamline the modeling process, and, eventually, enable automated bioclimatic modeling as a practical, readily accessible, low-cost, commercial cloud service.

John L. Schnase↗
NASA NTRS2000

Microwave Driven Actuators Power Allocation and Distribution

Design, fabrication and test of a power allocation and distribution (PAD) network for microwave driven actuators is presented in this paper. Development of a circuit that would collect power from a rectenna array amplify and distribute the power to actuators was designed and fabricated for space application in an actuator array driven by a microwave. A P-SPICE model was constructed initially for data reduction purposes, and was followed by a working real-world model. A voltage up - converter (VUC) is used to amplify the voltage from the individual rectenna. The testing yielded a 26:1 voltage amplification ratio with input voltage at 9 volts and a measured output voltage 230VDC. Future work includes the miniaturization of the circuitry, the use of microwave remote control, and voltage amplification technology for each voltage source. The objective of this work is to develop a model system that will collect DC voltage from an array of rectenna and propagate the voltage to an array of actuators.

Forbes, Timothy↗
NASA NTRS1972

Prediction of electron concentration reductions in re-entry flow fields due to electrophilic liquid and water injection.

Discussion of an analytical model which leads to predictions of reductions in electron concentrations in reentry flow fields due to the injection of electrophilic liquids and water. The processes incorporated into the model are: penetration and breakup of the liquid jet, droplet acceleration and vaporization, expansion of the liquid spray due to droplet vaporization, electrophilic vapor diffusion, heterogeneous and homogeneous charged species recombination kinetics and homogeneous electron attachment kinetics. Spray boundary calculations are shown to be in good agreement with photographic observations of water and Freon E-3 sprays in wind tunnel tests of a scale model RAM C-III flight vehicle. Fixed-bias electrostatic probe data taken during the RAM C-III flight are interpreted in terms of effective jet penetration distances - which are shown to be consistent with calculations using the present model.

Pergament, H. S.↗
NASA NTRS2024

Aera-Mip: Emission Pathways, Remaining Budgets, and Carbon Cycle Dynamics Compatible With 1.5 and 2 °C Global Warming Stabilization

While international climate policies now focus on limiting global warming to well below 2 °C or pursuing a 1.5 °C level of global warming, the climate modelling community has not provided an experimental design in which all Earth system models (ESMs) converge and stabilize at the same prescribed global warming levels. This gap hampers accurate estimations based on comprehensive ESMs of the carbon emission pathways and budgets needed to meet such agreed warming levels and of the associated climate impacts under temperature stabilization. Here, we apply the Adaptive Emission Reduction Approach (AERA) with ESMs to provide such simulations in which all models converge at 1.5 and 2.0 °C warming levels by adjusting their emissions over time. These emission-driven simulations provide a wide range of emission pathways and resulting atmospheric CO 2 projections for a given warming level, uncovering uncertainty ranges that were previously missing in the traditional Coupled Model Intercomparison Project (CMIP) scenarios with prescribed greenhouse gas concentration pathways. Meeting the 1.5 °C warming level requires a 40 % (full model range: 7 % to 76 %) reduction in multi-model mean CO 2 -forcing-equivalent (CO 2 -fe) emissions from 2025 to 2030, a 98 % (57 % to 127 %) reduction from 2025 to 2050, and a stabilization at 1.0 (−1.7 to 2.9) PgC yr−1 from 2100 onward after the 1.5 °C global warming level is reached. Meeting the 2.0 °C warming level requires a 47 % (8 % to 92 %) reduction in multi-model mean CO 2 -fe emissions until 2050 and a stabilization at 1.7 (−1.5 to 2.7) PgC yr−1 from 2100 onward. The on-average positive emissions under stabilized global temperatures are the result of a decreasing transient climate response to cumulative CO 2 -fe emissions over time under stabilized global warming. This evolution is consistent with a slightly negative zero emissions commitment – initially assumed to be zero – and leads to an increase in the post-2025 CO 2 -fe emission budget by a factor of 2.2 (−0.8 to 6.9) by 2150 for the 1.5 °C warming level and a factor of 1.4 (0.9 to 2.4) for the 2.0 °C warming level compared to its first estimate in 2025. The median CO 2 -only carbon budget by 2150, relative to 2020, is 800 GtCO 2 for the 1.5 °C warming level and 2250 GtCO 2 for the 2.0 °C warming level. These median values exceed the median IPCC AR6 estimates by 60 % for the 1.5 °C warming level and 67 % for 2.0 °C. Some of the differences may be explained by the choice of the mitigation scenario for non-CO 2 radiative agents. Our simulations highlight shifts in carbon uptake dynamics under stabilized temperature, such as a cessation of the carbon sinks in the North Atlantic and in tropical forests. On the other hand, the Southern Ocean remains a carbon sink centuries after temperatures stabilize. Overall, this new type of warming-level-based emission-driven simulation offers a more coherent assessment across climate models and opens up a wide range of possibilities for studying both the carbon cycle and climate impacts, such as extreme events, under climate stabilization.

Adaptive Emission Reduction Approach↗
NASA NTRSDate not supplied

Electrochemical Recycling of CO2

Carbon dioxide (CO2) is a molecule that plays multiple roles in our universe. Currently, its impact on global warming has rightfully given CO2 a label as a harmful waste product that must be amply handled. Nonetheless, under other circumstances, and from other perspectives, CO2 could be regarded as a valuable resource. As example, in nature CO2 is an essential building block in photosynthesis ultimately yielding molecules and materials that we harvest for numerous applications ranging from energy storage and construction to medicines and food. In a similar manner, there is a growing interest to utilize atmospheric CO2 to generate renewable fuels and platform chemicals through artificial processes. These processes can replace fossil based industrial processes on earth alleviating climate impact, but they can also find uses far away from our planet. In space, CO2 is an important source of precious oxygen, however, it can also serve as feedstock for carbon-based molecules and materials that are needed to sustain societies at distant planets such as Mars. In this presentation, I will discuss the contemporary understanding of electrochemical reduction of CO2 for selective production of desired molecules. We will zoom in to the very atomic scale to gain mechanistic understanding of how the structure and composition of the cathode electrode affects product distributions. This information is used as guide in the design of new materials that convert CO2 more efficiently and more selectively. On this basis, opportunities for recycling CO2 under different conditions will be discussed, as will remaining challenges for the ultimate application towards the sustainable human living on earth and in space.

electrochemistry↗