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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Computer study of a jet flap ASTVOL 'Harrier'

A study of the costs/benefits trade-off was conducted for an Advanced Supersonic Short Takeoff and Vertical Landing (ASTOVL) aircraft incorporating a jet flap. The data used were the theory of jet flaps and high aspect ratio nozzles, experience with a V/STOL aircraft study performed for NASA Ames Research Center in February 1982, and a high performance aircraft-synthesis program (ACSYNT). The methodology was to accurately model the supersonic Harrier V/STOL aircraft design on ACSYNT, and then modify the design by both adding high aspect-ratio nozzles in place of the rear (core-flow) nozzles on the Pegasus-type turbofan engine, and integrating these nozzles on each wing's trailing edge, thus creating a jet flap. The predicted performance advantages (increase in maximum lift coefficient with flap deflection and horizontal thrust recovery) were traded off against the disadvantages (additional weight and thrust loss due to ducting) on two representative missions.

Wilson, S. B., III↗
NASA NTRS1995

Aerothermodynamic Facilities And Measurement: Flow Characterization in Shock Tunnels

This presentation will examine the key performance aspects of shock tunnels as they relate to their use as aerothermodynamic flow simulation facilities. Assessment of shock tube reservoir conditions and flow contaminants generated in the shock tube will be presented along with their limiting impact on viable test envelopes, Facility nozzle performance as it pertains to test time assessment and nozzle exit flow quality (survey of pressure, temperature, and species) will be addressed. Also included will be a discussion of free stream flow diagnostics, both intrusive and nonintrusive, for measurement of critical flow properties not directly inferred from surface mounted transducers. The use of computational fluid dynamics for purposes of validating experimental measurements as well as predicting performance in regimes where measurements are not feasible or possible will be discussed. The use of CFD for facility research and design will also be presented.

Cavolowsky, John A.↗
NASA NTRS2002

Intersymbol Interference Investigations Using a 3D Time-Dependent Traveling Wave Tube Model

For the first time, a time-dependent, physics-based computational model has been used to provide a direct description of the effects of the traveling wave tube amplifier (TWTA) on modulated digital signals. The TWT model comprehensively takes into account the effects of frequency dependent AM/AM and AM/PM conversion; gain and phase ripple; drive-induced oscillations; harmonic generation; intermodulation products; and backward waves. Thus, signal integrity can be investigated in the presence of these sources of potential distortion as a function of the physical geometry and operating characteristics of the high power amplifier and the operational digital signal. This method promises superior predictive fidelity compared to methods using TWT models based on swept- amplitude and/or swept-frequency data. First, the TWT model using the three dimensional (3D) electromagnetic code MAFIA is presented. Then, this comprehensive model is used to investigate approximations made in conventional TWT black-box models used in communication system level simulations. To quantitatively demonstrate the effects these approximations have on digital signal performance predictions, including intersymbol interference (ISI), the MAFIA results are compared to the system level analysis tool, Signal Processing Workstation (SPW), using high order modulation schemes including 16 and 64-QAM.

Kory, Carol L.↗
DOE OSTI2024

Pressure-Gradient-Based RANS Model for Predicting Separation in Transitional and Turbulent Flows

Predicting flow separation poses a significant challenge for RANS models, particularly in transitional flows over airfoils. We propose a novel improvement to RANS models to predict incipient separation in both transitional and fully turbulent flows. Our approach modifies the eddy viscosity model in regions indicated by a pressure-gradient criterion that accounts for intermittency - determining whether the boundary layer is laminar or turbulent. This model demonstrates robust generalization across various airfoil shapes and Reynolds numbers. Applied to the NREL Phase VI wind turbine rotor, our model shows improved aerodynamic performance predictions compared to the baseline RANS model.

k-omega SST↗
DOE OSTI2025

Optimizing flow condensation models for next-generation refrigerants in axial micro-fin aluminum tubes

To support the transition to next-generation refrigerants, accurate modelling of heat transfer and pressure drop is essential for designing efficient heat exchangers. Current models, largely based on traditional refrigerants and unexpanded micro-fin tubes, may not reliably predict performance for new refrigerants and expanded micro-fin geometries. This study evaluates four condensation models using experimental data for six A2L refrigerants: R-32, R-454B, R-454C, R-455A, R-1234yf, and R-1234ze(E). For heat transfer models, the Han and Lee (2005) model initially yields the best accuracy (mean absolute Deviation, MAD = 22.1%). To further improve predictions, a correction factor reduces the Cavallini et al. (2009) model’s MAD from 68.2% to 15.4%, while optimization of the Kedzierski and Goncalves (1997) model achieves a MAD of 13.1%. For pressure drop, the Cavallini et al. (1997) model proves most accurate (MAD = 6.4%), with the simpler Haraguchi et al. (1993) model also effective (MAD = 9.4%). Keywords: Flow condensation models, heat transfer coefficient, frictional pressure drop, next-generation refrigerants, aluminum micro-fin tubes

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗
NASA NTRS1993

Prediction of static performance for single expansion ramp nozzles

A multiblock three-dimensional Navier-Stokes method was utilized in a two-dimensional fully implicit mode to calculate the flowfield of a single expansion ramp nozzle configuration. The code has been shown previously to be fairly accurate in predicting three-dimensional nozzle flowfields and internal performance for several axisymmetric and nonaxisymmetric geometries. A two-dimensional implementation of the method was used to reduce the resources required to obtain preliminary performance parameters of nozzle concepts. A two-dimensional description of a single-expansion ramp nozzle configuration was analyzed to verify the applicability of the Navier-Stokes code and nozzle performance package to this class of nozzles. Internal static pressure distributions, discharge coefficient and thrust ratio quantities were calculated for a range of operating conditions. Comparisons of predicted performance parameters with experimental data were within 0.5 percent for mass flow, and typically within l.5 percent for thrust ratio.

Carlson, John R.↗
NASA NTRS1992

Calculation of installation effects within performance computer programs

Gasturbine engine components as compressors, burners and turbines are usually tested on rigs prior to installation into an engine. In the engine, the component behaviour is different due to a variety of reasons. The installation effects are caused by small geometrical differences due to nonrepresentative rig operating temperatures and pressures, by different gas properties and Reynolds numbers and by radial as well as circumferential temperature and pressure profiles at the inlet to the component. For highly accurate performance predictions these rig-to-engine effects have to be taken into account. Traditionally the term "installation" is also used for describing all the differences in engine operation and behaviour between toothed and aircraft. Intake and afterbody drag, power offtake and bleed as well as intake pressure losses and inlet flow distortion have significant impact on airflow, thrust, specific fuel consumption and compressor stability. Using modem performance synthesis programs all these effects can be simulated reasonably well.

J Kurzke↗
NASA NTRS2002

Higher Order Modulation Intersymbol Interference Caused by Traveling-wave Tube Amplifiers

For the first time, a time-dependent, physics-based computational model has been used to provide a direct description of the effects of the traveling wave tube amplifier (TWTA) on modulated digital signals. The TWT model comprehensively takes into account the effects of frequency dependent AM/AM and AM/PM conversion; gain and phase ripple; drive-induced oscillations; harmonic generation; intermodulation products; and backward waves, Thus, signal integrity can be investigated in the presence of these sources of potential distortion as a function of the physical geometry and operating characteristics of the high power amplifier and the operational digital signal. This method promises superior predictive fidelity compared to methods using TWT models based on swept-amplitude and/or swept-frequency data. First, the TWT model using the three dimensional (3D) electromagnetic code MAFIA is presented. Then, this comprehensive model is used to investigate approximations made in conventional TWT black-box models used in communication system level simulations, To quantitatively demonstrate the effects these approximations have on digital signal performance predictions, including intersymbol interference (ISI), the MAFIA results are compared to the system level analysis tool, Signal Processing, Workstation (SPW), using high order modulation schemes including 16 and 64-QAM.

Kory, Carol L.↗
NASA NTRS1990

Thermal performance of a five year lifetime superfluid helium dewar for SIRTF

The Space Infrared Telescope Facility (SIRTF) is a 1 m class cryogenically cooled observatory for infrared astronomy. The SIRTF cryogenic system has to satisfy the five year mission lifetime requirement as well as to provide sufficient cooling for the science instruments and optical system. A 4000 cu dm superfluid helium dewar has been selected for the current baseline cryogenic system which represents the largest superfluid helium dewar proposed to date for a long lifetime space-borne application. This paper discusses the design and predicted performance of the current cryogenic system, as well as its comparison with IRAS and other space-borne superfluid helium dewars currently under development.

Lee, J. H.↗
NASA NTRSDate not supplied

Autonomous Navigation of a Lunar Relay Using GNSS and Other Measurements

Many of the highest priority destinations at the Moon lack a continuous view of Earth, such as the lunar poles or lunar far side. Exploration of these sites will require spacecraft in cislunar space to relay communications and provide position, navigation, and timing (PNT) services. Accurate knowledge of relay position, velocity, and time is essential to these services. This paper describes a concept for a PNT Instrument being developed for the Lunar Communications Relay and Navigation Systems (LCRNS) Project. The instrument is intended as a payload that would enable autonomous, on-board, real-time navigation and timing using Global Navigation Satellite System (GNSS), optical navigation, and one-way measurements from Earth-based ground stations. Hardware-in-the-loop simulations using flight software are used to realistically characterize performance on hardware platforms with a path to flight. These results provide preliminary validation of the proposed PNT Instrument, demonstrate the benefits of augmenting GNSS with other measurements, and serve as an insightful reference for the design of future lunar missions, including those that will operate within the LunaNet framework of standards. This instrument concept relies on several technologies developed at NASA Goddard Space Flight Center (GSFC). For GNSS observables, the instrument relies on the high-altitude NavCube 3 mini (NC3m) GNSS receiver specifically designed for cislunar applications. The autoNGC system, which consists of flight software and a hardware platform, is responsible for fusing the observables using its extended Kalman filter, the Goddard Enhanced Onboard Navigation System (GEONS). Optical navigation observables are processed within autoNGC (“autonomous Navigation, Guidance, and Control”) using the Goddard Image Analysis & Navigation Tool (GIANT) which is also responsible for simulating high-fidelity images for test and analysis. In addition to describing the PNT Instrument and its components, the paper will present predicted performance based on simulation results. As a baseline, it will present GNSS-only hardware-in-the loop results using a NC3m test unit to process Spirent-simulated GPS signals in a potential lunar relay trajectory: a 12-hour elliptical frozen lunar orbit (ELFO). GEONS then processes the GPS pseudorange and time differenced carrier phase measurements to estimate and propagate the relay state (position, velocity, and time). These results extend previously published work that showed preliminary ELFO performance. Previous work has shown the importance of other measurement types, so additional simulations are performed which augment GNSS with ground station observables and several methods of optical navigation, including celestial navigation, limb-finding (e.g., observations of the lunar horizon), and terrain relative navigation (TRN). TRN involves correlating simulated predicted images of the lunar surface with actual imagery; misalignments of landmarks identified in each image are translated into relay state updates. TRN is valuable as a measurement of the relay’s state relative to the Moon, especially during GNSS outages or after maneuvers. One-way Pseudorange and Doppler measurements from Earth-based ground stations are also simulated. The full set of observables is processed using autoNGC. These simulations make use of autoNGC and NC3m test units, a lab atomic clock, and a pulse-per-second (PPS) generation and distribution system. This combination of subsystems, and the hardware platforms used in this analysis, represents a PNT Instrument that could be flown on a lunar relay. Results from the hardware-in-the-loop simulations presented in this paper provide a preliminary assessment of the achievable navigation performance of this instrument concept. PNT Instrument performance is compared to the GPS-only performance, and a discussion is provided on the apparent merits and challenges of each measurement type.

Ben Ashman↗
DOE OSTI2020

Improving five-year survival prediction via multitask learning across HPV-related cancers

Oncology is a highly siloed field of research in which sub-disciplinary specialization has limited the amount of information shared between researchers of distinct cancer types. This can be attributed to legitimate differences in the physiology and carcinogenesis of cancers affecting distinct anatomical sites. However, underlying processes that are shared across seemingly disparate cancers probably affect prognosis. The objective of the current study is to investigate whether multitask learning improves 5-year survival cancer patient survival prediction by leveraging information across anatomically distinct HPV related cancers. Furthermore, data were obtained from the Surveillance, Epidemiology, and End Results (SEER) program database. The study cohort consisted of 29,768 primary cancer cases diagnosed in the United States between 2004 and 2015. Ten different cancer diagnoses were selected, all with a known association with HPV risk. In the analysis, the cancer diagnoses were categorized into three distinct topography groups of varying specificity. The most specific topography grouping consisted of 10 original cancer diagnoses differentiated by the first two digits of the ICD-O-3 topography code. The second topography grouping consisted of cancer diagnoses categorized into six distinct organ groups. Finally, the third topography grouping consisted of just two groups, head-neck cancers and ano-genital cancers. The tasks were to predict 5-year survival for patients within the different topography groups using 14 predictive features which were selected among descriptive variables available in the SEER database. The information from the predictive features was shared between tasks in three different ways, resulting in three distinct predictive models: 1) Information was not shared between patients assigned to different tasks (single task learning); 2) Information was shared between all patients, regardless of task (pooled model); 3) Only relevant information was shared between patients grouped to different tasks (multitask learning). Prediction performance was evaluated with Brier scores. All three models were evaluated against one another on each of the three distinct topography-defined tasks. The results showed that multitask classifiers achieved relative improvement for the majority of the scenarios studied compared to single task learning and pooled baseline methods. In this study, we have demonstrated that sharing information among anatomically distinct cancer types can lead to improved predictive survival models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

The Evaluation of Machine Learning Techniques for Isotope Identification Contextualized by Training and Testing Spectral Similarity

Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset and evaluated on twelve other datasets with varying standoff distances, shielding, and background configurations. A tailored statistical approach was introduced to quantify the similarity between the training and testing configurations, which was then related to the predictive performance. Wilcoxon signed-rank tests revealed that the OVR-wrapped XGB significantly outperformed the other algorithms, with confidence levels of 99.0% or above for the 133Ba, 60Co, 137Cs, and 152Eu sources. The findings from this work are significant as they outline techniques to promote the development of robust ML-based approaches for isotope identification.

domain adaptation↗
NASA NTRS1972

Development of advanced fuel cell system

Weight, life and performance characteristics optimization of hydrogen-oxygen fuel cell power systems were considered. A promising gold alloy cathode catalyst was identified and tested in a cell for 5,000 hours. The compatibility characteristics of candidate polymer structural materials were measured after exposure to electrolyte and water vapor for 8,000 hours. Lightweight cell designs were prepared and fabrication techniques to produce them were developed. Testing demonstrated that predicted performance was achieved. Lightweight components for passive product water removal and evaporative cooling of cells were demonstrated. Systems studies identified fuel cell powerplant concepts for meeting the requirements of advanced spacecraft.

Grevstad, P. E.↗
NASA NTRS2002

Multi-Zone Liquid Thrust Chamber Performance Code with Domain Decomposition for Parallel Processing

Computational Fluid Dynamics (CFD) has considerably evolved in the last decade. There are many computer programs that can perform computations on viscous internal or external flows with chemical reactions. CFD has become a commonly used tool in the design and analysis of gas turbines, ramjet combustors, turbo-machinery, inlet ducts, rocket engines, jet interaction, missile, and ramjet nozzles. One of the problems of interest to NASA has always been the performance prediction for rocket and air-breathing engines. Due to the complexity of flow in these engines it is necessary to resolve the flowfield into a fine mesh to capture quantities like turbulence and heat transfer. However, calculation on a high-resolution grid is associated with a prohibitively increasing computational time that can downgrade the value of the CFD for practical engineering calculations. The Liquid Thrust Chamber Performance (LTCP) code was developed for NASA/MSFC (Marshall Space Flight Center) to perform liquid rocket engine performance calculations. This code is a 2D/axisymmetric full Navier-Stokes (NS) solver with fully coupled finite rate chemistry and Eulerian treatment of liquid fuel and/or oxidizer droplets. One of the advantages of this code has been the resemblance of its input file to the JANNAF (Joint Army Navy NASA Air Force Interagency Propulsion Committee) standard TDK code, and its automatic grid generation for JANNAF defined combustion chamber wall geometry. These options minimize the learning effort for TDK users, and make the code a good candidate for performing engineering calculations. Although the LTCP code was developed for liquid rocket engines, it is a general-purpose code and has been used for solving many engineering problems. However, the single zone formulation of the LTCP has limited the code to be applicable to problems with complex geometry. Furthermore, the computational time becomes prohibitively large for high-resolution problems with chemistry, two-equation turbulence model, and two-phase flow. To overcome these limitations, the LTCP code is rewritten to include the multi-zone capability with domain decomposition that makes it suitable for parallel processing, i.e., enabling the code to run every zone or sub-domain on a separate processor. This can reduce the run time by a factor of 6 to 8, depending on the problem.

Homayun K. Navaz↗
DOE OSTI2024

Invariant Features for Accurate Predictions of Quantum Chemical UV-vis Spectra of Organic Molecules

Including invariance of global properties of a phys-ical system as an intrinsic feature in graph neural networks (GNNs) enhances the model's robustness and generalizability and reduces the amount of training data required to obtain a desired accuracy for predictions of these properties. Existing open source GNN libraries construct invariant features only for specific GNN architectures. This precludes the generalization of invariant features to arbitrary message passing neural network (MPNN) layers which, in turn, precludes the use of these libraries for new, user-specified predictive tasks. To address this limitation, we implement invariant MPNNs into the flexible and scalable HydraGNN architecture. HydraGNN enables a seamless switch between various MPNNs in a unified layer sequence and allows for a fair comparison between the predictive performance of different MPNNs. We trained this enhanced HydraGNN archi-tecture on the ultraviolet-visible (UV-vis) spectrum of GDB-9 molecules, a feature that describes the molecule's electronic exci-tation modes, computed with time-dependent density functional tight binding (TD-DFTB) and available open source through the GDB-9-Ex dataset. We assess the robustness (i.e., accuracy and generalizability) of the predictions obtained using different invariant MPNNs with respect to different values of the full width at half maximum (FWHM) for the Gaussian smearing of the theoretical peaks. Our numerical results show that incorporating invariance in the HydraGNN architecture significantly enhances both accuracy and generalizability in predicting UV-vis spectra of organic molecules.

Baker, Justin↗
DOE OSTI2021

Preparing an Incompressible-Flow Fluid Dynamics Code for Exascale-Class Wind Energy Simulations

The U.S. Department of Energy has identified exascale-class wind farm simulation as critical to wind energy scientific discovery. A primary objective of the ExaWind project is to build high-performance, predictive computational fluid dynamics (CFD) tools that satisfy these modeling needs. GPU accelerators will serve as the computational thoroughbreds of next-generation, exascale-class supercomputers. Here, we report on our efforts in preparing the ExaWind unstructured mesh solver, Nalu-Wind, for exascale-class machines. For computing at this scale, a simple port of the incompressible-flow algorithms to GPUs is insufficient. To achieve high performance, one needs novel algorithms that are application aware, memory efficient, and optimized for the latest-generation GPU devices. The result of our efforts are unstructured-mesh simulations of wind turbines that can effectively leverage thousands of GPUs. In particular, we demonstrate a first-of-its-kind, incompressible-flow simulation using Algebraic Multigrid solvers that strong scales to more than 4000 GPUs on the Summit supercomputer.

algebraic multigrid↗
NASA NTRS2016

The Athena X-ray Integral Field Unit (X-IFU)

The X-ray Integral Field Unit (X-IFU) on board the Advanced Telescope for High-ENergy Astrophysics (Athena) will provide spatially resolved high-resolution X-ray spectroscopy from 0.2 to 12 keV, with 5 pixels over a field of view of 5 arc minute equivalent diameter and a spectral resolution of 2.5 eV up to 7 keV. In this paper, we first review the core scientific objectives of Athena, driving the main performance parameters of the X-IFU, namely the spectral resolution, the field of view, the effective area, the count rate capabilities, the instrumental background. We also illustrate the breakthrough potential of the X-IFU for some observatory science goals. Then we brie y describe the X-IFU design as defined at the time of the mission consolidation review concluded in May 2016, and report on its predicted performance. Finally, we discuss some options to improve the instrument performance while not increasing its complexity and resource demands (e.g. count rate capability, spectral resolution). (2016) .

Space telescopes↗
DOE OSTI2024

Leveraging Calibration Transfer Techniques for Remote Monitoring of Samarium and Europium in LiCl Using Laser-Induced Florescence Spectroscopy for Radioisotope Production Applications

Radioisotope production relies on complex chemical processes that must be performed in radiological hot cells or glove boxes because of the radioactive and otherwise hazardous materials being used. In these situations, optical sensors can provide real-time monitoring to users, which is unobtainable by more traditional methods. This study explores the use of calibration transfer methods to train a model on one instrument and date and then transfer it to another instrument of the same or different configuration on a different date. By performing laser-induced fluorescence measurements of Eu(III) and Sm(III) in 10 M LiCl over the course of 6 months using two disparate spectrometers and two different training sets, a strategy for calibrating and deploying models for online monitoring was established. Three transfer techniques were compared: direct standardization (DS), piecewise direct standardization (PDS), and external parameter orthogonalization (EPO). DS and PDS outperformed EPO for day-to-day transfers, and EPO was not effective for instrument-to-instrument transfers. Transferring the initial date’s full factorial model provided better prediction performance compared with retraining models the day of measurements using a D-optimal designed calibration set. For both day-to-day and instrument-to-instrument transfers, five Kennard–Stone selected samples were sufficient. Based on this choice, the initial-date, high-resolution spectrometer model was transferred to a lower-resolution, compact spectrometer 6 months later to monitor a simulated, real-time demonstration. Here, the combined predictions of the DS and PDS transferred models were able to accurately track the anticipated concentration profiles, maintaining root-mean-square error of prediction values below 10 ppm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗