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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 577 records · Page 32

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NASA NTRS1986

Discrimination of natural and cultivated vegetation using Thematic Mapper spectral data

The availability of high quality spectral data from the current suite of earth observation satellite systems offers significant improvements in the ability to survey and monitor food and fiber production on both a local and global basis. Current research results indicate that Landsat TM data when used in either digital or analog formats achieve higher land-cover classification accuracies than MSS data using either comparable or improved spectral bands and spatial resolution. A review of these quantitative results is presented for both natural and cultivated vegetation.

Degloria, Stephen D.↗

NASA NTRS1993

Rotational frequencies of transition metal hydrides for astrophysical searches in the far-infrared

Accurate frequencies for the lowest rotational transitions of five transition metal hydrides (CrH, FeH, CoH, NiH, and CuH) in their ground electronic states are reported to help the identification of these species in astrophysical sources from their far-infrared spectra. Accurate frequencies are determined in two ways: for CuH, by calculation from rotational constants determined from higher J transitions with an accuracy of 190 kHz; for the other species, by extrapolation to zero magnetic field from laser magnetic resonance spectra with an accuracy of 0.7 MHz.

Brown, John M.↗

NASA NTRS1998

Variable Complexity Structural Optimization of Shells

Structural designers today face both opportunities and challenges in a vast array of available analysis and optimization programs. Some programs such as NASTRAN, are very general, permitting the designer to model any structure, to any degree of accuracy, but often at a higher computational cost. Additionally, such general procedures often do not allow easy implementation of all constraints of interest to the designer. Other programs, based on algebraic expressions used by designers one generation ago, have limited applicability for general structures with modem materials. However, when applicable, they provide easy understanding of design decisions trade-off. Finally, designers can also use specialized programs suitable for designing efficiently a subset of structural problems. For example, PASCO and PANDA2 are panel design codes, which calculate response and estimate failure much more efficiently than general-purpose codes, but are narrowly applicable in terms of geometry and loading. Therefore, the problem of optimizing structures based on simultaneous use of several models and computer programs is a subject of considerable interest. The problem of using several levels of models in optimization has been dubbed variable complexity modeling. Work under NASA grant NAG1-1808 has been concerned with the development of variable complexity modeling strategies with special emphasis on response surface techniques. In addition several modeling issues for the design of shells of revolution were studied.

Haftka, Raphael T.↗

NASA NTRS1999

Variable Complexity Structural Optimization of Shells

Structural designers today face both opportunities and challenges in a vast array of available analysis and optimization programs. Some programs such as NASTRAN, are very general, permitting the designer to model any structure, to any degree of accuracy, but often at a higher computational cost. Additionally, such general procedures often do not allow easy implementation of all constraints of interest to the designer. Other programs, based on algebraic expressions used by designers one generation ago, have limited applicability for general structures with modem materials. However, when applicable, they provide easy understanding of design decisions trade-off. Finally, designers can also use specialized programs suitable for designing efficiently a subset of structural problems. For example, PASCO and PANDA2 are panel design codes, which calculate response and estimate failure much more efficiently than general-purpose codes, but are narrowly applicable in terms of geometry and loading. Therefore, the problem of optimizing structures based on simultaneous use of several models and computer programs is a subject of considerable interest. The problem of using several levels of models in optimization has been dubbed variable complexity modeling. Work under NASA grant NAG1-2110 has been concerned with the development of variable complexity modeling strategies with special emphasis on response surface techniques. In addition, several modeling issues for the design of shells of revolution were studied.

Haftka, Raphael T.↗

NASA NTRS2000

Rapid Model Fabrication and Testing for Aerospace Vehicles

Advanced methods for rapid fabrication and instrumentation of hypersonic wind tunnel models are being developed and evaluated at NASA Langley Research Center. Rapid aeroheating model fabrication and measurement techniques using investment casting of ceramic test models and thermographic phosphors are reviewed. More accurate model casting techniques for fabrication of benchmark metal and ceramic test models are being developed using a combination of rapid prototype patterns and investment casting. White light optical scanning is used for coordinate measurements to evaluate the fabrication process and verify model accuracy to +/- 0.002 inches. Higher-temperature (<210C) luminescent coatings are also being developed for simultaneous pressure and temperature mapping, providing global pressure as well as global aeroheating measurements. Together these techniques will provide a more rapid and complete experimental aerodynamic and aerothermodynamic database for future aerospace vehicles.

Buck, Gregory M.↗

NASA NTRS2003

Assessing model uncertainty in the conceptual design of a monopropellant propulsion system

An assessment of model uncertainty via probabilistic methods is described. An important question that arises in conceptual design is how accurate do models have to be to be useful? That is to say, when do other uncertainties in higher fidelity model counteract its accuracy when compared to a lower fidelity model faced with these same uncertainties?.

model uncertainty probabilistic methods conceptual↗

NASA NTRS2014

Development of the Glenn Heat-Transfer (Glenn-HT) Computer Code to Enable Time-Filtered Navier-Stokes (TFNS) Simulations and Application to Film Cooling on a Flat Plate Through Long Cooling Tubes

Computational fluid dynamics (CFD) analysis using Reynolds-averaged Navier-Stokes (RANS) formulation for turbomachinery-related flows has enabled improved engine component designs. RANS methodology has limitations that are related to its inability to accurately describe the spectrum of flow phenomena encountered in engines. Examples of flows that are difficult to compute accurately with RANS include phenomena such as laminar/turbulent transition, turbulent mixing due to mixing of streams, and separated flows. Large eddy simulation (LES) can improve accuracy but at a considerably higher cost. In recent years, hybrid schemes that take advantage of both unsteady RANS and LES have been proposed. This study investigated an alternative scheme, the time-filtered Navier-Stokes (TFNS) method applied to compressible flows. The method developed by Shih and Liu was implemented in the Glenn-Heat-Transfer (Glenn-HT) code and applied to film-cooling flows. In this report the method and its implementation is briefly described. The film effectiveness results obtained for film cooling from a row of 30deg holes with a pitch of 3.0 diameters emitting air at a nominal density ratio of unity and two blowing ratios of 0.5 and 1.0 are shown. Flow features under those conditions are also described.

Ameri, Ali↗

NASA NTRS2014

Development of the Glenn-HT Computer Code to Enable Time-Filtered Navier-Stokes (TFNS) Simulations and Application to Film Cooling on a Flat Plate Through Long Cooling Tubes

Computational fluid dynamics (CFD) analysis using Reynolds-averaged Navier-Stokes (RANS) formulation for turbomachinery-related flows has enabled improved engine component designs. RANS methodology has limitations which are related to its inability to accurately describe the spectrum of flow phenomena encountered in engines. Examples of flows that are difficult to compute accurately with RANS include phenomena such as laminarturbulent transition, turbulent mixing due to mixing of streams, and separated flows. Large eddy simulation (LES) can improve accuracy but at a considerably higher cost. In recent years, hybrid schemes which take advantage of both unsteady RANS and LES have been proposed. This study investigated an alternative scheme, the time-filtered Navier-Stokes (TFNS) method applied to compressible flows. The method developed by Shih and Liu was implemented in the Glenn-HT code and applied to film cooling flows. In this report the method and its implementation is briefly described. The film effectiveness results obtained for film cooling from a row of 30 holes with a pitch of 3.0 diameters emitting air at a nominal density ratio of unity and four blowing ratios of 0.5, 1.0, 1.5 and 2.0 are shown. Flow features under those conditions are also described.

infrared↗

NASA NTRS2014

Development of the Glenn-Heat-Transfer (Glenn-HT) Computer Code to Enable Time-Filtered Navier Stokes (TFNS) Simulations and Application to Film Cooling on a Flat Plate Through Long Cooling Tubes

heat transfer↗

NASA NTRS1983

Sea ice motion measurements from Seasat SAR images

Data from the Seasat synthetic aperture radar (SAR) experiment are analyzed in order to determine the accuracy of this information for mapping the distribution of sea ice and its motion. Data from observations of sea ice in the Beaufort Sea from seven sequential orbits of the satellite were selected to study the capabilities and limitations of spaceborne radar application to sea-ice mapping. Results show that there is no difficulty in identifying homologue ice features on sequential radar images and the accuracy is entirely controlled by the accuracy of the orbit data and the geometric calibration of the sensor. Conventional radargrammetric methods are found to serve well for satellite radar ice mapping, while ground control points can be used to calibrate the ice location and motion measurements in the cases where orbit data and sensor calibration are lacking. The ice motion was determined to be approximately 6.4 + or - 0.5 km/day. In addition, the accuracy of pixel location was found over land areas. The use of one control point in 10,000 sq km produced an accuracy of about + or 150 m, while with a higher density of control points (7 in 1000 sq km) the location accuracy improves to the image resolution of + or - 25 m. This is found to be applicable for both optical and digital data.

Leberl, F.↗

NASA NTRS1987

A spectral-knowledge-based approach for urban land-cover discrimination

A prototype expert system was developed to demonstrate the feasibility of classifying multispectral remotely sensed data on the basis of spectral knowledge. The spectral expert was developed and tested with Thematic Mapper Simulator (TMS) data having eight spectral bands and a spatial resolution of 5 m. A knowledge base was developed that describes the target categories in terms of characteristic spectral relationships. The knowledge base was developed under the following assumptions: the data are calibrated to ground reflectance, the area is well illuminated, the pixels are dominated by a single category, and the target categories can be recognized without the use of spatial knowledge. Classification decisions are made on the basis of convergent evidence as derived from applying the spectral rules to a multiple spatial resolution representation of the image. The spectral expert achieved an accuracy of 80-percent correct or higher in recognizing 11 spectral categories in TMS data for the washington, DC, area. Classification performance can be expected to decrease for data that do not satisfy the above assumptions as illustrated by the 63-percent accuracy for 30-m resolution Thematic Mapper data.

Wharton, Stephen W.↗

NASA NTRS2000

A New Method for Accurate Treatment of Flow Equations in Cylindrical Coordinates Using Series Expansions

The motivation of this work is the ongoing effort at the Center for Turbulence Research (CTR) to use large eddy simulation (LES) techniques to calculate the noise radiated by jet engines. The focus on engine exhaust noise reduction is motivated by the fact that a significant reduction has been achieved over the last decade on the other main sources of acoustic emissions of jet engines, such as the fan and turbomachinery noise, which gives increased priority to jet noise. To be able to propose methods to reduce the jet noise based on results of numerical simulations, one first has to be able to accurately predict the spatio-temporal distribution of the noise sources in the jet. Though a great deal of understanding of the fundamental turbulence mechanisms in high-speed jets was obtained from direct numerical simulations (DNS) at low Reynolds numbers, LES seems to be the only realistic available tool to obtain the necessary near-field information that is required to estimate the acoustic radiation of the turbulent compressible engine exhaust jets. The quality of jet-noise predictions is determined by the accuracy of the numerical method that has to capture the wide range of pressure fluctuations associated with the turbulence in the jet and with the resulting radiated noise, and by the boundary condition treatment and the quality of the mesh. Higher Reynolds numbers and coarser grids put in turn a higher burden on the robustness and accuracy of the numerical method used in this kind of jet LES simulations. As these calculations are often done in cylindrical coordinates, one of the most important requirements for the numerical method is to provide a flow solution that is not contaminated by numerical artifacts. The coordinate singularity is known to be a source of such artifacts. In the present work we use 6th order Pade schemes in the non-periodic directions to discretize the full compressible flow equations. It turns out that the quality of jet-noise predictions using these schemes is especially sensitive to the type of equation treatment at the singularity axis. The objective of this work is to develop a generally applicable numerical method for treating the singularities present at the polar axis, which is particularly suitable for highly accurate finite-differences schemes (e.g., Pade schemes) on non-staggered grids. The main idea is to reinterpret the regularity conditions developed in the context of pseudo-spectral methods. A set of exact equations at the singularity axis is derived using the appropriate series expansions for the variables in the original set of equations. The present treatment of the equations preserves the same level of accuracy as for the interior scheme. We also want to point out the wider utility of the method, proposed here in the context of compressible flow equations, as its extension for incompressible flows or for any other set of equations that are solved on a non-staggered mesh in cylindrical coordinates with finite-differences schemes of various level of accuracy is straightforward. The robustness and accuracy of the proposed technique is assessed by comparing results from simulations of laminar forced-jets and turbulent compressible jets using LES with similar calculations in which the equations are solved in Cartesian coordinates at the polar axis, or in which the singularity is removed by employing a staggered mesh in the radial direction without a mesh point at r = 0.

Constantinescu, G.S.↗

NASA NTRS2001

Routine High-Resolution Forecasts/Analyses for the Pacific Disaster Center: User Manual

Enclosed herein is our HWCMO user manual. This manual constitutes the final report for our NASA/PDC grant, NASA NAG5-8730, "Routine High Resolution Forecasts/Analysis for the Pacific Disaster Center". Since the beginning of the grant, we have routinely provided experimental high resolution forecasts from the RSM/MSM for the Hawaii Islands, while working to upgrade the system to include: (1) a more robust input of NCEP analyses directly from NCEP; (2) higher vertical resolution, with increased forecast accuracy; (3) faster delivery of forecast products and extension of initial 1-day forecasts to 2 days; (4) augmentation of our basic meteorological and simplified fireweather forecasts to firedanger and drought forecasts; (5) additional meteorological forecasts with an alternate mesoscale model (MM5); and (6) the feasibility of using our modeling system to work in higher-resolution domains and other regions. In this user manual, we provide a general overview of the operational system and the mesoscale models as well as more detailed descriptions of the models. A detailed description of daily operations and a cost analysis is also provided. Evaluations of the models are included although it should be noted that model evaluation is a continuing process and as potential problems are identified, these can be used as the basis for making model improvements. Finally, we include our previously submitted answers to particular PDC questions (Appendix V). All of our initially proposed objectives have basically been met. In fact, a number of useful applications (VOG, air pollution transport) are already utilizing our experimental output and we believe there are a number of other applications that could make use of our routine forecast/analysis products. Still, work still remains to be done to further develop this experimental weather, climate, fire danger and drought prediction system. In short, we would like to be a part of a future PDC team, if at all possible, to further develop and apply the system for the Hawaiian and other Pacific Islands as well as the entire Pacific Basin.

Roads, John↗

DOE OSTI2025

Adaptive Client Selection in Federated Learning: A Network Anomaly Detection Use Case

Federated Learning (FL) has become a ubiquitous approach for training machine learning models on decentralized data, addressing the myriad privacy concerns inherent in traditional centralized methods. However, the efficiency of FL depends on effective client selection and robust privacy preservation mechanisms. Inadequate client selection may lead to suboptimal model performance, while insufficient privacy measures risk exposing sensitive data. This paper proposes a client selection framework for FL that integrates differential privacy and fault tolerance. Our adaptive approach dynamically adjusts the number of selected clients based on model performance and system constraints, ensuring privacy through calibrated noise addition. We evaluate our method on a network anomaly detection use case using the UNSW-NB15 and ROAD datasets. Results show up to a 7% increase in accuracy and a 25% reduction in training time compared to FedL2P. Moreover, we highlight the trade-offs between privacy budgets and model performance, with higher privacy budgets reducing noise and improving accuracy. Our fault tolerance mechanism, while causing a slight performance drop, enhances robustness to client failures. Statistical validation using Mann-Whitney U tests confirms the significance of these improvements (p < 0.05).

Marfo, William [University of Texas at El Paso,Dep↗

DOE OSTI2025

SPIKANs: separable physics-informed Kolmogorov–Arnold networks

Physics-Informed Neural Networks (PINNs) have emerged as a promising method for solving partial differential equations (PDEs) in scientific computing. While PINNs typically use multilayer perceptrons (MLPs) as their underlying architecture, recent advancements have explored alternative neural network structures. One such innovation is the Kolmogorov–Arnold Network (KAN), which has demonstrated benefits over traditional MLPs, including faster neural scaling and better interpretability. The application of KANs to physics-informed learning has led to the development of Physics-Informed KANs (PIKANs), enabling the use of KANs to solve PDEs. However, despite their advantages, KANs often suffer from slower training speeds, particularly in higher-dimensional problems where the number of collocation points grows exponentially with the dimensionality of the system. To address this challenge, we introduce Separable Physics-Informed Kolmogorov–Arnold Networks (SPIKANs). This novel architecture applies the principle of separation of variables to PIKANs, decomposing the problem such that each dimension is handled by an individual KAN. This approach drastically reduces the computational complexity of training without sacrificing accuracy, facilitating their application to higher-dimensional PDEs. Through a series of benchmark problems, we demonstrate the effectiveness of SPIKANs, showcasing their superior scalability and performance compared to PIKANs and highlighting their potential for solving complex, high-dimensional PDEs in scientific computing.

Kolmogorov-Arnold networks↗

NASA NTRS1981

Technologies for the multispectral mapping of earth resources

The application of solid-state detector array imaging to the remote sensing of the earth as a follow-on to currently planned Landsat missions provides the opportunity to achieve significantly increased performance. First-order advantages to be anticipated are higher sensitivity resulting in greater radiometric accuracies and improved geometric fidelity. The Multispectral Mapper design concept is responsive to a broad range of user needs by incorporating in-flight selection of spectral bands, instantaneous fields of view, and swath width. This versatility is achieved by the use of an imaging spectrometer which permits both spatial and spectral sampling in the image plane using area array detectors. Other improvements over the current Landsat multispectral scanner and Thematic Mapper include higher spatial resolution and inherently precise registration of the spectral bands. The key technologies required in order to realize these improvements include short-wavelength infrared detectors, wide field of view, broad spectral coverage optics, focal plane cooling, and high-speed onboard signal processing. Significant development activities will be required if an advanced remote sensing capability is to be implemented.

Wellman, J. B.↗

DOE OSTI2025

Higher-order factorization machine for accurate surrogate modeling in material design

Efficient and robust optimization is important in material science for identifying optimal structural parameters and enhancing material performance. Surrogate-based active learning algorithms have recently gained great attention for their ability to efficiently navigate large, high-dimensional design spaces. Among surrogate models, 2 nd -order factorization machine (FM) models are widely employed as the surrogate model in active learning algorithms due to their balance between simplicity and effectiveness. However, their quadratic nature limits their capacity to capture complex, higher-order interactions among variables, often leading to suboptimal solutions. To overcome this limitation, we propose an active learning scheme integrating a 3 rd -order FM model, capable of modeling three-variable interactions and more intricate relationships in material systems. We comprehensively evaluate the surrogate modeling performance of the 3 rd -order FM case using various objective functions. Furthermore, we examine the optimization reliability and efficiency of the 3 rd -order FM-based active learning in a real-world material design task (e.g., nanophotonic structures for transparent radiative cooling). Our study shows that the 3 rd -order FM outperforms the 2 nd -order model in both surrogate accuracy and optimization performance, highlighting higher-order models’ promises for material design and optimization problems.

Factorization machine↗

DOE OSTI2023

Reconsidering tympanal-acoustic interactions leads to an improved model of auditory acuity in a parasitoid fly

Although most binaural organisms locate sound sources using neurological structures to amplify the sounds they hear, some animals use mechanically coupled hearing organs instead. One of these animals, the parasitoid fly Ormia ochracea (O. ochracea), has astoundingly accurate sound localization abilities. It can locate objects in the azimuthal plane with a precision of 2°, equal to that of humans, despite an intertympanal distance of only 0.5 mm, which is less than 1/100th of the wavelength of the sound emitted by the crickets that it parasitizes. O. ochracea accomplishes this feat via mechanically coupled tympana that interact with incoming acoustic pressure waves to amplify differences in the signals received at the two ears. In 1995, Miles et al developed a model of hearing mechanics in O. ochracea that represents the tympana as flat, front-facing prosternal membranes, though they lie on a convex surface at an angle from the flies' frontal and transverse planes. The model works well for incoming sound angles less than ±30° but suffers from reduced accuracy (up to 60% error) at higher angles compared to response data acquired from O. ochracea specimens. Despite this limitation, it has been the basis for bio-inspired microphone designs for decades. Here, we present critical improvements to this classic hearing model based on information from three-dimensional reconstructions of O. ochracea's tympanal organ. We identified the orientation of the tympana with respect to a frontal plane and the azimuthal angle segment between the tympana as morphological features essential to the flies' auditory acuity, and hypothesized a differentiated mechanical response to incoming sound on the ipsi- and contralateral sides that depend on these features. We incorporated spatially-varying model coefficients representing this asymmetric response, making a new quasi-two-dimensional (q2D) model. The q2D model has high accuracy (average errors of under 10%) for all incoming sound angles. This improved biomechanical model may inform the design of new microscale directional microphones and other small-scale acoustic sensor systems.

36 MATERIALS SCIENCE↗