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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

MAC/GMC Code Enhanced for Coupled Electromagnetothermoelastic Analysis of Smart Composites

Intelligent materials are those that exhibit coupling between their electromagnetic response and their thermomechanical response. This coupling allows smart materials to react mechanically (e.g., an induced displacement) to applied electrical or magnetic fields (for instance). These materials find many important applications in sensors, actuators, and transducers. Recently interest has arisen in the development of smart composites that are formed via the combination of two or more phases, one or more of which is a smart material. To design with and utilize smart composites, designers need theories that predict the coupled smart behavior of these materials from the electromagnetothermoelastic properties of the individual phases. The micromechanics model known as the generalized method of cells (GMC) has recently been extended to provide this important capability. This coupled electromagnetothermoelastic theory has recently been incorporated within NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC). This software package is user friendly and has many additional features that render it useful as a design and analysis tool for composite materials in general, and with its new capabilities, for smart composites as well.

Bednarcyk, Brett A.↗
NASA NTRS1974

The utility of ERTS-1 data for applications in agriculture and forestry

A comprehensive study has been undertaken to determine the extent to which ERTS-1 data could be used to detect, identify (classify), locate and measure features of applications interest in the disciplines of Agriculture and Forestry. The study areas included: six counties in five states in which were located examples of the most important crops and practices of American agriculture; and a portion of the Sam Houston National Forest, a typical Gulf coastal plain pine forest. The investigation utilized conventional image interpretation and computer-aided (spectral pattern recognition) analysis using both image products and computer compatible tapes. The emphasis was generally upon the computer-aided techniques. It was concluded that ERTS-1 data can be used to detect, identify, locate and measure a wide array of features of interest in agriculture and forestry.

Erb, R. B.↗
NASA NTRS1975

The landing flare: An analysis and flight-test investigation

Results are given of an extensive investigation of conventional landing flares in general aviation type airplanes. A wide range of parameters influencing flare behavior are simulated in experimental landings in a variable-stability Navion. The most important feature of the flare is found to be the airplane's deceleration in the flare. Various effects on this are correlated in terms of the average flare load factor. Piloting technique is extensively discussed. Design criteria are presented.

Seckel, E.↗
NASA NTRS1991

ALDAS user's manual

The Acoustic Laboratory Data Acquisition System (ALDAS) is an inexpensive, transportable means to digitize and analyze data. The system is based on the Macintosh 2 family of computers, with internal analog-to-digital boards providing four channels of simultaneous data acquisition at rates up to 50,000 samples/sec. The ALDAS software package, written for use with rotorcraft acoustics, performs automatic acoustic calibration of channels, data display, two types of cycle averaging, and spectral amplitude analysis. The program can use data obtained from internal analog-to-digital conversion, or discrete external data imported in ASCII format. All aspects of ALDAS can be improved as new hardware becomes available and new features are introduced into the code.

Watts, Michael E.↗
NASA NTRS1988

Development of three-dimensional code for the analysis of jet mixing problem. Part 1: Laminar solution

Future aircraft will eventually feature nonaxisymmetric or rectangular nozzles. Developing a three-dimensional code to stimulate the characteristics of the jet exhaust plume, issuing from nonaxisymmetric nozzles, in general, at different flight conditions, is very important. Two three-dimensional codes were developed to simulate the shock-cell structure of circular nozzles. These codes were developed to solve the parabolized and simplified Navier-Stokes equations respectively. Both codes are based on a method previously developed by Newsome et al. These codes are fully vectorized on the VPS 32 at NASA Langley Research Center. The axisymmetric underexpanded supersonic jet flow problem, exhausting into still air, was used as a test case for developing an efficient three-dimensional problems and preserving crossplane symmetry of the flow downstream of the jet exit.

Abdol-Hamid, Khaled S.↗
NASA NTRS1974

Users guide for information retrieval using APL

A Programming Language (APL) is a precise, concise, and powerful computer programming language. Several features make APL useful to managers and other potential computer users. APL is interactive; therefore, the user can communicate with his program or data base in near real-time. This, coupled with the fact that APL has excellent debugging features, reduces program checkout time to minutes or hours rather than days or months. Of particular importance is the fact that APL can be utilized as a management science tool using such techniques as operations research, statistical analysis, and forecasting. The gap between the scientist and the manager could be narrowed by showing how APL can be used to do what the scientists and the manager each need to do, retrieve information. Sometimes, the information needs to be retrieved rapidly. In this case APL is ideally suited for this challenge.

Shapiro, A.↗
NASA NTRS1983

Shear zone ice deformation using supervised analysis of Seasat data

Spacecraft and aircraft Synthetic-Aperture Radar (SAR) images are commonly used to compute sea ice conditions including especially the drift velocities of ice features. Recent developments, described in this paper, in computer-aided analysis and in digital image processing have extended the analysis speed and accuracy of registration to the point that ice deformation can be examined on the geophysically important scales of about 100 m over tens of kilometers between two 'snapshots.' Examples are shown for the ice motion and rotation in the shear zone near the Alaska coast from Seasat data in 1978.

Carsey, F.↗
NASA NTRS1985

GRM crustal magnetic anomalies: Separating the Lord Howe Rise and Norfolk Ridge submarine structures

Multiple source bodies often lie within the resolution element of the MAGSAT and POGO data. Small weak sources lying near larger stronger sources will tend to be missed, although they do contribute to the total observed anomaly. Lower elevation magnetic anomaly surveys such as GRM alleviate this problem through the combined effects of significantly greater resolution and stronger signal amplitude. This permits the detection of smaller source bodies, and analysis of their structure and nature. The improvement a GRM will provide is demonstrated in the Lord Howe Rise/Norfolk Ridge area east of Australia, between the Tasman Sea and south Fiji Basin. The submarine features origin have important plate tectonic implications. The Lord Howe Rise (LHR) is a continental fragment broken off from Australia by the opening of the Tasman Sea. It is a wide, shallow structure lying between 160 and 165 deg longitude at 23 to 37 deg S latitude. Seismic refraction data show the LHR crust extending to depths in excess of 20 km.

Frey, H.↗
NASA NTRSDate not supplied

Carbon Tracers of Aqueous Processes: Isotopic Analysis of Cr Carbonate Grains With Implications for Bennu Samples

Carbonate grains in carbonaceous chondrites record aqueous alteration events on the asteroidal parent bodies, including evidence for episodic alteration, timing of alteration, and time and temperature evolution of volatiles. Spectral features in the 3.4 μm region at asteroid Bennu have been interpreted as coming from carbonate minerals. Coordinated analysis of carbonate grains will be a valuable tool for analysis of Bennu samples, and related analysis of analog materials provides important context for understanding aqueous alteration of carbonaceous asteroids more broadly. To that end, our team is analyzing carbonates in Bennu analog materials, using Raman spectroscopy to identify carbonates and assess the maturity of related organic materials, vacuum reflectance spectroscopy from the ultraviolet through thermal infrared range to constrain contributions from carbonates and organics, X-ray microtomography and electron probe microanalysis (EPMA) to assess the distribution of void space, transmission electron microscopy to characterize space weathering effects, and EPMA and secondary ion mass spectrometry (SIMS) to measure composition and isotopic ratios. Here, we describe in situ analysis of carbon and oxygen isotopes from carbonates in Grosvenor Mountains (GRO) 95577.

K E Miller↗
DOE OSTI2025

SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles

Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Analyzing the impact of design factors on solar module thermomechanical durability using interpretable machine learning techniques

Solar modules in utility-scale systems are expected to maintain decades of lifetime to rival conventional energy sources. However, cyclic thermomechanical loading often degrades their long-term performance, highlighting the importance of effective design to mitigate thermal expansion mismatches between module materials. Given the complex composition of solar modules, isolating the impact of individual components on overall durability remains a challenging task. In this work, we analyze a comprehensive data set that comprises bill-of-materials (BOM) and thermal cycling power loss from 251 distinct module designs to identify the predominant design factors and their impacts on the thermomechanical durability of modules. The methodology of our analysis combines machine learning modeling (random forest) and Shapley additive explanation (SHAP) to correlate design factors with power loss and interpret the model’s decision-making. The interpretation reveals that silicon type (monocrystalline or polycrystalline), encapsulant thickness, busbar numbers, and wafer thickness predominantly influence the degradation. With lower power loss of around 0.6% on average in the SHAP analysis, monocrystalline cells present better durability than polycrystalline cells. This finding is further substantiated by statistical testing on our raw data set. The SHAP analysis also demonstrates that while thicker encapsulants lead to reduced power loss, further increasing their thickness over around 0.6 to 0.7 mm does not yield additional benefits, particularly for the front side one. In addition, other important BOM features such as the number of busbars are analyzed. This study provides a blueprint for utilizing explainable machine learning techniques in a complex material system and can potentially guide future research on optimizing the design of solar modules.

14 SOLAR ENERGY↗
NASA NTRS1990

Photoclinometric analysis of wrinkle ridges on Lunae Planum, Mars

Wrinkle ridges are common morphologic features on Mars. Both volcanic and tectonic mechanisms were suggested to explain their origin; recent work has focused on a compressional origin. Analysis of terrestrial analogs has greatly influenced and aided the understanding of wrinkle ridge formation. An important aspect necessary to intrepret structure is topography. Topographic profiles across ridges can provide important constraints for models of internal structure and analyzing deformation associated with ridges. Topographic maps of Mars are too coarse to resolve the topography of individual ridges; therefore, monoscopic photoclinometry was used to derive topographic profiles for the ridges. Profiles spaced a few kilometers apart were obtained for each ridge, the number depended on ridge length, morphology, and albedo variation. Photoclinometry relies on pixel brightness variations which results from topography, albedo, or both. Because of the albedo variations, photoclimometric profiles can not be extended across large distances, such as between adjacent ridges (about 20 to 80 km). However, the technique is applicable to shorter distances, such as the distance across typical ridges. Profiles were measured across the ridge and extended a few kilometers on either side, including all visible components of the ridge. The results of these measurements and the use of internal structure and topographic profile models for estimating the shortening due to folding and faulting are discussed.

Plescia, J. B.↗
NASA NTRS1986

Decentralized control experiments on NASA's flexible grid

Methods arising from the area of decentralized control are emerging for analysis and control synthesis for large flexible structures. In this paper the control strategy involves a decentralized model reference adaptive approach using a variable structure control. Local models are formulated based on desired damping and response time in a model-following scheme for various modal configurations. Variable structure controllers are then designed employing co-located angular rate and position feedback. In this scheme local control forces the system to move on a local sliding mode in some local error space. An important feature of this approach is that the local subsystem is made insensitive to dynamical interactions with other subsystems once the sliding surface is reached. Experiments based on the above have been performed for NASA's flexible grid experimental apparatus. The grid is designed to admit appreciable low-frequency structural dynamics, and allows for implementation of distributed computing components, inertial sensors, and actuation devices. A finite-element analysis of the grid provides the model for control system design and simulation; results of several simulations are reported on here, and a discussion of application experiments on the apparatus is presented.

Ozguner, U.↗
DOE OSTI2025

Coupling between collective modes in the deformed 98 Zr nucleus: Insights from consistent HFB + QRPA calculations with the Gogny interaction

The zirconium isotopes exhibit structural properties that present multiple challenges to nuclear theory. Investigations of the coupling present within isoscalar modes and within isovector modes are scarce but important for advancing our understanding of the microscopic picture of nuclei. To explore some of these underlying coupling features, and to test the predictive power of a state-of-the-art nuclear structure approach, we provide a detailed analysis of the properties of 90,96,98 Zr . This region includes a benchmarking case and offers insights into nuclear deformation phenomena. Here, to investigate the coupling between collective modes in deformed nuclei, we focused our analysis on the ground and excited-state properties of these isotopes, employing a consistent approach with the axially symmetric deformed Hartree-Fock-Bogoliubov (HFB) and the quasiparticle random phase approximation (QRPA) framework, both using the Gogny D1M force. This approach effectively describes both low-lying and giant-resonance states. We devoted special attention to the deformed 98 Zr nucleus, where we confirm the existence of coupling between monopole and quadrupole excitations through the 𝐾 𝜋 = 0 + QRPA components and demonstrate an analogous dipole-octupole coupling through the 𝐾 𝜋 = 0 − and 𝐾 𝜋 = 1 − components. Intrinsic transition densities and associated radial projections illustrate the coupling. Our work complements and extends earlier studies carried out using density-functional-based methods and notably, we included the complete Coulomb interaction also in the pairing fields, i.e., we treat terms exactly that are approximated in typical calculations that use the Gogny D1 and D2 interaction families.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Bayesian inference of structured latent spaces from neural population activity with the orthogonal stochastic linear mixing model

The brain produces diverse functions, from perceiving sounds to producing arm reaches, through the collective activity of populations of many neurons. Determining if and how the features of these exogenous variables (e.g., sound frequency, reach angle) are reflected in population neural activity is important for understanding how the brain operates. Often, high-dimensional neural population activity is confined to low-dimensional latent spaces. However, many current methods fail to extract latent spaces that are clearly structured by exogenous variables. This has contributed to a debate about whether or not brains should be thought of as dynamical systems or representational systems. Here, we developed a new latent process Bayesian regression framework, the orthogonal stochastic linear mixing model (OSLMM) which introduces an orthogonality constraint amongst time-varying mixture coefficients, and provide Markov chain Monte Carlo inference procedures. We demonstrate superior performance of OSLMM on latent trajectory recovery in synthetic experiments and show superior computational efficiency and prediction performance on several real-world benchmark data sets. We primarily focus on demonstrating the utility of OSLMM in two neural data sets: μ ECoG recordings from rat auditory cortex during presentation of pure tones and multi-single unit recordings form monkey motor cortex during complex arm reaching. We show that OSLMM achieves superior or comparable predictive accuracy of neural data and decoding of external variables (e.g., reach velocity). Most importantly, in both experimental contexts, we demonstrate that OSLMM latent trajectories directly reflect features of the sounds and reaches, demonstrating that neural dynamics are structured by neural representations. Together, these results demonstrate that OSLMM will be useful for the analysis of diverse, large-scale biological time-series datasets.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1986

Development of a takeoff performance monitoring system

The development and testing of a real-time takeoff performance monitoring system is discussed. The algorithm is madeup of two segments: a pretakeoff segment and a real-time segment. One-time inputs of ambient conditions and airplane configuration information are used in the pretakeoff segment to generate schedule performance data for that takeoff. The real-time segment uses the scheduled performance data generated in the pretakeoff segment, runway length data, and measured parameters to monitor the performance of the airplane throughout the takeoff roll. Airplane and engine performance deficiencies are detected and annunciated. An important feature of this algorithm is the one-time estimation of the runway rolling friction coefficient. The algorithm was tested using a six degree of freedom airplane model in a computer simulation. Results from a series of sensitivity analysis are also included.

Srivatsan, R.↗
NASA NTRS1987

Development of a takeoff performance monitoring system

The development and testing of a real-time takeoff performance monitoring system is discussed. The algorithm is made up of two segments: a pretakeoff segment and a real-time segment. One-time inputs of ambient conditions and airplane configuration information are used in the pretakeoff segment to generate schedule performance data for that takeoff. The real-time segment uses the scheduled performance data generated in the pretakeoff segment, runway length data, and measured parameters to monitor the performance of the airplane throughout the takeoff roll. Airplane and engine performance deficiencies are detected and annunciated. An important feature of this algorithm is the one-time estimation of the runway rolling friction coefficient. The algorithm was tested using a six degree of freedom airplane model in a computer simulation. Results from a series of sensitivity analysis are also included.

Srivatsan, R.↗
NASA NTRS1988

Hierarchical neural networks for autonomous data analysis and decision making

A neural network based data analysis and decision making system to increase the autonomy of a planetary rover or similar exploratory vehicle is presented. A hierarchical series of neural networks for real time analysis of scientific images is used. The system under development emphasizes analysis of multispectral images by classifier and feature detector neural networks, to provide information on the mineral composition of a scene. A hierarchy of alternating analysis and decision making networks is being developed to allow increasingly fine scale analysis in regions of the image that are potentially important. It is noted that this system will facilitate both the selection of high priorty scientific information for transmission to earth, and the autonomous collection of rocks and soil for sample return.

Eberlein, Susan↗