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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Nearest Neighbor Algorithms for Pattern Classification

A solution of the discrimination problem is considered by means of the minimum distance classifier, commonly referred to as the nearest neighbor (NN) rule. The NN rule is nonparametric, or distribution free, in the sense that it does not depend on any assumptions about the underlying statistics for its application. The k-NN rule is a procedure that assigns an observation vector z to a category F if most of the k nearby observations x sub i are elements of F. The condensed nearest neighbor (CNN) rule may be used to reduce the size of the training set required categorize The Bayes risk serves merely as a reference-the limit of excellence beyond which it is not possible to go. The NN rule is bounded below by the Bayes risk and above by twice the Bayes risk.

Barrios, J. O.↗
NASA NTRS1980

Remote sensing of ozone in the middle ultraviolet

Earlier studies of the remote sensing of the ozone distribution from satellites in the middle ultraviolet are extended, giving particular attention to the analytic model method. After a brief introduction, the historical background of this subject is presented. This is followed by a summary and review of early work based upon the analytic model. Then a linearized approach to the problem and a linearized equation for a density correction are discussed. These indicate some of the general limitations of the inversion method. Finally the parametrized model approach is reexamined by using both simulated data and some actual satellite data.

Green, A. E. S.↗
NASA NTRS1983

A Framework for Wetlands Research: Development of a Wetlands Data Base

Issues related to the assembly of a comprehensive global wetlands data base are presented. A strategy to collect relevant data for wetland ecosystems through remote sensing inventories of wetland distribution was discussed. Elements of a research program on biogenic gas fluxes were identified. The major wetland parameters and their functional importance to material exchange mechanisms are summarized.

Source record↗
NASA NTRS1984

Estimation of agronomic variables using spectral signatures

Techniques for the determination of leaf area index or leaf angle distribution from remote-sensing canopy-reflectance (CR) measurements are developed on the basis of empirical models relating CR to parameters such as soil and vegetation spectral properties, solar flux, and viewing angle. A general procedure for inverting CR models is presented and applied to the models of Suits (1972), Verhoef and Bunnik (1981), and Norman (1979) in the IR range. Numerical results for a soybean canopy are compared in a table, and the error sensitivity of the inverted models is shown to be relatively high, requiring the use of ancillary data such as soil reflectance, leaf reflectance, and leaf transmittance.

Goel, N. S.↗
NASA NTRS1988

A methodology for mapping forest latent heat flux densities using remote sensing

Surface temperatures and reflectances of an upper elevation Sierran mixed conifer forest were monitored using the Thematic Mapper Simulator sensor during the summer of 1985 in order to explore the possibility of using remote sensing to determine the distribution of solar energy on forested watersheds. The results show that the method is capable of quantifying the relative energy allocation relationships between the two cover types defined in the study. It is noted that the method also has the potential to map forest latent heat flux densities.

Pierce, Lars L.↗
NASA NTRS1994

The Global Emergency Observation and Warning System

Based on an extensive characterization of natural hazards, and an evaluation of their impacts on humanity, a set of functional technical requirements for a global warning and relief system was developed. Since no technological breakthroughs are required to implement a global system capable of performing the functions required to provide sufficient information for prevention, preparedness, warning, and relief from natural disaster effects, a system is proposed which would combine the elements of remote sensing, data processing, information distribution, and communications support on a global scale for disaster mitigation.

Bukley, Angelia P.↗
NASA NTRS1996

Optimum Transonic Airfoils Based on the Euler Equations

We solve the problem of determining airfoils that approximate, in a least square sense, given surface pressure distributions in transonic flight regimes. The flow is modeled by means of the Euler equations and the solution procedure is an adjoint- based minimization algorithm that makes use of the inverse Theodorsen transform in order to parameterize the airfoil. Fast convergence to the optimal solution is obtained by means of the pseudo-time method. Results are obtained using three different pressure distributions for several free stream conditions. The airfoils obtained have given a trailing edge angle.

Iollo, Angelo↗
NASA NTRS2005

Structural Anomaly Detection Using Fiber Optic Sensors and Inverse Finite Element Method

NASA Langley Research Center is investigating a variety of techniques for mitigating aircraft accidents due to structural component failure. One technique under consideration combines distributed fiber optic strain sensing with an inverse finite element method for detecting and characterizing structural anomalies anomalies that may provide early indication of airframe structure degradation. The technique identifies structural anomalies that result in observable changes in localized strain but do not impact the overall surface shape. Surface shape information is provided by an Inverse Finite Element Method that computes full-field displacements and internal loads using strain data from in-situ fiberoptic sensors. This paper describes a prototype of such a system and reports results from a series of laboratory tests conducted on a test coupon subjected to increasing levels of damage.

Quach, Cuong C.↗
NASA NTRS2009

Robotic Recon for Human Exploration

Robotic reconnaissance has the potential to significantly improve scientific and technical return from lunar surface exploration. In particular, robotic recon may increase crew productivity and reduce operational risk for exploration. However, additional research, development and field-testing is needed to mature robot and ground control systems, refine operational protocols, and specify detailed requirements. When the new lunar surface campaign begins around 2020, and before permanent outposts are established, humans will initially be on the Moon less than 10% of the time. During the 90% of time between crew visits, robots will be available to perform surface operations under ground control. Understanding how robotic systems can best address surface science needs, therefore, becomes a central issue Prior to surface missions, lunar orbiters (LRO, Kaguya, Chandrayyan-1, etc.) will map the Moon. These orbital missions will provide numerous types of maps: visible photography, topographic, mineralogical and geochemical distributions, etc. However, remote sensing data will not be of sufficient resolution, lighting, nor view angle, to fully optimize pre-human exploration planning, e.g., crew traverses for field geology and geophysics. Thus, it is important to acquire supplemental and complementary surface data. Robotic recon can obtain such data, using robot-mounted instruments to scout the surface and subsurface at resolutions and at viewpoints not achievable from orbit. This data can then be used to select locations for detailed field activity and prioritize targets to improve crew productivity. Surface data can also help identify and assess terrain hazards, and evaluate alternate routes to reduce operational risk. Robotic recon could be done months in advance, or be part of a continuing planning process during human missions.

Deans, Matthew↗
NASA NTRS2011

Deformed Shape Calculation of a Full-Scale Wing Using Fiber Optic Strain Data from a Ground Loads Test

A ground loads test of a full-scale wing (175-ft span) was conducted using a fiber optic strain-sensing system to obtain distributed surface strain data. These data were input into previously developed deformed shape equations to calculate the wing s bending and twist deformation. A photogrammetry system measured actual shape deformation. The wing deflections reached 100 percent of the positive design limit load (equivalent to 3 g) and 97 percent of the negative design limit load (equivalent to -1 g). The calculated wing bending results were in excellent agreement with the actual bending; tip deflections were within +/- 2.7 in. (out of 155-in. max deflection) for 91 percent of the load steps. Experimental testing revealed valuable opportunities for improving the deformed shape equations robustness to real world (not perfect) strain data, which previous analytical testing did not detect. These improvements, which include filtering methods developed in this work, minimize errors due to numerical anomalies discovered in the remaining 9 percent of the load steps. As a result, all load steps attained +/- 2.7 in. accuracy. Wing twist results were very sensitive to errors in bending and require further development. A sensitivity analysis and recommendations for fiber implementation practices, along with, effective filtering methods are included

Jutte, Christine V.↗
NASA NTRS2019

Complex Dynamics of Air Traffic Flow

Air traffic in the United States has continued to grow at a steady pace since 1980, except for a dip immediately after the tragic events of September 11, 2001. There are different growth scenarios associated both with the magnitude and the composition of the future air traffic. The Terminal Area Forecast (TAF), prepared every year by the FAA, projects the growth of traffic in the United States. Both Boeing and Airbus publish market outlooks for air travel annually. Although predicting the future growth of traffic is difficult, there are two significant trends: heavily congested major airports continue to see an increase in traffic, and the emergence of regional jets and other smaller aircraft with fewer passengers operating directly between non-major airports. The interaction between air traffic demand and the ability of the system to provide the necessary airport and airspace resources can be modeled as a network. The size of the resulting network varies depending on the choice of its nodes. It would be useful to understand the properties of this network to guide future design and development. Many questions, such as the growth of delay with increasing traffic demand and impact of the en route weather on future air traffic, require a systematic understanding of the properties of the air traffic network. There has been a major advance in the understanding of the behavior of networks with a large number of components. Several theories have been advanced about the evolution of large biological and engineering networks by authors in diversified disciplines like physics, mathematics, biology and computer science. Several networks exhibit a scale-free property in the sense that the probabilistic distribution of their nodes as a function of connections decreases slower than an exponential. These networks are characterized by the fact that a small number of components have a disproportionate influence on the performance of the network. Scale-free networks are tolerant to random failure of components, but are vulnerable to selective attack on components. This paper examines two network representations for the baseline air traffic system. A network defined with the 40 major airports as nodes and with standard flight routes as links has a characteristic scale: all nodes have 60 or more links and no node has more than 460 links. Another network is defined with baseline aircraft routing structure exhibits an exponentially truncated scale-free behavior. Its degree ranges from 2 connections to 2900 connections, and 225 nodes have more than 250 connections. Furthermore, those high-degree nodes are homogeneously distributed in the airspace. A consequence of this scale-free behavior is that the random loss of a single node has little impact, but the loss of multiple high-degree nodes (such as occurs during major storms in busy airspace) can adversely impact the system. Two future scenarios of air traffic growth are used to predict the growth of air traffic in the United States. It is shown that a three-times growth in the overall traffic may result in a ten-times impact on the density of traffic in certain parts of the United States.

Scale-free Networks↗
NASA NTRS2022

Estimating pixel-level uncertainty in ocean color retrievals from MODIS

The spectral distribution of marine remote sensing reflectance, R(rs), is the fundamental measurement of ocean color science, from which a host of bio-optical and biogeochemical properties of the water column can be derived. Estimation of uncertainty in these derived properties is thus dependent on knowledge of the uncertainty in satellite-retrieved R(rs) (u(c)(R(rs))) at each pixel. Uncertainty in R(rs), in turn, is dependent on the propagation of various uncertainty sources through the R(rs) retrieval process, namely the atmospheric correction (AC). A derivative-based method for uncertainty propagation is established here to calculate the pixel-level uncertainty in R(rs), as retrieved using NASA’s multiple-scattering epsilon (MSEPS) AC algorithm and verified using Monte Carlo (MC) analysis. The approach is then applied to measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, with uncertainty sources including instrument random noise, instrument systematic uncertainty, and forward model uncertainty. The uc(Rrs) is verified by comparison with statistical analysis of coincident retrievals from MODIS and in situ Rrs measurements, and our approach performs well in most cases. Based on analysis of an example 8-day global products, we also show that relative uncertainty in R(rs) at blue bands has a similar spatial pattern to the derived concentration of the phytoplankton pigment chlorophyll-a (chl-a), and around 7.3%, 17.0%, and 35.2% of all clear water pixels (chl-a ≤ 0.1 mg/cu.m) with valid u(c)(R(rs)) have a relative uncertainty ≤ 5% at bands 412 nm, 443 nm, and 488 nm respectively, which is a common goal of ocean color retrievals for clear waters. While the analysis shows that u(c)(R(rs)) calculated from our derivative-based method is reasonable, some issues need further investigation, including improved knowledge of forward model uncertainty and systematic uncertainty in instrument calibration.

Pixel-level uncertainty↗
NASA NTRS1974

A review of initial investigations to utilize ERTS-1 data in determining the availability and distribution of living marine resources

The National Marine Fisheries Service has been studying the application of aerospace remote sensing to fisheries management and utilization for many years. The 15-month ERTS study began in July 1972 to: (1) determine the reliability of satellite and high altitude sensors to provide oceanographic parameters in coastal waters; (2) demonstrate the use of remotely-sensed oceanographic information to predict the distribution and abundance of adult menhaden; and (3) demonstrate the potential use of satellites for acquiring information for improving the harvest and management of fisheries resources. The study focused on a coastal area in the north-central portion of the Gulf of Mexico, including parts of Alabama, Mississippi, and Louisiana. The test area used in the final analysis was the Mississippi Sound and the area outside the barrier islands to approximately the 18-meter (10-fathom) curve.

Stevenson, W. H.↗
NASA NTRS1980

Field size, length, and width distributions based on LACIE ground truth data

The development of agricultural remote sensing systems requires knowledge of agricultural field size distributions so that the sensors, sampling frames, image interpretation schemes, registration systems, and classification systems can be properly designed. Malila et al. (1976) studied the field size distribution for wheat and all other crops in two Kansas LACIE (Large Area Crop Inventory Experiment) intensive test sites using ground observations of the crops and measurements of their field areas based on current year rectified aerial photomaps. The field area and size distributions reported in the present investigation are derived from a representative subset of a stratified random sample of LACIE sample segments. In contrast to previous work, the obtained results indicate that most field-size distributions are not log-normally distributed. The most common field size observed in this study was 10 acres for most crops studied.

Pitts, D. E.↗
NASA NTRS2004

Progress of Multicolor Single Detector to Detector Array Development for Remote Sensing

Knowledge of the spatial and temporal distribution of atmospheric species such as CO2, O3, H2O, and CH4 is important for understanding the chemistry and physical cycles involving Earth s atmosphere. Although several remote sensing techniques are suitable for such measurements they are considered high cost techniques involving complicated instrumentation. Therefore, simultaneous measurement of atmospheric species using a single remote sensing instrument is significant for minimizing cost, size and complexity. While maintaining the instrument sensitivity and range, quality of multicolor detector, in terms of high quantum efficiency and low noise are vital for these missions. As the first step for developing multicolor focal plan array, the structure of a single element multicolor detector is presented in this paper. The detector consists of three p-n junction layers of Si, GaSb and InAs wafer bonded to cover the spectral range UV to 900 nm, 800 nm to 1.7 m, and 1.5 m to 3.4 m, respectively. Modeling of the absorption coefficient for each material was carried out for optimizing the layers thicknesses for maximum absorption. The resulted quantum efficiency of each layer has been determined except InAs layer. The optical and electrical characterization of each layer structure is reported including dark current and spectral response measurements of Si pin structure and of GaSb and InAs p-n junctions. The effect of the material processing is discussed.

Abedin, M. Nurul↗
NASA NTRS2023

Single-Scattering Properties of Ellipsoidal Dust Aerosols Constrained By Measured Dust Shape Distributions

Most global aerosol models approximate dust as spherical particles, whereas most remote sensing retrieval algorithms approximate dust as spheroidal particles with a shape distribution that conflicts with measurements. These inconsistent and inaccurate shape assumptions generate biases in dust single-scattering properties. Here, we obtain dust single-scattering properties by approximating dust as triaxial ellipsoidal particles with observationally constrained shape distributions. We find that, relative to the ellipsoidal dust optics obtained here, the spherical dust optics used in most aerosol models underestimate dust single-scattering albedo, mass extinction efficiency, and asymmetry parameter for almost all dust sizes in both the shortwave and longwave spectra. We further find that the ellipsoidal dust optics are in substantially better agreement with observations of the scattering matrix and linear depolarization ratio than the spheroidal dust optics used in most retrieval algorithms. However, relative to observations, the ellipsoidal dust optics overestimate the lidar ratio by underestimating the backscattering intensity by a factor of ∼2. This occurs largely because the computational method used to simulate ellipsoidal dust optics (i.e., the improved geometric optics method) underestimates the backscattering intensity by a factor of ∼2 relative to other computational methods (e.g., the physical geometric optics method). We conclude that the ellipsoidal dust optics with observationally constrained shape distributions can help improve global aerosol models and possibly remote sensing retrieval algorithms that do not use the backscattering signal.

Dust↗
NASA NTRS2019

Evaluation of Wing Load Calibration and Sensing Methods Using Conventional Strain Gages and a Fiber Optic Sensing System Installed on a Straight Tapered Wing

State-of-the-art instrumentation techniques have provided an opportunity to obtain greater insight into structural wing loads during flight. An investigation was undertaken to research new wing instrumentation and load sensing techniques for measuring accurate in-flight spanwise load distributions on wing structures. A straight tapered wing was instrumented with both conventional foil strain gages at five spanwise wing stations and fiber optic strain sensors at every half inch along the entire wing span. Thirty-nine unique load cases were applied to the wing lower surface using hydraulic actuators to obtain various shear, bending moment, and torque load distributions on the wing. This paper will highlight three load calibration approaches. Conventional linear regression calibration methods were applied to foil strain gages providing a single wing station vertical shear, bending moment, and torque load. Linear regression methods were applied to a fiber optic sensing system to provide bending moment and torque spanwise load distributions. A load sensing scheme using strain derived wing shape information derived from a single load case provided vertical shear and bending moment spanwise load distribution information. Aspects of the three different approaches will be compared and contrasted to inform the reader of the benefits or disadvantages of each. Instrument installation, sensor characteristics, test execution aspects, and recommended calibration techniques will be discussed.

structural mechanics↗
DOE OSTI2026

Study on Application of Distributed Network of Sensors with List Mode for NMAC Literature Review

Nuclear material accounting and control (NMAC) for nuclear security detects, deters, and resolves questions related to unauthorized removal (i.e. theft) or misuse of nuclear material. NMAC also serves as a key insider threat mitigation measure and aids in recovery of nuclear material that is missing. Effective nuclear security depends on NMAC for timely and accurate information about nuclear material types, quantities, and locations. Bulk nuclear material processing facilities, however, present unique challenges for effective NMAC due to the presence of large quantities of material in-process and the accumulation of residual material holdup within process equipment. These holdup accumulations can obscure accurate physical inventory taking and complicate efforts to resolve NMAC irregularities at the facility level. Bulk material monitoring systems often rely on material balance calculations and indirect measurement techniques, which may mask protracted theft of smaller amounts of nuclear material. These monitoring limitations have generated increased interest in continuous monitoring technologies, including distributed non-destructive assay (NDA) sensor networks capable of providing real-time or near-real-time measurement of material movement and accumulation within bulk processing environments. Recent advancements in distributed networks of NDA radiation detectors and sensing technologies provide an opportunity to address these limitations. Although such distributed sensor networks have been implemented in select facilities for IAEA Safeguards applications, their potential for supporting NMAC functions specifically tailored to nuclear security objectives remains largely unexplored. Furthermore, emerging list-mode data acquisition technologies have reached high technology readiness levels, enabling time-correlated detection of nuclear events across multiple temporal scales. These capabilities provide enhanced opportunities for accurate holdup measurement, continuous process monitoring, and improved detection of material theft or misuse over time. The increasing global expansion of civil nuclear power and development of related bulk material processing facilities, including those supporting high-assay low-enriched uranium (HALEU) and other advanced reactor fuel fabrication, further increases the need for advanced measurement and monitoring strategies for NMAC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗