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NASA NTRS1991

Automated multisensor registration - Requirements and techniques

The synergistic utilization of data from a suite of remote sensors requires multi-dimensional analysis of the data. Prior to this analysis, processing is required to correct for the systematic geometric distortions characteristic of each sensor, followed by a registration operation to remove any residual offsets. Furthermore, to handle a large volume of data and high data rates, the registration process must be fully automated. A conceptual approach is presented that integrates a variety of registration techniques and selects the candidate algorithm based on certain performance criteria. The performance requirements for an operational algorithm are formulated given the spatially, temporally, and spectrally varying factors that influence the image characteristics and the science requirements of various applications. Several computational techniques are tested and their performance evaluated using a multisensor test data set assembled from the Landsat TM, Seasat, SIR-B, TIMS, and SPOT sensors. The results are discussed and recommendations for future studies are given.

Rignot, Eric J. M.↗

NASA NTRS1945

Data for Design of Entrance Vanes from Two-Dimensional Tests of Airfoils in Cascade

As a part of a program of the NACA directed toward increasing the efficiency of compressors and turbines, data were obtained for application to the design of entrance vanes for axfax-flow compressors or turbines. A series of blower-blade sections with relatively high critical speeds have been developed for turning air efficiently from 0 deg to 80 deg starting with an axial direction. Tests were made of five NACA 65-series blower blades (modified NACA 65(216)-010 airfoils) and of four experimentally designed blower blades in a stationary cascade at low Mach numbers. The turning effectiveness and the pressure distributions of these blade sections at various angles of attack were evaluated over a range of solidities near 1. Entrance-vane design charts are presented that give a blade section and angle of attack for any desired turning angle. The blades thus obtained operate with peak-free pressure distributions. Approximate critical Mach numbers were calculated from the pressure distributions.

FLOW-VANES, GUIDE↗

NASA NTRS1994

LSENS: A General Chemical Kinetics and Sensitivity Analysis Code for homogeneous gas-phase reactions. Part 3: Illustrative test problems

LSENS, the Lewis General Chemical Kinetics and Sensitivity Analysis Code, has been developed for solving complex, homogeneous, gas-phase chemical kinetics problems and contains sensitivity analysis for a variety of problems, including nonisothermal situations. This report is part 3 of a series of three reference publications that describe LSENS, provide a detailed guide to its usage, and present many example problems. Part 3 explains the kinetics and kinetics-plus-sensitivity analysis problems supplied with LSENS and presents sample results. These problems illustrate the various capabilities of, and reaction models that can be solved by, the code and may provide a convenient starting point for the user to construct the problem data file required to execute LSENS. LSENS is a flexible, convenient, accurate, and efficient solver for chemical reaction problems such as static system; steady, one-dimensional, inviscid flow; reaction behind incident shock wave, including boundary layer correction; and perfectly stirred (highly backmixed) reactor. In addition, the chemical equilibrium state can be computed for the following assigned states: temperature and pressure, enthalpy and pressure, temperature and volume, and internal energy and volume. For static problems the code computes the sensitivity coefficients of the dependent variables and their temporal derivatives with respect to the initial values of the dependent variables and/or the three rate coefficient parameters of the chemical reactions.

Bittker, David A.↗

NASA NTRS2003

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/~ge/gedihome.html Supplementary information: http://www.chip.org/~ge/gedihome.html.

Database Management Systems↗

NASA NTRS2024

Artificial Intelligence Medical Support for Long-Duration Space Missions

We envision an artificial intelligence (AI) based system that will provide support and recommendations to the crew medical officer (CMO) and ground flight surgeon during long-duration space missions. Such a system would be pretrained on the knowledgebase of clinical knowledge on Earth, minimizing the amount of Earth data that needs to be transferred into space. Then during deployment, the system would be constantly refined through active learning from diverse streams of data from sensors in the spacecraft, data collected daily from individual astronauts, and human-in-the-loop feedback from the crew. The model could be interrogated for predictions and recommendations on personalized crew health based on the overall status of the spacecraft, medicinal stores, and status of other crew members. Adaptation techniques would be used to incorporate spaceflight data that have very different distributions from the training data due to the extreme environment. Edge computing and the most advanced neuromorphic processing would enable computation in scenarios with low power and bandwidth, while dimensionality reduction would be employed to ensure that the input data streams from spaceflight are as small as possible. In order to realize this long-term vision, several hardware and software aspects need to be developed and assembled. First, models pretrained on Earth biomedical data would need to be evaluated for predictive accuracy, and the best one selected. That model would need to be adapted to learn from diverse, sparse, and inconsistently measured data streams, as well as human-in-the-loop feedback. A data integration, standardization, and dimensionality reduction methodology would need to be developed to handle all data types and feed them into the model. Once the software and data infrastructure is developed, it would need to be integrated with small footprint compute processors and tested in high-radiation, high-vibration, unregulated temperature situations. As a short-term goal, we recommend to focus on the development of the data and model software structure. Several large language models (LLM) already exist that have been trained on Earth biomedical and clinical knowledgebases, including BioMedLLM, Med-PaLM, SPOKE LLM, and Foresight. These models need to be evaluated for accuracy and the best one chosen for a proof-of-concept structure, while maintaining awareness of the accelerating AI field and incorporating any newly improved model architectures as needed. Then, we recommend to develop a database of synthetic data types to mimic the diverse data streams that are expected in a long-duration space mission. This should include environmental and microbial data from the spacecraft, non-invasive data from wearables and point-of-care devices employed by astronauts, and more invasive molecular and physiological monitoring of clinical and biomarker data from astronauts. The data standardization methodology should be developed, and these data streams used to refine the clinical LLM. Several scenarios should be developed that could plausibly come up in a long-duration space mission, and changes or aberrations introduced to the data at specific times to mimic these scenarios. Then, question and answer tasks should be designed to interrogate the model for predictions and recommendations, with acceptable answers already identified.

Artificial Intelligence↗

NASA NTRS2005

Northern Hemisphere Gullies on Mars: Analysis of Spacecraft Data and Implications for Formation Mechanisms

The origin of geologically recent gullies on Mars has remained controversial since the discovery of these features by Malin and Edgett in 2000. Numerous models have been proposed which invoke various physical processes as well as various agents of erosion to explain the origin of the Martian gullies. Hypotheses to explain the formation of the gullies invoke shallow liquid water aquifers, deep liquid water aquifers, melting ground ice, snowmelt, dry landslides, and carbon dioxide aquifers. We test the validity of such gully formation mechanisms by analyzing data from the Mars Global Surveyor and Mars Odyssey spacecrafts to uncover trends in the dimensional and physical properties of the gullies and their surrounding terrain. A similar study has previously been completed for gullies located in the southern hemisphere of Mars. The work presented here focuses exclusively on gullies in the northern hemisphere based on the identification of 136 Mars Orbiter Camera (MOC) images containing clear evidence of gully landforms, distributed in the northern mid and high latitudes. These sites have been analyzed in combination with Mars Orbiter Laser Altimeter (MOLA), Thermal Emission Spectrometer (TES), and Gamma Ray Spectrometer (GRS) data to provide quantitative measurements of numerous gully characteristics. Parameters measured include apparent source depth and distribution, vertical and horizontal dimensions, slopes, compass orientations, near-surface ice content, and factors controlling present-day climatic conditions.

Heldmann, J. L.↗

NASA NTRSDate not supplied

FUN3D Analyses in Support of the 1st AIAA Stability and Control Prediction Workshop

The 1st AIAA Stability and Control Prediction Workshop was created to establish best practices for the prediction of stability & control derivatives using computational fluid dynamics and assess the limitations of these computational methods when those best practices are applied. The inaugural workshop considers the ONERA version of the NASA/Boeing Common Research Model(CRM), which includes the wing, body, horizontal tail, and a vertical tail designed by ONERA. Wind tunnel tests have been conducted for this configuration with longitudinal tests having been previously published, in addition to unpublished data at small sideslip angles that will serve as ‘blind’ data for workshop data comparisons. Participants were provided a ‘family’ of unstructured grids for the full-span ONERA CRM model with the wind-tunnel sting included. This family of mixed-element grids consists of 5 levels of refinement (tiny, coarse, medium, fine, and extra fine) with surface and volume mesh scaling, resulting in a size range of 14.6 to 53.4 million nodes. In addition, a medium refinement mesh has been provided for the ONERA CRM configuration without a sting to evaluate the sting’s impact on static longitudinal stability characteristics. In addition to these workshop-provided grids, the present work also considers an equivalent ‘family’ of computational grids generated using Heldenmesh™, a rapid grid generation software by Helden Aerospace Corporation for creating high-quality, three-dimensional, mixed-element unstructured meshes. Because of the authors’ familiarity with this software, these additional grids were generated as a comparison to the workshop-provided grids and to better understand the implications of using volume-mirrored grids for stability and control predictions. The present work will contribute to the workshop with test case data generated using the NASA FUN3D code, a parallelized, unstructured, node-based, finite-volume discretization, Reynolds-averaged Navier-Stokes flow solver. Numerical simulations will be conducted using the Quadratic Constitutive Relationship (QCR) version of the Spalart-Allmaras (SA) turbulence model with negative turbulence variable provisions. Both steady and2nd-order, time-accurate simulation results are to be generated and compared for select test cases, as time permits, to investigate their impact on FUN3D predictions. The present work will consider the three primary workshop test cases: (1) grid convergence study, (2) Mach number effect on static stability, and (3) wind tunnel sting increments. Additionally, data will be provided for the two optional test cases, which include:(1) static stability derivative calculations and (2)sideslip angle sweeps. In each of the test cases, the vehicle is stationary, and the body is assumed to be rigid, where vehicle deformation has been accounted for in the model configuration geometry. For all test cases, longitudinal and lateral force and moment aerodynamic coefficients will be provided for the total configuration, in addition to a component-level breakdown that includes the port wing, starboard wing, fuselage, and tail.

CFD↗

NASA NTRS1995

Three-dimensional aerodynamic analysis of a subsonic transport high-lift configuration and comparisons with wind-tunnel test results

The sizing and efficiency of an aircraft is largely determined by the performance of its high-lift system. Subsonic civil transports most often use deployable multi-element airfoils to achieve the maximum-lift requirements for landing, as well as the high lift-to-drag ratios for take-off. However, these systems produce very complex flow fields which are not fully understood by the scientific community. In order to compete in today's market place, aircraft manufacturers will have to design better high-lift systems. Therefore, a more thorough understanding of the flows associated with these systems is desired. Flight and wind-tunnel experiments have been conducted on NASA Langley's B737-100 research aircraft to obtain detailed full-scale flow measurements on a multi-element high-lift system at various flight conditions. As part of this effort, computational aerodynamic tools are being used to provide preliminary flow-field information for instrumentation development, and to provide additional insight during the data analysis and interpretation process. The purpose of this paper is to demonstrate the ability and usefulness of a three-dimensional low-order potential flow solver, PMARC, by comparing computational results with data obtained from 1/8 scale wind-tunnel tests. Overall, correlation of experimental and computational data reveals that the panel method is able to predict reasonably well the pressures of the aircraft's multi-element wing at several spanwise stations. PMARC's versatility and usefulness is also demonstrated by accurately predicting inviscid three-dimensional flow features for several intricate geometrical regions.

Edge, D. Christian↗

NASA NTRSDate not supplied

Flow field Reconstruction for Inhomogeneous Turbulence using Data and Physics Driven Models

A methodology combining Large Eddy Simulation (LES) trained data and a physics driven wave packet model to obtain a reduced order reconstruction for broadband, three-dimensional, temporally stationary but spatially inhomogeneous, incompressible turbulence. Wake turbulence generated by an axisymmetric dragging disk with a turbulent co-flow serves as the benchmark test case. We begin by studying the proper-orthogonal decomposition of the turbulent fluctuations taken from a high-resolution LES to first identify whether the fields demonstrate a low-rank character. It is argued that the presence of the turbulent co-flow results in a largely broadband character lacking any tonal properties. This is especially true for Strouhal numbers greater than 1 and only a small fraction of energy is contained in the leading order Kelvin-Helmholtz modes. As such reconstructions and reduced order modeling purely relying on data from LES does not appear to be a lucrative solution - contrary to problems with strongly tonal character. To supplement the missing energy from a low order truncated mode expansion, we utilize a physics based super-resolution (enrichment) algorithm that relies on spatio-temporally localized Gabor wave packets whose time evolution is described using a set of ordinary differential equations. The reconstructed flow has single- and two-point correlations that are consistent with the reference high resolution simulation data.

SLS↗

NASA NTRS1983

Experimental study of the separating confluent boundary-layer. Volume 2: Experimental data

An experimental low speed study of the separating confluent boundary layer on a NASA GAW-1 high lift airfoil is described. The airfoil was tested in a variety of high lift configurations comprised of leading edge slat and trailing edge flap combinations. The primary test instrumentation was a two dimensional laser velocimeter (LV) system operating in a backscatter mode. Surface pressures and corresponding LV derived boundary layer profiles are given in terms of velocity components, turbulence intensities and Reynolds shear stresses as characterizing confluent boundary layer behavior up to and beyond stall. LV derived profiles and associated boundary layer parameters and those obtained from more conventional instrumentation such as pitot static transverse, Preston tube measurements and hot-wire surveys are compared.

Braden, J. A.↗

NASA NTRSDate not supplied

Cloud-Precipitation Hybrid Regimes and their Projection onto IMERG Precipitation Data

We extend and enhance the concept of the Cloud Regimes (CRs) developed from two-dimensional joint histograms of cloud optical thickness and cloud top pressure from the Moderate Resolution Imaging Spectroradiometer (MODIS), by adding precipitation information in order to better understand cloud-precipitation relationships. Taking advantage of the high-resolution Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation dataset, cloud-precipitation “hybrid” regimes are derived by implementing the k-means clustering algorithm with advanced initialization and objective measures to determine the most optimal clusters. By expressing precipitation rates within 1-degree grid cell as histograms and making choices on the relative weight of cloud and precipitation, we could obtain several editions of hybrid cloud-precipitation regimes (CPRs), and examine their characteristics. In the deep tropics, when precipitation is weighted weakly, the cloud part of the hybrid entroids resembles the centroid of cloud-only regimes, but still tightens the cloud-precipitation relationship by decreasing the precipitation variability of each regime. As precipitation weight progressively increases, the shape of the cloudy part of the hybrid centroids becomes blunter, while the precipitation part of the centroids sharpens. In the case where cloud and precipitation are weighted equally, the CPRs representing high clouds with intermediate to heavy precipitation exhibit distinct features in the precipitation parts of the centroids, which allows us to project them onto the 30-minly IMERG domain. Such a projection can be used to overcome the temporal sparseness of MODIS cloud observations, which leads to great application potential for various convection-focused studies, including diurnal cycle analysis.

cloud-precipitation↗

DOE OSTI2025

Autonomous platform for solution processing of electronic polymers

The manipulation of electronic polymers’ solid-state properties through processing is crucial in electronics and energy research. Yet, efficiently processing electronic polymer solutions into thin films with specific properties remains a formidable challenge. We introduce Polybot, an artificial intelligence (AI) driven automated material laboratory designed to autonomously explore processing pathways for achieving high-conductivity, low-defect electronic polymers films. Leveraging importance-guided Bayesian optimization, Polybot efficiently navigates a complex 7-dimensional processing space. In particular, the automated workflow and algorithms effectively explore the search space, mitigate biases, employ statistical methods to ensure data repeatability, and concurrently optimize multiple objectives with precision. The experimental campaign yields scale-up fabrication recipes, producing transparent conductive thin films with averaged conductivity exceeding 4500 S/cm. Feature importance analysis and morphological characterizations reveal key design factors. This work signifies a significant step towards transforming the manufacturing of electronic polymers, highlighting the potential of AI-driven automation in material science.

Wang, Chengshi [Argonne National Laboratory (ANL),↗

NASA NTRS1973

Three-dimensional hypersonic transitional/turbulent mean flow profiles.

Detailed three-dimensional compressible transitional/turbulent boundary-layer profiles are presented for use as test cases in numerical and integral calculation procedures. The profiles were obtained from tests conducted in the Mach 20 leg of the Langley High Reynolds Number Helium Facility. The presented data represent an arduous test case for analytical prediction methods, since 'low Reynolds number' and precursor transition effects should probably be accounted for to accurately predict the boundary-layer growth and development.

Fischer, M. C.↗

NASA NTRS1976

Evidence of the beam pattern concept of subsonic jet noise emission

The methods and results are described of an approach toward positively identifying the apparent location and strength of the sound source in a subsonic jet. The Green's function technique is applied to regenerate the three-dimensional distribution of the acoustic far field from measured data on a two-dimensional plane. The apparent sound-source location is also determined by using geometrical ray acoustics. The results revealed a number of features of the subsonic jet noise mechanisms; they show that the apparent sound source is highly localized within the jet flow and that the spontaneous noise emission from such a compact source volume is in the fashion of a narrow beam with random directions. These observable properties of the sound field offer the basis for a beam pattern concept of subsonic jet noise radiation. A powerful and accurate technique of aerodynamic noise measurement is verified. This technique is expected to have important applications in the development of jet noise reduction technology.

Pao, S. P.↗

NASA NTRS1982

Simulation studies of the physical and chemical processes occurring in the stratospheric clouds of the Mount St. Helens eruptions of May and June 1980

The large and diverse set of observational data collected in the high-altitude clouds of May 18, May 25, and June 13, 1980 was organized and analyzed for trends which reveal the processes at work. The data were used to guide and constrain model simulations of the volcanic eruptions. A comprehensive one-dimensional model of stratospheric sulfate aerosols, sulfur precursor gases, and volcanic ash and dust particles is utilized which accounts for homogeneous and heterogeneous chemistry in the clouds, aerosol nucleation and growth, and cloud expansion. Computational results are given for the time histories of the gaseous species concentrations, sulfate aerosol size dispersions, and ash burdens in the eruption clouds. The long-term buildup of stratospheric aerosols in the Northern Hemisphere and the persistent effects of injected chlorine and water vapor on ozone are discussed. It is concluded that SO2, water vapor, and ash are the most important substances injected by the volcano into the stratosphere, with respect to both the widespread effects on composition and the impact on climate. It is found that the volcano probably had little influence on the climate ( 0.05 K global surface cooling) or on stratospheric ozone ( 0.2 percent maximum hemispherical reduction).

Turco, R. P.↗

NASA NTRS1983

Numerical solution to the glancing sidewall oblique shock wave/turbulent boundary layer interaction in three dimension

A supersonic three-dimensional viscous forward-marching computer design code called PEPSIS is used to obtain a numerical solution of the three-dimensional problem of the interaction of a glancing sidewall oblique shock wave and a turbulent boundary layer. Very good results are obtained for a test case that was run to investigate the use of the wall-function boundary-condition approximation for a highly complex three-dimensional shock-boundary layer interaction. Two additional test cases (coarse mesh and medium mesh) are run to examine the question of near-wall resolution when no-slip boundary conditions are applied. A comparison with experimental data shows that the PEPSIS code gives excellent results in general and is practical for three-dimensional supersonic inlet calculations.

Anderson, B. H.↗

NASA NTRS1983

Numerical solution to the glancing sidewall oblique shock wave/turbulent boundary layer interaction in three-dimension

Anderson, B. H.↗

NASA NTRS1990

Weather prediction using a genetic memory

Kanaerva's sparse distributed memory (SDM) is an associative memory model based on the mathematical properties of high dimensional binary address spaces. Holland's genetic algorithms are a search technique for high dimensional spaces inspired by evolutional processes of DNA. Genetic Memory is a hybrid of the above two systems, in which the memory uses a genetic algorithm to dynamically reconfigure its physical storage locations to reflect correlations between the stored addresses and data. This architecture is designed to maximize the ability of the system to scale-up to handle real world problems.

Rogers, David↗