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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Boundary-Layer Detection at Cryogenic Conditions Using Temperature Sensitive Paint Coupled with a Carbon Nanotube Heating Layer

Detection of flow transition on aircraft surfaces and models can be vital to the development of future vehicles and computational methods for evaluating vehicle concepts. In testing at ambient conditions, IR thermography is ideal for this measurement. However, for higher Reynolds number testing, cryogenic facilities are often used, in which IR thermography is difficult to employ. In these facilities, temperature sensitive paint is an alternative with a temperature step introduced to enhance the natural temperature change from transition. Traditional methods for inducing the temperature step by changing the liquid nitrogen injection rate often change the tunnel conditions. Recent work has shown that adding a layer consisting of carbon nanotubes to the surface can be used to impart a temperature step on the model surface with little change in the operating conditions. Unfortunately, this system physically degraded at 130 K and lost heating capability. This paper describes a modification of this technique enabling operation down to at least 77 K, well below the temperature reached in cryogenic facilities. This is possible because the CNT layer is in a polyurethane binder. This was tested on a Natural Laminar Flow model in a cryogenic facility and transition detection was successfully visualized at conditions from 200 K to 110 K. Results were also compared with the traditional temperature step method.

Goodman, Kyle Z.↗
NASA NTRS2021

A Machine Learning Approach to Objective Identification of Dust in Satellite Imagery

Airborne dust has broad adverse effects on human activity, including aviation, human health, and agriculture. Remote sensing observations are used to detect dust and aerosols in the atmosphere using long established techniques. False color Red-Green-Blue (RGB) imagery using band differences sensitive to dust absorption (Dust RGB) is currently used operationally to assist forecasters and decision-makers in identifying dust at night, but there are still limitations, subjectivity, and nuances to image interpretation making night-time dust identification difficult even for experts. This study applies machine learning to the problem of night-time dust detection with a simple random forest (RF) model using Geostationary Operational Environmental Satellite-16 (GOES-16) Advanced Baseline Imager (ABI) infrared imagery, band differences sensitive to dust absorption, and Dust RGB color components as inputs to the model. The RF model achieves an Area-Under-Curve (AUC) of 0.97 with a standard deviation of 0.04 for dust cases. For images with dust present, the model correctly labels 85% of dust pixels and 99.96% of no-dust pixels for all dust images in the validation data set. The addition of a single null case to the training data set drastically reduces error in labeling no-dust pixels as dust from 45% to 14.5%. Application of the machine learning model to the April 13–14, 2019 dust event demonstrates the ability of the model to identify dust during night-time hours when visual dust detection is limited by the cooling ground surface characteristics.

dust↗
NASA NTRSDate not supplied

Prediction of Broadband Blade-Wake Back-Scatter Noise from a Hovering Ideally Twisted Rotor using OVERFLOW2-ANOPP2

This work illustrates the use of a hybrid RANS/LES framework for the prediction of broadband noise via integral formulations from an ideally twisted hovering rotor. Four simulations were conducted, which investigated the effect of different turbulence modeling and spatiotemporal resolutions. The aerodynamic performance and aeroacoustics predicted by these four computational cases were compared against data acquired in the Small Hover Anechoic Chamber at the NASA Langley Research Center and against previous simulations conducted using the lattice-Boltzmann solver, PowerFLOW. The simulation case with the finest spatial resolution had the most favorable aerodynamic performance and broadband noise comparison with measured data; however, the simulation case utilizing the SST-DDES turbulence model predicted the most accurate tonal noise signature. Aerodynamic flowfield visualizations identified near-wake trailing edge vortex shedding, perpendicular blade-vortex interactions, and tip vortex formation, which are known to cause broadband noise. The fluid dynamics associated with a new broadband noise source, blade-wake back-scatter, were also identified. Lastly, a broadband noise source visualization technique was utilized to confirm the presence of blade-wake back-scatter as a dominant broadband noise source.

blade-wake back-scatter↗
NASA NTRSDate not supplied

Improving Sim-to-Real Transfer in Vision-Based Robot Navigation Via Instance-Level GAN-Based Data Augmentation

Achieving robust vision-based robotic tasks requires large amounts of data, which are often difficult to obtain in real-world scenarios. Simulators and synthetic data offer a cost-effective alternative, but the visual gap between simulation and reality hinders the performance of models when deployed in real-world environments. In this paper, we present a data augmentation pipeline that integrates a foundation model (Segment Anything Model) with an unsupervised image-to-image translation model (CycleGAN) for instance-level domain transfer from simulation to reality. This pipeline enables the generation of realistic labeled data from synthetic images for training supervised machine learning models in vision-based navigation tasks. We evaluate our approach on real-world data for ego-vehicle pose estimation, a critical autonomous navigation task involving the prediction of cross-track position and heading angle relative to road center line markings. The results of our tests show that our GAN-based data augmentation pipeline significantly outperforms models trained solely on simulation data or on data processed with standard image augmentation methods for sim-to-real transfer, enhancing model robustness and generalizability in real-world scenarios. Our method provides a scalable and flexible data augmentation tool for leveraging large synthetic datasets to enhance vision-based robotic navigation tasks.

artificial intelligence↗
NASA NTRS2026

Improvement in the Thermal-to-Structural Model Mapping Process for Integrated Modeling for the Roman Space Telescope

Integrated Modeling has been a key component of verifying optical requirements for the Nancy Grace Roman Space Telescope (RST) that are either impossible or impractical to verify exclusively through ground testing. Two major areas for integrated Modeling are Jitter and Thermal Distortion that require the exchanges of model performance predictions across disciplines. In both cases, distortions are impressed on optical models to evaluate the impact on boresight alignment and wave front error. In the case of Jitter, the disturbances are driven by reactions to motions most often from actuators; however, in the case of thermal distortion, the motions are driven by thermal expansion or contraction as a result of changing temperatures. This then requires a link further upstream to the thermal model, which is used to predict the thermal performance and temperature gradients and stability. The process for mapping temperatures from a thermal model to a corresponding structural model has been performed numerous times through the RST project lifecycle, with improvements in the accuracy, verification, and effort sought throughout. This paper describes some of the recent improvements to the process, including: capture of the visualization parameters, automatic generation of the mapped images for both the thermal and structural model groupings, and reduction in the effort to assemble the full set of mapped temperatures. These upgrades have greatly reduced the manual effort associated with thermal mapping and allowed for faster turn-around of Integrated Modeling predictions.

Thermal Mapping↗
NASA NTRS1995

Investigations of the pathogenesis of acquired pendular nystagmus

We investigated the pathogenesis of acquired pendular nystagmus (APN) in six patients, three of whom had multiple sclerosis. First, we tested the hypothesis that the oscillations of APN are due to a delay in visual feedback secondary, for example, to demyelination of the optic nerves. We manipulated the latency to onset of visually guided eye movements using an electronic technique that induces sinusoidal oscillations in normal subjects. This manipulation did not change the characteristics of the APN, but did superimpose lower-frequency oscillations similar to those induced in normal subjects. These results are consistent with current models for smooth (non-saccadic) eye movements, which predict that prolongation of visual feedback could not account for the high-frequency oscillations that often characterize APN. Secondly, we attempted to determine whether an increase in the gain of the visually-enhanced vestibulo-ocular reflex (VOR), produced by viewing a near target, was accompanied by a commensurate increase in the amplitude of APN. Increases in horizontal or vertical VOR gain during near viewing occurred in four patients, but only two of them showed a parallel increase in APN amplitude. On the other hand, APN amplitude decreased during viewing of the near target in the two patients who showed no change in VOR gain. Taken together, these data suggest that neither delayed visual feedback nor a disorder of central vestibular mechanisms is primarily responsible for APN. More likely, these ocular oscillations are produced by abnormalities of internal feedback circuits, such as the reciprocal connections between brainstem nuclei and cerebellum.

NASA Program Space Physiology and Countermeasures↗
NASA NTRS1999

Aerodynamic Characteristics and Control Effectiveness of the HL-20 Lifting Body Configuration at Mach 10 in Air

A 0.0196-scale model of the HL-20 lifting-body, one of several configurations proposed for future crewed spacecraft, was tested in the Langley 31-Inch Mach 10 Tunnel. The purpose of the tests was to determine the effectiveness of fin-mounted elevons, a lower surface flush-mounted body flap, and a flush-mounted yaw controller at hypersonic speeds. The nominal angle-of-attack range, representative of hypersonic entry, was 2 deg to 41 deg, the sideslip angles were 0 deg, 2 deg, and -2 deg, and the test Reynolds number was 1.06 x 10 E6 based on model reference length. The aerodynamic, longitudinal, and lateral control effectiveness along with surface oil flow visualizations are presented and discussed. The configuration was longitudinally and laterally stable at the nominal center of gravity. The primary longitudinal control, the fin-mounted elevons, could not trim the model to the desired entry angle of attack of 30 deg. The lower surface body flaps were effective for roll control and the associated adverse yawing moment was eliminated by skewing the body flap hinge lines. A yaw controller, flush-mounted on the lower surface, was also effective, and the associated small rolling moment was favorable.

Scallion, William I.↗
NASA NTRS1992

Calibration of the ARID robot

The author has formulated a new, general model for specifying the kinematic properties of serial manipulators. The new model kinematic parameters do not suffer discontinuities when nominally parallel adjacent axes deviate from exact parallelism. From this new theory the author develops a first-order, lumped-parameter, calibration-model for the ARID manipulator. Next, the author develops a calibration methodology for the ARID based on visual and acoustic sensing. A sensor platform, consisting of a camera and four sonars attached to the ARID end frame, performs calibration measurements. A calibration measurement consists of processing one visual frame of an accurately placed calibration image and recording four acoustic range measurements. A minimum of two measurement protocols determine the kinematics calibration-model of the ARID for a particular region: assuming the joint displacements are accurately measured, the calibration surface is planar, and the kinematic parameters do not vary rapidly in the region. No theoretical or practical limitations appear to contra-indicate the feasibility of the calibration method developed here.

Doty, Keith L↗
NASA NTRS1994

Computational Approaches to Vestibular Research

The Biocomputation Center at NASA Ames Research Center is dedicated to a union between computational, experimental and theoretical approaches to the study of neuroscience and of life sciences in general. The current emphasis is on computer reconstruction and visualization of vestibular macular architecture in three-dimensions (3-D), and on mathematical modeling and computer simulation of neural activity in the functioning system. Our methods are being used to interpret the influence of spaceflight on mammalian vestibular maculas in a model system, that of the adult Sprague-Dawley rat. More than twenty 3-D reconstructions of type I and type II hair cells and their afferents have been completed by digitization of contours traced from serial sections photographed in a transmission electron microscope. This labor-intensive method has now been replace d by a semiautomated method developed in the Biocomputation Center in which conventional photography is eliminated. All viewing, storage and manipulation of original data is done using Silicon Graphics workstations. Recent improvements to the software include a new mesh generation method for connecting contours. This method will permit the investigator to describe any surface, regardless of complexity, including highly branched structures such as are routinely found in neurons. This same mesh can be used for 3-D, finite volume simulation of synapse activation and voltage spread on neuronal surfaces visualized via the reconstruction process. These simulations help the investigator interpret the relationship between neuroarchitecture and physiology, and are of assistance in determining which experiments will best test theoretical interpretations. Data are also used to develop abstract, 3-D models that dynamically display neuronal activity ongoing in the system. Finally, the same data can be used to visualize the neural tissue in a virtual environment. Our exhibit will depict capabilities of our computational approaches and some of our findings from their application. For example, our research has demonstrated that maculas of adult mammals retain the property of synaptic plasticity. Ribbon synapses increase numerically and undergo changes in type and distribution (p<0.0001) in type II hair cells after exposure to microgravity for as few as nine days. The finding of macular synaptic plasticity is pertinent to the clinic, and may help explain some. balance disorders in humans. The software used in our investigations will be demonstrated for those interested in applying it in their own research.

Ross, Muriel D.↗
NASA NTRS1986

Wind-Tunnel-Model Leak-Checking System

Voice-actuated system allows one operator to do work of three. System uses voice-recognition-and-response unit and graphics terminal to interact with technician and to provide technician visual feedback. Computer-based Leakcheck system allows computer to do more of total work in checking model for leaks to reduce time and manpower required to perform task.

Larson, W. E.↗
DOE OSTI2024

Simulation of Helium Flow Visualization Apparatus for Studies of Blanket Cooling in Fusion Reactors

Flow visualization is essential to understanding helium cooling performance. This article investigates helium flow visualization in an apparatus to support the design of the blanket first wall for a fusion reactor. Helium’s safety advantages make it an attractive coolant, but effective cooling and flow visualization remain challenging. Sophisticated simulations are conducted in different test sections to address three key areas in the design of a test apparatus and cooling channel enhancements: the influence of viewing glass windows on flow patterns, the impact of increased heating, and the effectiveness of cooling structures like baffles. Viewing glass windows introduce flow recirculation region bifurcation and flow asymmetry, affecting flow patterns and necessitating careful analysis in future experiments. Increased heating results in helium flow detachment from the heated surface, leading to hot spots. Cooling structures, particularly baffles, prove effective in maintaining consistent attachment to the heated surface, improving the heat transfer performance. Further, this study also examines a tunable parameter in the turbulence model, highlighting the importance of accurate model tuning for future fusion reactor cooling designs. With an imminent helium flow visualization facility, these simulations will be used to optimize cooling structures on the heated wall to improve flow attachment and heat transfer efficiency. This work serves as a first investigation of the helium flow visualization apparatus for blanket cooling enhancement in fusion reactor design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1993

The enhanced Software Life Cyle Support Environment (ProSLCSE): Automation for enterprise and process modeling

In this paper, we have introduced a comprehensive method for enterprise modeling that addresses the three important aspects of how an organization goes about its business. FirstEP includes infrastructure modeling, information modeling, and process modeling notations that are intended to be easy to learn and use. The notations stress the use of straightforward visual languages that are intuitive, syntactically simple, and semantically rich. ProSLCSE will be developed with automated tools and services to facilitate enterprise modeling and process enactment. In the spirit of FirstEP, ProSLCSE tools will also be seductively easy to use. Achieving fully managed, optimized software development and support processes will be long and arduous for most software organizations, and many serious problems will have to be solved along the way. ProSLCSE will provide the ability to document, communicate, and modify existing processes, which is the necessary first step.

Milligan, James R.↗
NASA NTRS2002

Quick Fix for Managing Risks

Under a Phase II SBIR contract, Kennedy and Lumina Decision Systems, Inc., jointly developed the Schedule and Cost Risk Analysis Modeling (SCRAM) system, based on a version of Lumina's flagship software product, Analytica(R). Acclaimed as "the best single decision-analysis program yet produced" by MacWorld magazine, Analytica is a "visual" tool used in decision-making environments worldwide to build, revise, and present business models, minus the time-consuming difficulty commonly associated with spreadsheets. With Analytica as their platform, Kennedy and Lumina created the SCRAM system in response to NASA's need to identify the importance of major delays in Shuttle ground processing, a critical function in project management and process improvement. As part of the SCRAM development project, Lumina designed a version of Analytica called the Analytica Design Engine (ADE) that can be easily incorporated into larger software systems. ADE was commercialized and utilized in many other developments, including web-based decision support.

Source record↗
NASA NTRS1995

Visualization of numerical simulation results: An interactive tool for mission oriented theory

With the advent of multispacecraft missions, it became obvious that theoretical models are needed, not only to interpret local spacecraft observations, but also to link single point measurements. Models that address space plasma phenomena on local and global scales, that involve nonlinear processes, and that use self-consistent approaches, were developed. An interactive system for visualizing and analyzing numerical simulation results was also developed. This system is based on visualization modules which use the application visualization system and the NCAR graphic packages. Examples from recent simulations illustrate how these modules can be used for displaying and manipulating simulation results.

Berchem, Jean↗
NASA NTRS2000

Bubble Formation on a Wall in Cross-Flowing Liquid and Surrounding Fluid Motion,With and Without Heating

Application of gas-liquid two-phase flow systems for space-based thermal management and for the HEDS program demands a precise control of bubble size distribution in liquid. The necessity of bulk liquid motion for controlling bubble size and frequency in the space environment has been suggested by recent studies on pool, forced convection boiling and bubble formation in flowing liquid. The present work, consisting of two parts, explores bubble generation at wall in a cross-flowing liquid, i.e., in a forced convection boiling configuration. A schematic is shown. The first part looks into the bubble formation process under isothermal conditions in a reduced gravity environment, by injecting gas through a hole in the wall of a flowing liquid channel. In the latter part with channel wall heating, flow and temperature fields near a single bubble are studied under normal (1-g) and micro-gravity (mu-g) conditions. The objective of the isothermal experiments is to experimentally investigate the effects of liquid cross-flow velocity, gas flow rate, and orifice diameter on bubble formation. Data were taken mainly under reduced gravity conditions but some data were taken in normal gravity for comparison. The reduced gravity experiment was conducted aboard the NASA DC-9 Reduced Gravity Aircraft. The results show that the process of bubble formation and detachment depends on gravity, the orifice diameter (D(sub N)), the gas flow rate (Q(sub g)), and the liquid cross-flow velocity (U(sub L)). The reduced gravity data are shown. The data are analyzed based on a force balance, and two different detachment mechanisms are identified. When the gas momentum is large, the bubble detaches from the injection orifice as the gas momentum overcomes the attaching effects of liquid drag and inertia. The surface tension force is much reduced because a large part of the bubble pinning edge at the orifice is lost as the bubble axis is tilted by the liquid flow. When the gas momentum is small, the force balance in the liquid flow direction is important, and the bubble detaches when the bubble axis inclination exceeds a certain angle. With wall heating, liquid motion around an air bubble in cross-flowing 2cs silicone oil is experimentally investigated in 1-g. A spectral element based steady 2D numerical model is also developed. The traces of particles from experimental flow visualization and the corresponding computed streamlines are shown. At the upstream side of the bubble facing the cross-flow, thermocapillary and forced convection create liquid motion away from the wall, up along the surface. At the downstream side, a competing interaction between the two creates a recirculation cell, causing the bulk liquid to stagnate on the surface and separate thereafter. The important dimensionless parameters are - Surface tension and local cross-flow Reynolds numbers R(sub sigma)(U(sub ref)a/v) and Re(sub loc)(U(sub L)a/v), respectively based on reference thermocapillary U(sub ref)(sigma(sub T)Delta.T/mu, Delta T=T(sub wall)-T(sub liquid)) and local cross-flow velocity U(sub L), Prandtl number P(sub r) and Grashoff number Gr(rho.g.beta.DeltaTa(sup 3)/mu.v). Variation of the stagnation point with R(sub sigma) and Re(sub loc) is shown. Also shown are good agreement between experimental and numerical results in 1-g. The computational model is extended to mu-g condition to investigate temperature and velocity on the bubble surface, stagnation and reattachment points of the recirculation cell and wall heat transfer. It is observed that wall heating significantly alters the flow field around the bubble and thus the forces acting on the bubble, which control its detachment. Thus a combination of heating and liquid cross-flow can be utilized to precisely control bubble formation in a mu-g environment.

Bhunia, Avijit↗
DOE OSTI2025

CGSim: A Simulation Framework for Large Scale Distributed Computing Environment

Large-scale distributed computing infrastructures such as the Worldwide LHC Computing Grid (WLCG) require comprehensive simulation tools for evaluating performance, testing new algorithms, and optimizing resource allocation strategies. However, existing simulators suffer from limited scalability, hardwired algorithms, lack of real-time monitoring, and inability to generate datasets suitable for modern machine learning approaches. We present CGSim, a simulation framework for large-scale distributed computing environments that addresses these limitations. Built upon the validated SimGrid simulation framework, CGSim provides high-level abstractions for modeling heterogeneous grid environments while maintaining accuracy and scalability. Key features include a modular plugin mechanism for testing custom workflow scheduling and data movement policies, interactive real-time visualization dashboards, and automatic generation of event-level datasets suitable for AI-assisted performance modeling. We demonstrate CGSim’s capabilities through a comprehensive evaluation using production ATLAS PanDA workloads, showing significant calibration accuracy improvements across WLCG computing sites. Scalability experiments show near-linear scaling for multi-site simulations, with distributed workloads achieving 6 × better performance compared to single-site execution. The framework enables researchers to simulate WLCG-scale infrastructures with hundreds of sites and thousands of concurrent jobs within practical time budget constraints on commodity hardware.

Vatsavai, Sairam Sri [Brookhaven National Laborato↗