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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Atomic-Scale Structure and Non-Stoichiometry of Meteoritic Hibonite: A Transmission Electron Microscope Study

Hibonite (CaAl_12O_19) is a common refractory mineral in Ca-Al-rich inclusions (CAIs) in primitive meteorites. Transmission electron microscope (TEM) studies have identified enigmatic planar defects in different occurrences of hibonite in the Allende meteorite that give rise to strong streaking along c* in electron diffraction patterns. Atomic resolution high-angle annular dark-field (HAADF) imaging and energy-dispersive X-ray (EDX) analyses were used to determine the nature and origin of these planar features. HAADF images of hibonite grains reveal lamellar intergrowths of common 1.6 nm spacing, and less commonly 2.0 and 2.5 nm spacings, interspersed in stoichiometric hibonite showing 1.1 nm (002) spacing. Stoichiometric hibonite consists of alternating Ca-containing (“R”) and spinel-structured (“S”) blocks stacked in a sequence RS. In contrast, the 1.6 nm layers result from a doubled S block such that the stacking sequence is RSS, while in the widest defect observed, the stacking sequence is RSSSS. These intergrowths are epitaxial and have coherent, low-strain boundaries with the host hibonite Meteoritic hibonite shows common Ti and Mg substitution for Al in its structure. Atomic-resolution EDX maps of hibonite grains in the Allende CAI confirm the preferred site occupancy of Mg on tetragonal M3 sites in S blocks and of Ti on trigonal bipyramidal M2 and octahedral M4 sites in R blocks. Mg is highly concentrated, but Ti is absent in the planar defects where wider S blocks show Al-rich compositions compared to stoichiometric MgAl_2O_4 spinel. Therefore, Mg likely played the major role in the formation and metastability of planar defects in hibonite. Electron energy loss spectroscopy data from the Ti L_2,3 edge show the presence of mixed Ti oxidation states with ~ 15–20% of Ti as Ti^(3+) in hibonite, suggesting a direct substitution of Ti^(3+) ↔ Al^(3+) in hibonite. The remaining ~ 80–85% of Ti is present as Ti^(4+) and corresponding EDX analyses are consistent with the well-known coupled substitution 2Al^(3+) ↔ Ti^(4+) + Mg^(2+) being the major mechanism for Ti and Mg substitution in hibonite. The formation of planar defects in hibonite occurred during high-temperature nebular condensation or melting/crystallization processes. The occurrence of non-stoichiometric hibonite in the Allende CAI deviates from the mineral formation sequence predicted from equilibrium condensation models. Overall, our atomic resolution TEM observations signify non-equilibrium, kinetic-controlled crystal growth during the high-temperature formation of refractory solids in the early solar nebula.

hibonite↗
NASA NTRS2004

Cockpit System Situational Awareness Modeling Tool

This project explored the possibility of predicting pilot situational awareness (SA) using human performance modeling techniques for the purpose of evaluating developing cockpit systems. The Improved Performance Research Integration Tool (IMPRINT) was combined with the Adaptive Control of Thought-Rational (ACT-R) cognitive modeling architecture to produce a tool that can model both the discrete tasks of pilots and the cognitive processes associated with SA. The techniques for using this tool to predict SA were demonstrated using the newly developed Aviation Weather Information (AWIN) system. By providing an SA prediction tool to cockpit system designers, cockpit concepts can be assessed early in the design process while providing a cost-effective complement to the traditional pilot-in-the-loop experiments and data collection techniques.

Keller, John↗
NASA NTRS1989

Coupled rotor/fuselage dynamic analysis of the AH-1G helicopter and correlation with flight vibrations data

Under a research program designated Design Analysis Methods for VIBrationS (DAMVIBS), existing analytical methods are used for calculating coupled rotor-fuselage vibrations of the AH-1G helicopter for correlation with flight test data from an AH-1G Operational Load Survey (OLS) test program. The analytical representation of the fuselage structure is based on a NASTRAN finite element model (FEM), which has been developed, extensively documented, and correlated with ground vibration test. One procedure that was used for predicting coupled rotor-fuselage vibrations using the advanced Rotorcraft Flight Simulation Program C81 and NASTRAN is summarized. Detailed descriptions of the analytical formulation of rotor dynamics equations, fuselage dynamic equations, coupling between the rotor and fuselage, and solutions to the total system of equations in C81 are included. Analytical predictions of hub shears for main rotor harmonics 2p, 4p, and 6p generated by C81 are used in conjunction with 2p OLS measured control loads and a 2p lateral tail rotor gearbox force, representing downwash impingement on the vertical fin, to excite the NASTRAN model. NASTRAN is then used to correlate with measured OLS flight test vibrations. Blade load comparisons predicted by C81 showed good agreement. In general, the fuselage vibration correlations show good agreement between anslysis and test in vibration response through 15 to 20 Hz.

Corrigan, J. C.↗
NASA NTRS2007

Surveillance and Control of Malaria Transmission in Thailand using Remotely Sensed Meteorological and Environmental Parameters

These slides address the use of remote sensing in a public health application. Specifically, this discussion focuses on the of remote sensing to detect larval habitats to predict current and future endemicity and identify key factors that sustain or promote transmission of malaria in a targeted geographic area (Thailand). In the Malaria Modeling and Surveillance Project, which is part of the NASA Applied Sciences Public Health Applications Program, we have been developing techniques to enhance public health's decision capability for malaria risk assessments and controls. The main objectives are: 1) identification of the potential breeding sites for major vector species; 2) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity; 3) implementation of a dynamic transmission model to identify the key factors that sustain or intensify malaria transmission. The potential benefits are: 1) increased warning time for public health organizations to respond to malaria outbreaks; 2) optimized utilization of pesticide and chemoprophylaxis; 3) reduced likelihood of pesticide and drug resistance; and 4) reduced damage to environment. !> Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. The NASA Earth science data sets that have been used for malaria surveillance and risk assessment include AVHRR Pathfinder, TRMM, MODIS, NSIPP, and SIESIP. Textural-contextual classifications are used to identify small larval habitats. Neural network methods are used to model malaria cases as a function of the remotely sensed parameters. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Discrete event simulations are used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results are in good agreement with mosquito vector and human malaria data acquired by Coleman et al. over 4.5 years in Kong Mong Tha, a remote village in western Thailand. Application of our models is not restricted to the Greater Mekong Subregion. Our models have been applied to malaria in Indonesia, Korea, and other regions in the world with similar success.

Kiang, Richard K.↗
NASA NTRS1980

An empirical propellant response function for combustion stability predictions

An empirical response function model was developed for ammonium perchlorate propellants to supplant T-burner testing at the preliminary design stage. The model was developed by fitting a limited T-burner data base, in terms of oxidizer size and concentration, to an analytical two parameter response function expression. Multiple peaks are predicted, but the primary effect is of a single peak for most formulations, with notable bulges for the various AP size fractions. The model was extended to velocity coupling with the assumption that dynamic response was controlled primarily by the solid phase described by the two parameter model. The magnitude of velocity coupling was then scaled using an erosive burning law. Routine use of the model for stability predictions on a number of propulsion units indicates that the model tends to overpredict propellant response. It is concluded that the model represents a generally conservative prediction tool, suited especially for the preliminary design stage when T-burner data may not be readily available. The model work included development of a rigorous summation technique for pseudopropellant properties and of a concept for modeling ordered packing of particulates.

Hessler, R. O.↗
NASA NTRS1977

Prediction of pilot opinion ratings using an optimal pilot model

A brief review of some of the more pertinent applications of analytical pilot models to the prediction of aircraft handling qualities is undertaken. The relative ease with which multiloop piloting tasks can be modeled via the optimal control formulation makes the use of optimal pilot models particularly attractive for handling qualities research. To this end, a rating hypothesis is introduced which relates the numerical pilot opinion rating assigned to a particular vehicle and task to the numerical value of the index of performance resulting from an optimal pilot modeling procedure as applied to that vehicle and task. This hypothesis is tested using data from piloted simulations and is shown to be reasonable. An example concerning a helicopter landing approach is introduced to outline the predictive capability of the rating hypothesis in multiaxis piloting tasks.

Hess, R. A.↗
NASA NTRSDate not supplied

Passive Thermal Coating Observatory Operating in Low-Earth Orbit (PATCOOL)

Long-term presence on the moon, mars, and beyond necessitates the transport of liquid oxygen (LOX). Resources are limited in space and LOX not only servers as an oxidizer for fuel, but can also be utilized in the production of breathable air for space habitats. A cryogenic thermal control coating, developed by scientists at Kennedy Space Center (KSC), is getting ready to demonstrate it has the potential to answer these challenges. Aluminum samples coated with the cryogenic thermal control coating and AZ-93 white paint will be launching to the International Space Station (ISS) and deployed on a CubeSat into a low-earth orbit. This work covers the predicted sample temperatures in a simulated space environment and a review of the Thermal Desktop model.

Cryogenic Thermal Control Coating↗
DOE OSTI2025

Artificial intelligence-based predictive modeling for imaging neutral particle analyzers on the DIII-D tokamak

The Imaging Neutral Particle Analyzer (INPA) at DIII-D is a diagnostic system used to accurately resolve the energy and spatial distributions of fast ions in fusion plasmas. A novel artificial intelligence (AI) technique named INPA-net is based on Reservoir Computing Networks and developed here to predict active and passive signals produced by charge-exchange reactions from injected and edge-cold neutrals, respectively, in magnetically confined fusion plasmas. This model is trained using a set of 21 time domain signals between 0 s to 3.35 s that includes injected beam and thermal plasma information, and 6444 real 2D experimental images of the INPA in 12 plasma discharges at DIII-D. The trained neural network is able to forecast experimental images in real-time. The model achieves an R-squared value of 0.91, which is higher than the 0.83 value achieved by a simple linear regression model. This improvement highlights the model's enhanced predictive accuracy for measured images from the validation set. This AI approach is valuable due to its rapid response times and potential for integration into real-time plasma control systems. A version of this model capable of generating syntehic images would be useful for the real-time monitoring of fast-ion transport. A comprehensive sensitivity study reveals that INPA-net maintains high performance even with variations in the input parameters, indicating the model's robustness and reliability. While developed for the INPA, the underlying architecture is adaptable and may be applied to various 2D imaging diagnostics in fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1993

The importance of properties in modeling

Casting and welding of superalloys, stainless steel and titanium alloys are processes which can be improved through modeling of heat flow, fluid flow, residual stress development, and microstructural evolution. These simulations require inputs of thermophysical data, some of which involves the partially or totally liquid state. In particular, these processes involve melting, flow in the liquid, and solidification. Modeling of such processes can lead to an improved understanding of defects such as shrinkage, inclusions, cracks, incomplete filling (or penetration), macrosegregation, improper grain structure, and deviations from dimensional specifications. Effective modeling can shorten process development time and improve quality. An approach to these problems is to develop efficient models; validate through correlations with thermal, distortion, and microstructural data; run parametric studies; extract knowledge based rules; and apply to adaptive closed loop control systems. With the appropriate pre- and post-processing, such analyses can be made 'user friendly'. This would include graphical user interfaces as well as realistic images and color maps. In such form, these models can be used for sensitivity analyses, which are useful in defining appropriate sensors and in the development of control strategies. Such modeling can be done at several levels, e.g., the MARO level, modeling large scale phenomena such as heat and fluid flow or material deformation; the MICRO level, modeling the development of dendrites, grains or precipitates; or at the NANO level, modeling point defects, dislocations, stacking faults, etc. There are many computational issues associated with these simulations, e.g. computational efficiency and accuracy. In addition, there are many materials issues, not the least of which is the availability of accurate high temperature thermophysical data for complex alloys. This would include latent heat of fusion, temperature dependent heat capacity and thermal conductivity (for liquid and solid), viscosity, surface tension, thermal expansion, mechanical properties, etc. Preliminary data is frequently gathered from the literature; however, this is often not available for modern alloys. If additional data are required, measurements can be used; however, these are costly, time consuming and can be erroneous due to a lack of testing standards or impure materials. Microstructural predictors can be extracted from thermal information, e.g. cooling rate and thermal gradient; the prediction of microstructure is dependent on solidus and liquidus temperature, mushy zone permeability, the solidification curve, volume changes, phase transformations, alloying effects (such as surface tension or viscosity), mold/metal reactions, metal/environment reactions, etc. Defect maps may be needed to predict the onset of shrinkage, hot cracking or 'freckling'. Constants may be needed for stress relaxation, dendrite coarsening, vaporization, etc. Visualization was used as a tool to better comprehend complex data sets associated with the analysis of directional solidification (including crystal growth) and welding. Examples include not only isotherms, but also cooling rate, growth rate and thermal gradient. The latter two are not single valued scalars, but rather time and space dependent vector fields. Efficient models were developed for both casting and welding to predict heat flow and the relationship to dendrite and grain growth. These codes include many of the non-linear effects, e.g. radiation, which dominate these processes. The home-built FDM code(s) were designed to be useful not only to the scientist, but also to the process engineer. Special output can be requested to compare directly to experimental data. Visualization procedures were developed to visualize critical results, e.g. fusion zone width at the surface opposite that where the arc is applied ('penetration'). Both elaborate and simplified distortion analyses were carried out. It is clear that extensive mechanical property data are critical in order to accurately predict residual stress patterns. A scheme is currently being developed to integrate these modeling tools into a set of control algorithms; however, the success of this approach is critically dependent on the availability of accurate high temperature thermophysical data.

Giamei, A. F.↗
NASA NTRS2017

Spectro-Photometer for the History of the Universe, Epoch of Reionization, and Ices Explorer, One Quarter Scale Prototype Thermal Testing

The Spectro-Photometer for the History of the Universe, Epoch of Reionization, and Ices Explorer (SPHEREx) instrument has been proposed as NASA Small Explorer (SMEX) and Medium Explorer (MIDEX) missions designed to perform an all-sky near-infrared survey. The primary science objective of the SPHEREx instrument is the mapping and cataloging of data on galaxy red shifts and absorption spectra. The SPHEREx instrument utilizes a linear variable band pass filter to provide discrete spectral coverage of the 0.75 to 5.0 μm range. The nominal on-orbit mission lifetime for the instrument is two years with continuous primary science imaging. The SPHEREx instrument will be placed in a near-circular LEO sun-synchronous terminator orbit with a mean altitude of 600 km, and solar beta angles ranging from 59° to 90°. A passive V-groove radiator cooling system was selected for the SPHEREx instrument. This design was chosen for its simplicity and lack of vibration. It includes five radiator stages with the coldest two stages providing temperatures below 80K and 55K for the 2.5μm and 5.3μm detectors respectively. A one quarter scale thermal prototype was constructed to characterize the performance of the SPHEREx thermal control subsystem. This prototype was directly derived and scaled from the current flight design, and accurately replicates all heat flow paths at scale. The prototype was tested in two bounding hot flight-like environments in the Cryogenic Systems Engineering, Advanced Thermal Technology Lab at NASA’s Jet Propulsion Laboratory. Following testing, a previously developed one quarter scale thermal model was correlated to the two conditions seen in test. The resultant correlated model is able to predict the prototype test temperatures to within 1K for all critical radiator stages. An overview of the thermal control design approach, the test configuration, and test and correlation results are presented.

Bolton, Douglas A.↗
NASA NTRSDate not supplied

Interval Predictor Models for Robust System Identification

This paper proposes a framework for the identification and uncertainty quantification of plant models according to multivariable data. The only restriction imposed upon such models is for their outputs to depend continuously on their parameters. An Interval Predictor Model (IPM) prescribes the parameters of a computational model as a path-connected set thereby making each predicted output an interval-valued function of its inputs. The formulation proposed seeks the parameter set for which the predicted outputs tightly enclose the data. This set, which is modeled as a semi-algebraic set of low-degree polynomials, enables the characterization of possibly strong parameter dependencies commonly found in practice. This uncertainty characterization makes the resulting plant model amenable to robust control approaches using polynomial optimization. Furthermore, we use non-convex scenario theory to assess the reliability of the resulting IPM. This assessment yields a distribution-free upper bound on the probability that future data will fall outside the predicted intervals.

interval↗
NASA NTRS1999

Development of a flow feedback pulse duplicator system with rhesus monkey arterial input impedance characteristics

An in vitro pulsatile pump flow system that is capable of producing physiologic pressures and flows in a mock circulatory system tuned to reproduce the first nine harmonics of the input impedance of a rhesus monkey was developed and tested. The system was created as a research tool for evaluating cardiovascular function and for the design, testing, and evaluation of electrical-mechanical cardiovascular models and chronically implanted sensors. The system possesses a computerized user interface for controlling a linear displacement pulsatile pump in a controlled flow loop format to emulate in vivo cardiovascular characteristics. Evaluation of the pump system consisted of comparing its aortic pressure and flow profiles with in vivo rhesus hemodynamic waveforms in the time and frequency domains. Comparison of aortic pressure and flow data between the pump system and in vivo data showed good agreement in the time and frequency domains, however, the pump system produced a larger pulse pressure. The pump system can be used for comparing cardiovascular parameters with predicted cardiovascular model values and for evaluating such items as vascular grafts, heart valves, biomaterials, and sensors. This article describes the development and evaluation of this feedback controlled cardiovascular dynamics simulation modeling system.

Non-NASA Center↗
NASA NTRS2020

Generation and Calibration of Linear Models of Aircraft with Highly Coupled Aeroelastic and Flight Dynamics

The lightweight structures and unconventional configurations being considered for the next generation of aircraft mean that any effort to predict or control the flight dynamics is impacted by the structural dynamics. One of the most severe forms of coupling between aeroelasticity and flight dynamics is an instability called body freedom flutter. The existing tools often assume a relatively weak effect of structural dynamics on the flight dynamics, and are therefore incapable of modeling strong interactions like body freedom flutter. A method of combining different sources of data traditionally used for aeroelasticity and flight dynamics is described by reconciling many of the differences between these models. By building upon past modeling efforts, a level of familiarity in the approach is achieved. Generally the differences from the traditional approaches are subtle but significant. The traditional frequency domain flutter model in a modal coordinate system is converted to a form consistent with a time domain flight dynamics model. The time domain rational function approximation about a non-inertial coordinate system and the unique constraints for the conversion between the inertial and non-inertial coordinate systems are discussed. A consistent transformation of the states of aeroelastic models to flight dynamics models is derived, which enables the integration of data from higher fidelity computational fluid dynamics models or wind-tunnel testing. The present method of integrating multidisciplinary data was used to create models that compare well with X-56A flight-test data, including conditions past the flutter speed.

Ouellette, Jeffrey↗
NASA NTRS1988

Sensitivity of a global climate model to the specification of convective updraft and downdraft mass fluxes

The response of the GISS global climate model to different parameterizations of moist convective mass flux is studied. A control run with arbitrarily specified updraft mass flux is compared to experiments predicting cumulus mass fulx on the basis of low-level convergence, convergence plus surface evaporation, or convergence and evaporation modified by varying boundary layer height. Also, an experiment that includes a simple parameterization of saturated convective-scale downdrafts is discussed. It is found that the model correctly simulates the correlation between deep convection strength and tropical sea surface temperature in each experiment with the parameterization of cumulus mass flux having little effect. The implications of the experiments for cloud effects on climate sensitivity are examined.

Del Genio, Anthony D.↗
DOE OSTI2025

Microwave Debinding of Ceramics Produced by Additive Manufacturing

Microwave-assisted debinding offers an innovative approach to processing 3D-printed engineering ceramics. Ceramic parts produced with photopolymer-based additive manufacturing techniques require thermal debinding to remove polymers that bind ceramic particles during the printing process. Microwave-assisted debinding significantly reduces processing times and offers energy savings over conventional thermal treatments due to higher heating rates and more uniform heating. Finite-element modeling of the debinding process allows for the optimization and prediction of temperature distribution, stress development, and potential defects, leading to improved process control and material quality.

36 - MATERIALS SCIENCE↗
NASA NTRS2017

WFIRST coronagraph optical modeling

End-to-end numerical optical modeling of the WFIRST coronagraph incorporating wavefront sensing and control is used to determine the performance of the coronagraph with realistic errors, including pointing jitter and polarization. We present the performance estimates of the current flight designs as predicted by modeling. We also describe the release of a new version of the PROPER optical propagation library, our primary modeling tool, which is now available for Python and Matlab in addition to IDL.

Zhou, Hanying↗
NASA NTRS2010

Modeling a Large Submillimeter-Wave Observatory

The 25 meter aperture Cornell Caltech Atacama Telescope (CCAT) will provide an enormous increase in sensitivity in the submillimeter bands compared to existing observatories, provided it can establish and maintain excellent image quality. To accomplish this at a very low cost, it is necessary to conduct accurate engineering trades, including the most effective segment and wavefront sensing and control approach, to determine the best method for continuously maintaining wavefront quality in the operational environment. We describe an integrated structural/optical/controls model that provides accurate performance prediction. We also detail the analysis methods used to quantify critical design trades.

Segment Sensing↗
DOE OSTI2025

Vector-level feedforward control of LPBF melt pool area using a physics-based thermal model

Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and geometric inaccuracies, stemming in part from variations in the melt pool. Here, this paper proposes a novel vector-level feedforward control framework for regulating melt pool area in LPBF. By decoupling part-scale thermal behavior from small-scale melt pool physics, the controller provides a scale-agnostic prediction of melt pool area and efficient optimization over it. This is done by operating on two coupled lightweight models: a finite-difference thermal model that efficiently captures vector-level temperature fields and a reduced-order, analytical melt pool model. Each model is calibrated separately with minimal single-track and 2D experiments, and the framework is validated on a complex 3D geometry in both Inconel 718 and 316L stainless steel. Results showed that feedforward vector-level laser power scheduling reduced geometric inaccuracy in key dimensions by 62%, overall porosity by 16.5%, and photodiode root-mean-squared deviation by 38.5% on average. Overall, this modular, data-efficient approach demonstrates that proactively compensating for known thermal effects can significantly improve part quality while remaining computationally efficient and readily extensible to other materials and machines.

Additive manufacturing↗