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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 55 records · Page 3

Microcomputer-based tests for repeated-measures: Metric properties and predictive validities

A menu of psychomotor and mental acuity tests were refined. Field applications of such a battery are, for example, a study of the effects of toxic agents or exotic environments on performance readiness, or the determination of fitness for duty. The key requirement of these tasks is that they be suitable for repeated-measures applications, and so questions of stability and reliability are a continuing, central focus of this work. After the initial (practice) session, seven replications of 14 microcomputer-based performance tests (32 measures) were completed by 37 subjects. Each test in the battery had previously been shown to stabilize in less than five 90-second administrations and to possess retest reliabilities greater than r = 0.707 for three minutes of testing. However, all the tests had never been administered together as a battery and they had never been self-administered. In order to provide predictive validity for intelligence measurement, the Wechsler Adult Intelligence Scale-Revised and the Wonderlic Personnel Test were obtained on the same subjects.

Kennedy, Robert S.↗

A unit-cell model of textile composite beams for predicting stiffness properties

Flexural stiffness properties of a textile composite beam are obtained from a finite-element model of the unit cell. Three linearly independent deformations, namely, pure extension, pure bending and pure shear, are applied to the unit cell. The top and bottom surfaces of the beam are assumed to be traction free. Periodic boundary conditions on the lateral boundaries of the unit cell are enforced by multi-point constraint elements. From the forces acting on the unit cell, the flexural stiffness coefficients of the composite beam are obtained. The difficulties in determining the transverse shear stiffness are discussed, and a modified approach is presented. The methods are first verified by applying them to isotropic and bimaterial beams for which the results are known, and then illustrated for a simple plain-weave textile composite.

Sankar, Bhavani V.↗

CEMCAN Software Enhanced for Predicting the Properties of Woven Ceramic Matrix Composites

Major advancements are needed in current high-temperature materials to meet the requirements of future space and aeropropulsion structural components. Ceramic matrix composites (CMC's) are one class of materials that are being evaluated as candidate materials for many high-temperature applications. Past efforts to improve the performance of CMC's focused primarily on improving the properties of the fiber, interfacial coatings, and matrix constituents as individual phases. Design and analysis tools must take into consideration the complex geometries, microstructures, and fabrication processes involved in these composites and must allow the composite properties to be tailored for optimum performance. Major accomplishments during the past year include the development and inclusion of woven CMC micromechanics methodology into the CEMCAN (Ceramic Matrix Composites Analyzer) computer code. The code enables one to calibrate a consistent set of constituent properties as a function of temperature with the aid of experimentally measured data.

Murthy, Pappu L. N.↗

Thermal radiation heat transfer.

A comprehensive discussion of heat transfer by thermal radiation is presented, including the radiative behavior of materials, radiation between surfaces, and gas radiation. Among the topics considered are property prediction by electromagnetic theory, the observed properties of solid materials, radiation in the presence of other modes of energy transfer, the equations of transfer for an absorbing-emitting gas, and radiative transfer in scattering and absorbing media. Also considered are radiation exchange between black isothermal surfaces, radiation exchange in enclosures composed of diffuse gray surfaces and in enclosures having some specularly reflecting surfaces, and radiation exchange between nondiffuse nongray surfaces. The use of the Monte Carlo technique in solving radiant-exchange problems and problems of radiative transfer through absorbing-emitting media is explained.

Siegel, R.↗

Prediction of Mechanical Properties of Polymers With Various Force Fields

The effect of force field type on the predicted elastic properties of a polyimide is examined using a multiscale modeling technique. Molecular Dynamics simulations are used to predict the atomic structure and elastic properties of the polymer by subjecting a representative volume element of the material to bulk and shear finite deformations. The elastic properties of the polyimide are determined using three force fields: AMBER, OPLS-AA, and MM3. The predicted values of Young s modulus and shear modulus of the polyimide are compared with experimental values. The results indicate that the mechanical properties of the polyimide predicted with the OPLS-AA force field most closely matched those from experiment. The results also indicate that while the complexity of the force field does not have a significant effect on the accuracy of predicted properties, small differences in the force constants and the functional form of individual terms in the force fields determine the accuracy of the force field in predicting the elastic properties of the polyimide.

Odegard, Gregory M.↗

Theoretical Prediction of Thermal Expansion Anisotropy for Y 2 Si 2 O 7 Environmental Barrier Coatings Using a Deep Neural Network Potential and Comparison to Experiment

Environmental barrier coatings (EBCs) are an enabling technology for silicon carbide (SiC)-based ceramic matrix composites (CMCs) in extreme environments such as gas turbine engines. However, development of new coating systems is hindered by the large design space and difficulty in predicting properties for these materials. Density Functional Theory (DFT) has successfully been used to model and predict some thermodynamic and thermo-mechanical properties of high-temperature ceramics for EBCs, although these calculations are challenging due to their high computational costs. In this work, we use machine learning to train a deep neural network potential (DNP) for Y 2 Si 2 O 7 , which is then applied to calculate thermodynamic and thermo-mechanical properties at near-DFT accuracy much faster and using less computational resources than DFT. We use this DNP to predict phonon-based thermodynamic properties of Y 2 Si 2 O 7 with good agreement to DFT and experiments. We also utilize the DNP to calculate the anisotropic, lattice direction-dependent coefficients of thermal expansion (CTEs) for Y 2 Si 2 O 7 . Molecular dynamics trajectories using the DNP correctly demonstrate accurate prediction of the anisotropy of the CTE in good agreement with diffraction experiments. In the future, this DNP could be applied to accelerate additional property calculations for Y 2 Si 2 O 7 compared to DFT or experiments.

rare earth silicates↗

Modeling of 3-D Woven Ceramic Matrix Composites

Three different approaches are being pursued at the NASA Glenn Research Center to predict the nanostructural behavior of three-dimensional woven ceramic matrix composites. These are: a micromechanics-based approach using W-CEMCAN (Woven Ceramic Matrix Composite Analyzer), a laminate analogy method and a structural frame approach (based on the finite element method). All three techniques are applied to predict the thermomechanical properties of a three-dimensional woven angle interlock C/SiC composite. The properties are predicted for room temperature and 1100 C and the predicted properties are compared to measurements. General observations regarding the three approaches for three-dimensional composite modeling are discussed.

Murthy, Pappu L. N.↗

Multi-Scale Modeling of Liquid Phase Sintering Affected by Gravity: Preliminary Analysis

A multi-scale simulation concept taking into account impact of gravity on liquid phase sintering is described. The gravity influence can be included at both the micro- and macro-scales. At the micro-scale, the diffusion mass-transport is directionally modified in the framework of kinetic Monte-Carlo simulations to include the impact of gravity. The micro-scale simulations can provide the values of the constitutive parameters for macroscopic sintering simulations. At the macro-scale, we are attempting to embed a continuum model of sintering into a finite-element framework that includes the gravity forces and substrate friction. If successful, the finite elements analysis will enable predictions relevant to space-based processing, including size and shape and property predictions. Model experiments are underway to support the models via extraction of viscosity moduli versus composition, particle size, heating rate, temperature and time.

Olevsky, Eugene↗

Electrostatic Levitation for Studies of Additive Manufactured Materials

The electrostatic levitation (ESL) laboratory at NASA's Marshall Space Flight Center is a unique facility for investigators studying high temperature materials. The laboratory boasts two levitators in which samples can be levitated, heated, melted, undercooled, and resolidified. Electrostatic levitation minimizes gravitational effects and allows materials to be studied without contact with a container or instrumentation. The lab also has a high temperature emissivity measurement system, which provides normal spectral and normal total emissivity measurements at use temperature. The ESL lab has been instrumental in many pioneering materials investigations of thermophysical properties, e.g., creep measurements, solidification, triggered nucleation, and emissivity at high temperatures. Research in the ESL lab has already led to the development of advanced high temperature materials for aerospace applications, coatings for rocket nozzles, improved medical and industrial optics, metallic glasses, ablatives for reentry vehicles, and materials with memory. Modeling of additive manufacturing materials processing is necessary for the study of their resulting materials properties. In addition, the modeling of the selective laser melting processes and its materials property predictions are also underway. Unfortunately, there is very little data for the properties of these materials, especially of the materials in the liquid state. Some method to measure thermophysical properties of additive manufacturing materials is necessary. The ESL lab is ideal for these studies. The lab can provide surface tension and viscosity of molten materials, density measurements, emissivity measurements, and even creep strength measurements. The ESL lab can also determine melting temperature, surface temperatures, and phase transition temperatures of additive manufactured materials. This presentation will provide background on the ESL lab and its capabilities, provide an approach to using the ESL in supporting the development and modeling of the selective laser melting process for metals, and provide an overview of the results to date.

SanSoucie, Michael P.↗

ASRM radiation and flowfield prediction status

Existing and proposed methods for the prediction of plume radiation are discussed in terms of their application to the NASA Advanced Solid Rocket Motor (ASRM) and Space Shuttle Main Engine (SSME) projects. Extrapolations of the Solid Rocket Motor (SRM) are discussed with respect to preliminary predictions of the primary and secondary radiation environments. The methodology for radiation and initial plume property predictions are set forth, including a new code for scattering media and independent secondary source models based on flight data. The Monte Carlo code employs a reverse-evaluation approach which traces rays back to their point of absorption in the plume. The SRM sea-level plume model is modified to account for the increased radiation in the ASRM plume due to the ASRM's propellant chemistry. The ASRM cycle-1 environment predictions are shown to identify a potential reason for the shutdown spike identified with pre-SRM staging.

Reardon, J. E.↗

Evaluation of a High-Resolution Numerical Weather Prediction Model’s Simulated Clouds Using Observations from CloudSat, GOES-13 and in Situ Aircraft

This study aimed to assess tropical cloud properties predicted by Environment and Climate Change Canada’s Global Environmental Multiscale (GEM)modelwhen run with the Milbrandt–Yau double-moment cloud microphysical scheme and one-way nesting that culminated at a (∼300 km)2 inner domain with 0.25 km horizontal grid spacing. The assessment utilized satellite and in situ data collected during the High Ice Water Content (HIWC) and High Altitude Ice Crystals (HAIC) projects for a mesoscale convective system on 16May 2015 over French Guiana.Data fromCloud- Sat’s cloud-profiling radar and GOES-13’s imager were compared to data either simulated directly by GEM or produced by operating on GEM’s cloud data with both the CFMIP (Cloud Feedback Model Intercomparison Project) Observation Simulator Package (COSP) instrument simulator and a three-dimensional Monte Carlo solar radiative transfer model. In situ observations were made from research aircraft – Canada’s National Research Council Convair-580 and the French SAFIRE Falcon-20 – whose flight paths were aligned with CloudSat’s ground-track. Spatial and temporal shifts of clouds simulated by GEM compared well to GOES-13 imagery. There are, however, differences between simulated and observed amounts of high and low cloud. While GEM did well at predicting ranges of ice-water content (IWC) near 11 km altitude (Falcon-20), it produces too much graupel and snow near 7 km (Convair-580). This produced large differences between CloudSat’s and COSP-generated radar reflectivities and two-way attenuations. On the other hand, CloudSat’s inferred values of IWC agree well with in situ samples at both altitudes. Generally, GEM’s visible reflectances exceeded GOES-13’s on account of having produced too much low-level liquid cloud. It is expected that GEM’s disproportioning of cloud hydrometeors will improve once it includes a better representation of secondary ice production.

Qu, Zhipeng↗

Application of finite element techniques in predicting the acoustic properties of turbofan inlets

An analytical technique was developed for predicting the acoustic performance of turbofan inlets carrying a subsonic axisymmetric steady flow. The finite element method combined with the method of weighted residuals is used in predicting the acoustic properties of variable area, annular ducts with or without acoustic treatments along their walls. An approximate solution for the steady inviscid flow field is obtained using an integral method for calculating the incompressible potential flow field in the inlet with a correction to account for compressibility effects. The accuracy of the finite element technique was assessed by comparison with available analytical solutions for the problems of plane and spinning wave propagation through a hard walled annular cylinder with a constant mean flow.

Majjigi, R. K.↗

A Stochastic Model of Space-Time Variability of Mesoscale Rainfall: Statistics of Spatial Averages

A characteristic feature of rainfall statistics is that they depend on the space and time scales over which rain data are averaged. A previously developed spectral model of rain statistics that is designed to capture this property, predicts power law scaling behavior for the second moment statistics of area-averaged rain rate on the averaging length scale L as L right arrow 0. In the present work a more efficient method of estimating the model parameters is presented, and used to fit the model to the statistics of area-averaged rain rate derived from gridded radar precipitation data from TOGA COARE. Statistical properties of the data and the model predictions are compared over a wide range of averaging scales. An extension of the spectral model scaling relations to describe the dependence of the average fraction of grid boxes within an area containing nonzero rain (the "rainy area fraction") on the grid scale L is also explored.

Kundu, Prasun K.↗

Morphology of Arabidopsis grown under chronic centrifugation and on the clinostat

Morphological measurements were made on populations of Arabidopsis thaliana grown from seed for 21 days under essentially constant environmental conditions except for the influence of gravitational or centrifugal accelerations. Growth conditions were what had been proposed for experiments in an artificial satellite. Observations are reported for plants grown at normal 1-g upright or on horizontal clinostats and for plants grown on a centrifuge. Increased g-force, up to 15 times normal, was found to have significant but small effects on some morphological end points. The plants' sensitivity to the magnitude of the g-force was much less than to its vector direction. Data from centrifuge experiments were extrapolated to zero-g to predict a set of morphological characteristics of a plant developing in the satellite environment. As an alternative means of predicting properties of a zero-g plant, characteristics of plants grown on horizontal clinostats were measured. The results of these two predictive methods were not in agreement. Clinostat grown plants were morphologically distinct from upright stationary controls.

Brown, A. H.↗

Prediction of ECS and SSC Models for Flux-Limited Samples of Gamma-Ray Blazars

The external Compton scattering (ECS) and synchrotron self-Compton (SSC) models make distinct predictions for the amount of Doppler boosting of high-energy gamma-rays emitted by Nazar. We examine how these differences affect the predicted properties of active galactic nucleus (AGN) samples selected on the basis of Murray emission. We create simulated flux-limited samples based on the ECS and SSC models, and compare their properties to those of identified EGRET blazars. We find that for small gamma-ray-selected samples, the two models make very similar predictions, and cannot be reliably distinguished. This is primarily due to the fact that not only the Doppler factor, but also the cosmological distance and intrinsic luminosity play a role in determining whether an AGN is included in a flux-limited gamma-ray sample.

Lister, Matthew L.↗

High-Throughput Strategies that Encompass Experiments and Machine Learning to Predict the Mechanical Properties of Additive Manufactured Aerospace Alloys

Small Punch Test (SPT) uses a thin disk of material to predict mechanical properties. While SPT has existed for decades, it has been used largely as a qualitative evaluator of mechanical properties. Recent advances in computational modeling have enabled the extraction of uniaxial stress-strain response from the measured SPT load-displacement data. Due to small sample volumes and unidirectional testing, SPT is conducive to high-throughput automation and ideally suited to extract properties from high-cost materials. Aerospace alloys have been of recent interest to the Additive Manufacturing (AM) community due to AM’s unique ability to fabricate complex designs not possible, or extremely arduous, with conventional manufacturing. In this research, SPT, coupled with Materials Informatics and computational modeling, is used to develop relevant Process-Structure-Property relationships to decrease the cost and time of process optimization for AM aerospace alloys, namely Inconel 718, Inconel 625, and Niobium C103.

High-throughput Testing↗