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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 19 records

A comparison of arcjet plume properties to model predictions

This paper describes an experimental study of the plasma plume properties of a 1 kW class hydrogen arcjet thruster and the comparison of measured temperature and velocity field to model predictions. The experiments are based on laser-induced fluorescence excitation of the Balmer-alpha transition. The model is based on a single-fluid magnetohydrodynamic description of the flow originally developed to predict arcjet thruster performance. Excellent agreement between model predictions and experimental velocity is found, despite the complex nature of the flow. Measured and predicted exit plane temperatures are in disagreement by as much as 2000K over a range of operating conditions. The possible sources for this discrepancy are discussed.

Cappelli, M. A.↗

A predictive model for failure properties of thermoset resins

A predictive model for the three-dimensional failure behavior of engineering polymers has been developed in a recent NASA-sponsored research program. This model acknowledges the underlying molecular deformation mechanisms and thus accounts for the effects of different chemical compositions, crosslink density, functionality of the curing agent, etc., on the complete nonlinear stress-strain response including yield. The material parameters required by the model can be determined from test-tube quantities of a new resin in only a few days. Thus, we can obtain a first-order prediction of the applicability of a new resin for an advanced aerospace application without synthesizing the large quantities of material needed for failure testing. This technology will effect order-of-magnitude reductions in the time and expense required to develop new engineering polymers.

Caruthers, James M.↗

Comparison of Multiscale Method of Cells-Based Models for Predicting Elastic Properties of Filament Wound C/C-SiC

Three different multiscale models, based on the method of cells (generalized and high fidelity) micromechanics models were developed and used to predict the elastic properties of C/C-SiC composites. In particular, the following multiscale modeling strategies were employed: Concurrent multiscale modeling of all phases using the generalized method of cells, synergistic (two-way coupling in space) multiscale modeling with the generalized method of cells, and hierarchical (one-way coupling in space) multiscale modeling with the high fidelity generalized method of cells. The three models are validated against data from a hierarchical multiscale finite element model in the literature for a repeating unit cell of C/C-SiC. Furthermore, the multiscale models are used in conjunction with classical lamination theory to predict the stiffness of C/C-SiC plates manufactured via a wet filament winding and liquid silicon infiltration process recently developed by the German Aerospace Institute.

multiscale modeling↗

A Model for Predicting Thermoelectric Properties of Bi2Te3

A parameterized orthogonal tight-binding mathematical model of the quantum electronic structure of the bismuth telluride molecule has been devised for use in conjunction with a semiclassical transport model in predicting the thermoelectric properties of doped bismuth telluride. This model is expected to be useful in designing and analyzing Bi2Te3 thermoelectric devices, including ones that contain such nano - structures as quantum wells and wires. In addition, the understanding gained in the use of this model can be expected to lead to the development of better models that could be useful for developing other thermoelectric materials and devices having enhanced thermoelectric properties. Bi2Te3 is one of the best bulk thermoelectric materials and is widely used in commercial thermoelectric devices. Most prior theoretical studies of the thermoelectric properties of Bi2Te3 have involved either continuum models or ab-initio models. Continuum models are computationally very efficient, but do not account for atomic-level effects. Ab-initio models are atomistic by definition, but do not scale well in that computation times increase excessively with increasing numbers of atoms. The present tight-binding model bridges the gap between the well-scalable but non-atomistic continuum models and the atomistic but poorly scalable ab-initio models: The present tight-binding model is atomistic, yet also computationally efficient because of the reduced (relative to an ab-initio model) number of basis orbitals and flexible parameterization of the Hamiltonian.

Lee, Seungwon↗

Geometrical modelling of textile reinforcements

The mechanical properties of textile composites are dictated by the arrangement of yarns contained within the material. Thus, to develop a comprehensive understanding of the performance of these materials, it is necessary to develop a geometrical model of the fabric structure. This task is quite complex, as the fabric is made from highly flexible yarn systems which experience a certain degree of compressibility. Furthermore there are tremendous forces acting on the fabric during densification typically resulting in yarn displacement and misorientation. The objective of this work is to develop a methodology for characterizing the geometry of yarns within a fabric structure including experimental techniques for evaluating these models. Furthermore, some applications of these geometric results to mechanical property predictions models are demonstrated.

Pastore, Christopher M.↗

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↗

Improving the Effectiveness of Integral Property Calculation in a CSG Solid Modeling System by Exploiting Predictability

Integral property calculation is an important application for solid modeling systems. Algorithms for computing integral properties for various solid representation schemes are fairly well known. It is important to deigners and users of solid modeling systems to understand the behavior of such algorithms. Specifically the trade-off between execution time and accuracy is critical to effective use of integral property calculation. The average behavior of two algorithms for Constructive Solid Geometry (CSG) representations is investigated. Experimental results from the PADL-2 solid modeling system show that coarse decompositions can be used to predict execution time and error estimates for finer decompositions. Exploiting this predictability allow effective use of the algorithms in a solid modeling system.

Clark, A. L.↗

A Comparison of Different Modeling Strategies for Predicting Effective Properties of 3D Woven Composites

Three-dimensional (3D) woven composites are an attractive means of achieving superior mechanical performance in aerospace structures. Limited analysis capability currently exists to predict both effective elastic and strength properties for these complex composites. In this study, a comparison of three modeling strategies was performed to assess the ability of the different methods to predict the effective elastic properties of four distinct 3D orthogonal woven composites. Two finite element techniques (in-plane and triply-periodic boundary conditions) and one method of cells technique, the Multiscale Generalized Method of Cells, were considered.

Ricks, Trenton M.↗

An evaluation of string theory for the prediction of dynamic tire properties using scale model aircraft tires

The string theory was evaluated for predicting lateral tire dynamic properties as obtained from scaled model tests. The experimental data and string theory predictions are in generally good agreement using lateral stiffness and relaxation length values obtained from the static or slowly rolling tire. The results indicate that lateral forces and self-aligning torques are linearly proportional to tire lateral stiffness and to the amplitude of either steer or lateral displacement. In addition, the results show that the ratio of input excitation frequency to road speed is the proper independent variable by which frequency should be measured.

Clark, S. K.↗

The effect of interface properties on nickel base alloy composites

This program was performed to assess the extent to which mechanical behavior models can predict the properties of sapphire fiber/nickel aluminide matrix composites and help guide their development by defining improved combinations of matrix and interface coating. The program consisted of four tasks: 1) selection of the matrices and interface coating constituents using a modeling-based approach; 2) fabrication of the selected materials; 3) testing and evaluation of the materials; and 4) evaluation of the behavior models to develop recommendations. Ni-50Al and Ni-20AI-30Fe (a/o) matrices were selected which gave brittle and ductile behavior, respectively, and an interface coating of PVD YSZ was selected which provided strong bonding to the sapphire fiber. Significant fiber damage and strength loss was observed in the composites which made straightforward comparison of properties with models difficult. Nevertheless, the models selected generally provided property predictions which agreed well with results when fiber degradation was incorporated. The presence of a strong interface bond was felt to be detrimental in the NiAI MMC system where low toughness and low strength were observed.

Groves, M.↗

Microstructure Quantification and Random Forest Regression Models for Li4Ti5O12–Ni Property Prediction

All-solid-state structural lithium-ion batteries are sought to enable all-electric propulsion in next generation aerospace concepts through improved safety and systems level weight savings. In this work, the influence of processing conditions on microstructural evolution was evaluated for anode composites of strain-free Li4Ti5O12 and metallic nickel current collector. Beyond size distributions, this study explored methods of quantifying microstructural features that describe changes in the spatial distribution and coalescence of nickel particles as a function of sample composition and sintering conditions. Processing-microstructure-property relationships were described by microstructure quantifiers including nickel particle count per area, nearest neighbor distance distribution, and edge-to-edge distance distribution. Machine learning methods were applied to compare the relative influence of processing conditions and microstructural features on electrical conductivity and mechanical strength to optimize for simultaneous energy storage and load bearing performance. Insights gained from this work inform future evaluation of alternative energy storage materials and microstructures for multifunctional performance, and generation of microstructural descriptors strengthens modeling across length scales.

anode↗

The inertial properties of the body and its segments

Mass distribution properties of the adult human body are summarized. The summary is user-oriented for design engineers and mathematical modeling. Properties are dicussed in terms of the musculoskeletal linkage system, axes systems, mass, volume, center of mass, and inertial properties. Data and prediction equations or coefficients for modeling these properties are provided. Predictive formulas use total body weight and stature as independent variables. The data are based on small samples of living and cadaveric subjects typical of the white European male.

Reynolds, H. M.↗

A Particle and Energy Balance Model of the Orificed Hollow Cathode

A particle and energy balance model of orificed hollow cathodes was developed to assist in cathode design. The model presented here is an ensemble of original work by the author and previous work by others. The processes in the orifice region are considered to be one of the primary drivers in determining cathode performance, since the current density was greatest in this volume (up to 1.6 x 10(exp 8) A/m2). The orifice model contains comparatively few free parameters, and its results are used to bound the free parameters for the insert model. Next, the insert region model is presented. The sensitivity of the results to the free parameters is assessed, and variation of the free parameters in the orifice dominates the calculated power consumption and plasma properties. The model predictions are compared to data from a low-current orificed hollow cathode. The predicted power consumption exceeds the experimental results. Estimates of the plasma properties in the insert region overlap Langmuir probe data, and the predicted orifice plasma suggests the presence of one or more double layers. Finally, the model is used to examine the operation of higher current cathodes.

Domonkos, Matthew T.↗

High Temperature Material Property Data and Challenges to Thermal Process Model Predictions and In-Situ/Ex-Situ Measurements for Metallic Additive Manufacturing

Understanding and predicting performance properties of parts produced by metallic additive manufacturing has improved significantly over the past decade; however, difficult to measure material properties and process outcomes continue to be challenges. The qualification or certification of aerospace parts require extensive measures to quantify variable part properties in order to buy down the risk of component failure. The variability, inherent to the additive manufacturing, process adds unwanted uncertainty in the production of load critical structural components. Process modeling has proven valuable in providing predictions and context for understanding outcomes of the additive manufacturing process; however, these physically informed process models require material properties at temperatures that are difficult to measure and rarely available. Further, calibrating or validating such models is difficult because the process itself is challenging to measure. This talk will explore some of the challenges resulting from difficult to acquire input data by relating thermal process model predictions to in-situ and ex-situ optical microscopy measurements.

Process Model↗

Uncertainty Quantification of Classical Theories of Dendritic Growth Kinetics Applied to Nickel-Based Alloys

The solidification velocity in a model nickel-alloy single crystal during laser spot melting was recently characterized using synchrotron X-ray imaging. The measured solidification velocity was found to exceed the absolute stability threshold predicted by the Kurz-Giovanola-Trivedi (KGT) model. The discrepancies between the model and experiments motivate the further assessment of accurate material properties. This work quantifies the impact material property uncertainty has on model predictions of the absolute stability threshold velocities. Properties from the literature are reviewed and compared to those calculated using computational thermodynamics to provide uncertainty estimates on input properties to the KGT model. Global sensitivity analysis is used to quantify the influence of each uncertain input property on the predicted threshold velocity. This work supports the understanding of the nickel-alloy solidification during powder bed fusion additive manufacturing and identifies the solidification material properties that are the most important to assess from first-principles computations and experiments.

Computational thermodynamics↗

Multiphysics Modeling for Dimensional Analysis of a Self-Heated Molten Regolith Electrolysis Reactor for Oxygen and Metals Production on the Moon and Mars

The technology of direct electrolysis of molten lunar regolith to produce oxygen and molten metal alloys has progressed greatly in the last few years. The development of long-lasting inert anodes and cathode designs as well as techniques for the removal of molten products from the reactor has been demonstrated. The containment of chemically aggressive oxide and metal melts is very difficult at the operating temperatures ca 1600 C. Containing the molten oxides in a regolith shell can solve this technical issue and can be achieved by designing a self-heating reactor in which the electrolytic currents generate enough Joule heat to create a molten bath. In a first phase, a thermal analysis model was built to study the formation of a melt of lunar basaltic regolith irradiated by a focused solar beam This mode of heating was selected because it relies on radiative heat transfer, which is the dominant mode of transfer of energy in melts at 1600 C. Knowing and setting the Gaussian-type heat flux from the concentrated solar beam and the phase and temperature dependent thermal properties, the model predicts the dimensions and temperature profile of the melt. A validation of the model is presented in this paper through the experimental formation of a spherical cap melt realized by others. The Orbitec/PSI experimental setup uses an 3.6-cm diameter concentrated solar beam to create a hemispheric melt in a bed of lunar regolith simulant contained in a large pot. Upon cooling, the dimensions of the vitrified melt are measured to validate the thermal model. In a second phase, the model is augmented by multiphysics components to compute the passage of electrical currents between electrodes inserted in the molten regolith. The current through the melt generates Joule heating due to the high resistivity of the medium and this energy is transferred into the melt by conduction, convection and primarily by radiation. The model faces challenges in two major areas, the change of phase as temperature increases, and the dominance of radiative heat flux as heat transfer mechanism within the melt the change of phase concerns the regolith itself which is present in states ranging from a fine grain regolith with low thermal conductivity and low density to a vitrified melt with much higher thermal conductivity, and higher density. As the regolith is heated, it starts to soften around 1300 C the melt iS very viscous and evolving gas bubbles out in thick, lava-like fashion. By 1600 C the regolith is completely melted and the viscosity is low The second challenge resides in the proper modeling of the radiative heat flux requiring the addition of the computing-demanding radiative-heat-transfer function to the general heat transfer equation. The model Includes temperature-dependent properties (density, thermal conductivity, heat capacity, and viscosity, and absorption coefficients) and solves the radiative heat flux equation assuming gray (fine grains) and semi-transparent (melt) media and using an absorption coefficient spectral found in the literature for terrestrial minerals similar in composition to those of lunar regolith simulant

Dominguez, Jesus A.↗

Evaluation of ceramics for stator application: Gas turbine engine report

Current ceramic materials, component fabrication processes, and reliability prediction capability for ceramic stators in an automotive gas turbine engine environment are assessed. Simulated engine duty cycle testing of stators conducted at temperatures up to 1093 C is discussed. Materials evaluated are SiC and Si3N4 fabricated from two near-net-shape processes: slip casting and injection molding. Stators for durability cycle evaluation and test specimens for material property characterization, and reliability prediction model prepared to predict stator performance in the simulated engine environment are considered. The status and description of the work performed for the reliability prediction modeling, stator fabrication, material property characterization, and ceramic stator evaluation efforts are reported.

Trela, W.↗

Distant magnetotails of the outer magnetic planets

The distant planetary magnetotails of Jupiter, Saturn, Uranus, and Neptune are assumed to be partially open, hot, long plasma cavities generally in pressure equilibrium with the solar wind. Most of the magnetosheath magnetic field lines drape around the magnetotails. Conservation of momentum density, magnetic field, plasma density, and energy density fluxes are invoked at the tail boundaries to determine the shape of the magnetotails and the variations of plasma and magnetic field characteristics with distance down the magnetotail. Voyager observations are used to initialize calculations in the near-planet portions of each magnetotail. Estimates of magnetotail cross sections, magnetic field strengths, and plasma densities are described as a function of downstream distance. The model accurately predicts properties of the Jovian magnetotail at least as far as Saturn's orbit.

Macek, W. M.↗