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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
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Prediction of natural frequency variability due to uncertainty in material properties

Composite materials are widely used in various types of modern engineering structures. Traditional studies on composite structures have been based on the assumption that the material properties of the composites are characterized by a priori known elastic moduli, and no uncertainties of these moduli have been considered. However, the composite materials are invariably subject to a certain amount of scatter in their measured elastic moduli. To a large extent, the properties of composite materials are dependent on the fabrication process. But even the composite materials manufactured by the same process demonstrate differences in their elastic properties. This paper proposes a new, non-probabilistic method to predict the variability in the natural frequencies of the composite cylindrical shell, resulting from the unavoidable scatter in elastic moduli. The available measurements of elastic moduli are fitted by the four-dimensional uncertainty ellipsoid. The upper and lower bounds of the natural frequency are derived. With these bounds, designers will have a better understanding of the real dynamic behavior of the structure.

Li, Y. W.↗
NASA NTRS1984

Materials properties data base computerization

Material property data plays a key role in the design of jet engine components. Consistency, accuracy and efficient use of material property data is of prime importance to the engineering community. The system conception, development, implementation, and future plans for computer software that captures the Material Properties Handbook into a scientific data base are described. The engineering community is given access to raw data and property curves, display of multiple curves for material evaluation and selection, direct access by design analysis computer programs, display of the material specification, and a historical repository for the material evolution. The impact of this activity includes significant productivity gains and cost reductions; all users have access to the same information nd provides consistent, rapid response to the needs of the engineering community. Future plans include incorporating the materials properties data base into a network environment to access information from other data bases and download information to engineering work stations.

Baur, R. G.↗
NASA NTRS2001

Upgrades to the TPSX Material Properties Database

The TPSX Material Properties Database is a web-based tool that serves as a database for properties of advanced thermal protection materials. TPSX provides an easy user interface for retrieving material property information in a variety of forms, both graphical and text. The primary purpose and advantage of TPSX is to maintain a high quality source of often used thermal protection material properties in a convenient, easily accessible form, for distribution to government and aerospace industry communities. Last year a major upgrade to the TPSX web site was completed. This year, through the efforts of researchers at several NASA centers, the Office of the Chief Engineer awarded funds to update and expand the databases in TPSX. The FY01 effort focuses on updating correcting the Ames and Johnson thermal protection materials databases. In this session we will summarize the improvements made to the web site last year, report on the status of the on-going database updates, describe the planned upgrades for FY02 and FY03, and provide a demonstration of TPSX.

Squire, T. H.↗
DOE OSTI2026

Coupling Microstructural Evolution Simulations to Material Property Degradation Predictions for Plasma-Facing Materials

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗
NASA NTRS1985

Design of test specimens and procedures for generating material properties of Douglas fir/epoxy laminated wood composite material: With the generation of baseline data at two environmental conditions

In support of the design of wind turbine generator airfoils/blades utilizing Douglas Fir/West System Epoxy laminated composite material, a program was undertaken to define pertinent material properties utilizing small scale test specimens. Task 1 was the development of suitable monotonic tension, compression, short beam shear and full reversed cyclic specimen designs and the companion grips and testing procedures. Task 2 was the generation of the material properties at two environmental conditions utilizing the specimens and procedures developed in Task 1. The monotonic specimens and procedures generated results which compare favorably with other investigators while the cyclic results appear somewhat conservative. Adding moisture and heat or scarf joints degraded the monotonic performance but had a more nebulus effect with cyclic loading.

Johnson, Paul E.↗
NASA NTRS1983

Effects of long duration exposure to simulated space environment on nonmetallic materials properties

Nonmetallic materials specimens from the Viking program were tested in situ invacuo after continuous thermal vacuum exposure from 1971/1972 to the present. Eleven tests were done on appropriate specimens of 30 materials; however, no single material received all the tests. Some specimens also were exposed to 1 or 2.5 MeV electrons at differing fluences before testing. Baseline exposure data is reported for graphite/epoxy specimens that were exposed to vacuum since 1974. These materials were transferred to the thermal vacuum storage facility for future in situ testing and irradiation. Thin G/E specimens were tensile tested after thermal-vacuum cycling exposure. Photomicrographic examinations and SEM analyses were done on the failed specimens.

Peacock, C. L., Jr.↗
DOE OSTI2025

Adaptive Interface-PINNs (AdaI-PINNs) for inverse problems: Determining material properties for heterogeneous systems

Here, we determine spatially varying discontinuous material properties using a domain-decomposition based physics-informed neural networks (PINNs) framework named the Adaptive Interface-PINNs or AdaI-PINNs (Roy et al., 2024). We propose the use of distinct neural networks for the field variables and material properties within each material, utilizing adaptive activation functions. While the neural networks across different materials share the same weights and biases, their activation functions are uniquely tailored using a hyperparameter that influences the slope of the activation function. The proposed framework is tested on several one-dimensional and two-dimensional benchmark examples, and its performance is compared with conventional PINNs and existing domain-decomposition PINNs frameworks, namely, the Multi-domain physics-informed neural network (M-PINN), and the eXtended physics-informed neural networks (XPINNs). The results demonstrate that the proposed approach can determine randomly distributed discontinuous material properties with an L 2 error of $\mathscr{O}$ (10 -3 ) for the material property and the root-mean-square error of $\mathscr{O}$ (10 -3 ) for the primary variable while the other approaches yield errors that are approximately two orders of magnitude larger (that is, $\mathscr{O}$ (10 -1 )). Moreover, the spatial distribution of material properties obtained using the proposed framework is in close agreement with the true distribution, whereas the other approaches fare much worse. Additionally, the proposed approach is approximately 40% faster than its competitors, indicating its potential as a robust alternative for solving inverse problems in heterogeneous materials.

36 MATERIALS SCIENCE↗
NASA NTRS2024

Space Nuclear Propulsion (SNP) Material Property Handbook

The National Aeronautics and Space Administration’s (NASA’s) Space Nuclear Propulsion (SNP) project aims to demonstrate the feasibility of nuclear thermal propulsion (NTP) as a thrust mechanism for spacecraft. An initial Demonstration Rocket for Agile Cislunar Operations (DRACO) launch will serve as a test of the technology in Earth’s orbit. Future work may involve the development of an NTP engine and spacecraft design with the capability to transport astronauts from Earth to Mars and back safely, though NTP has other potential uses too.

Nuclear Thermal Propulsion↗
NASA NTRS1972

A study of the effect of selected material properties on the ablation performance of artificial graphite

Eighteen material properties were measured on 45 different, commercially available, artificial graphites. Ablation performance of these same graphites were also measured in a Mach 2 airstream at a stagnation pressure of 5.6 atm. Correlations were developed, where possible, between pairs of the material properties. Multiple regression equations were then formulated relating ablation performance to the various material properties, thus identifying those material properties having the strongest effect on ablation performance. These regression equations reveal that ablation performance in the present test environment depends primarily on maximum grain size, density, ash content, thermal conductivity, and mean pore radius. For optimization of ablation performance, grain size should be small, ash content low, density and thermal conductivity high, and mean pore radius large.

Maahs, H. G.↗
NASA NTRS2012

A Statistics-Based Material Property Analysis to Support TPS Characterization

Accurate characterization of entry capsule heat shield material properties is a critical component in modeling and simulating Thermal Protection System (TPS) response in a prescribed aerothermal environment. The thermal decomposition of the TPS material during the pyrolysis and charring processes is poorly characterized and typically results in large uncertainties in material properties as inputs for ablation models. These material property uncertainties contribute to large design margins on flight systems and cloud re- construction efforts for data collected during flight and ground testing, making revision to existing models for entry systems more challenging. The analysis presented in this work quantifies how material property uncertainties propagate through an ablation model and guides an experimental test regimen aimed at reducing these uncertainties and characterizing the dependencies between properties in the virgin and charred states for a Phenolic Impregnated Carbon Ablator (PICA) based TPS. A sensitivity analysis identifies how the high-fidelity model behaves in the expected flight environment, while a Monte Carlo based uncertainty propagation strategy is used to quantify the expected spread in the in-depth temperature response of the TPS. An examination of how perturbations to the input probability density functions affect output temperature statistics is accomplished using a Kriging response surface of the high-fidelity model. Simulations are based on capsule configuration and aerothermal environments expected during the Mars Science Laboratory (MSL) entry sequence. We identify and rank primary sources of uncertainty from material properties in a flight-relevant environment, show the dependence on spatial orientation and in-depth location on those uncertainty contributors, and quantify how sensitive the expected results are.

Copeland, Sean R.↗
NASA NTRS1968

Material Properties Measurements for Selected Materials

Hugoniot equation of state measurements were made on Coconino sandstone, Vacaville basalt, Kaibab limestone, Mono Crater, pumice and Zelux (a polycarbonate resin) for pressures to 2 Mb. A single data point was obtained for fused quartz at 1.6 Mb. In addition to the hugoniot studies, the uniaxial compressive stress behavior of Vacaville basalt and Zelux was investigated at strain rates from about 10(exp -5)/sec to 10(exp 3)/second. The data presented include the stress - strain relations as a function of strain rate for these two materials.

Green, S. J.↗
NASA NTRS1972

Determination of the effects of graphite material properties on ablation performance.

Application of statistical methods to the problem of identifying those material properties of artificial graphite having the strongest effect on ablation performance. Ablation performance, as determined by total length change during test, recession rate, surface temperature, surface texture, and degree of gouging, was measured on 40 different, commercially available, artificial graphites in a Mach 2 airstream having a nominal enthalpy of 2.2 MJ/kg and a stagnation pressure of 5.6 atm. Eighteen material properties were measured on these same graphites, and correlations between pairs of these material properties were developed where possible, reducing the original 18 properties to ten mutually independent properties. Multiple regression equations were formulated relating ablation performance to the reduced set of ten independent material properties, thereby identifying those material properties having the most pronounced effect on ablation performance. These regression equations reveal that for optimum ablation performance in the present environment, grain size should be small, ash content low, density and thermal conductivity high, and mean pore radius large.

Maahs, H. G.↗
NASA NTRSDate not supplied

Stochastic Reconstruction of Thermal Protection Material Properties from Arc-Jet Experiments

Material response models are used to assess reliability using variances in the bond-line temperature predictions based on uncertainties in trajectory, aerothermal environment, and material properties. A key deficiency in the current approach is that input uncertainties are too often subjective, empirical, or ad-hoc, and are not rigorously linked to the arc-jet test data used to develop the TPS material model. While materials such as PICA are well understood, future missions may require more novel materials such as HEEET where unknown uncertainties have real consequences on the ability to assess reliability. A quantifiable estimate of reliability requires an iterative methodology where the parameters driving the variance in bond-line temperature (for example) are systematically identified. A test campaign to collect data or develop new models can then be identified to reduce those input uncertainties. A Bayesian inference loop defines these connections mathematically, i.e., prior knowledge about uncertainty is updated based on observation. While these concepts are well known (and often applied intuitively in a non-rigorous approach), only recent advances in reduced-order modelling have made them computationally viable methods for engineering. By replacing deterministic inverse methods with stochastic approaches, the hope is new materials proposed for future missions can more rapidly be developed with a greater understanding of the TPS material reliability. Two additional steps for the analysis of arc jet test data are discussed. The first is ability to construct a reduced-order model using material response simulations (Icarus/US3D) of the arc-jet test articles, and the second is the inclusion of this surrogate model in the Bayesian inversion process. Both capabilities will be demonstrated using prior PICA arc-jet test data. The quality of a surrogate model will be investigated and the variances on the calibrated material properties will be compared to our current understanding of the PICA material model.

Material response↗
NASA NTRS1990

Real-time measurement of materials properties at high temperatures by laser produced plasmas

Determination of elemental composition and thermophysical properties of materials at high temperatures, as visualized in the context of containerless materials processing in a microgravity environment, presents a variety of unusual requirements owing to the thermal hazards and interferences from electromagnetic control fields. In addition, such information is intended for process control applications and thus the measurements must be real time in nature. A new technique is described which was developed for real time, in-situ determination of the elemental composition of molten metallic alloys such as specialty steel. The technique is based on time-resolved spectroscopy of a laser produced plasma (LPP) plume resulting from the interaction of a giant laser pulse with a material target. The sensitivity and precision were demonstrated to be comparable to, or better than, the conventional methods of analysis which are applicable only to post-mortem specimens sampled from a molten metal pool. The LPP technique can be applied widely to other materials composition analysis applications. The LPP technique is extremely information rich and therefore provides opportunities for extracting other physical properties in addition to the materials composition. The case in point is that it is possible to determine thermophysical properties of the target materials at high temperatures by monitoring generation and transport of acoustic pulses as well as a number of other fluid-dynamic processes triggered by the LPP event. By manipulation of the scaling properties of the laser-matter interaction, many different kinds of flow events, ranging from shock waves to surface waves to flow induced instabilities, can be generated in a controllable manner. Time-resolved detection of these events can lead to such thermophysical quantities as volume and shear viscosities, thermal conductivity, specific heat, mass density, and others.

Kim, Yong W.↗
NASA NTRS2015

Analytic Thermoelectric Couple Modeling: Variable Material Properties and Transient Operation

To gain a deeper understanding of the operation of a thermoelectric couple a set of analytic solutions have been derived for a variable material property couple and a transient couple. Using an analytic approach, as opposed to commonly used numerical techniques, results in a set of useful design guidelines. These guidelines can serve as useful starting conditions for further numerical studies, or can serve as design rules for lab built couples. The analytic modeling considers two cases and accounts for 1) material properties which vary with temperature and 2) transient operation of a couple. The variable material property case was handled by means of an asymptotic expansion, which allows for insight into the influence of temperature dependence on different material properties. The variable property work demonstrated the important fact that materials with identical average Figure of Merits can lead to different conversion efficiencies due to temperature dependence of the properties. The transient couple was investigated through a Greens function approach; several transient boundary conditions were investigated. The transient work introduces several new design considerations which are not captured by the classic steady state analysis. The work helps to assist in designing couples for optimal performance, and also helps assist in material selection.

Seebeck Effect↗
DOE OSTI2025

Extracting Material Property Measurements from Scientific Literature with Limited Annotations

Extracting material property data from scientific text is pivotal for advancing data-driven research in chemistry and materials science; however, the extensive annotation effort required to produce training data for named entity recognition (NER) models for this task often makes it a barrier to extracting specialized data sets. Here, in this work, we present a comparative study of the conventional, supervised NER methodology to alternative few-shot learning architectures and large language model (LLM)-based approaches that mitigate the need to label large training data sets. We find that the best-performing LLM (GPT-4o) not only excels in directly extracting relevant material properties based on limited examples but also enhances supervised learning through data augmentation. We supplement our findings with error and data quality assessments to provide a nuanced understanding of factors that impact property measurement extraction.

36 MATERIALS SCIENCE↗