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Results for “Processing and Properties”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Optical-data-processing properties of a liquid-crystal television spatial light modulator

The potential of an extremely inexpensive liquid-crystal television (LCTV) as a two-dimensional spatial light modulator has been investigated. The LCTV modulates the transmission of coherent or incoherent light and can either be electronically addressed through a microcomputer or optically addressed with a TV camera. The transmission characteristics of the device have been measured, its diffraction pattern is examined, and its use as an input device for an optical correlator is tested. It is discovered that, with proper modifications, it has potential for optical-data-processing applications.

Liu, H.-K.↗
NASA NTRS1985

Characterization of the relationship of the cure cycle chemistry to cure cycle processing properties

Dynamic dielectric analysis (DDA) is used to study curing polymer systems and thermoplastics. Measurements are made over a frequency range of six decades. This wide range of frequencies increases the amount of information which can be obtained. The data is analyzed in terms of the frequency dependence of the complex permittivity epsilon sup *, specific conductivity sigma (ohm/cm) and the relaxation time tau, parameters which are characteristic of the cure state of the material and independent of the size of the sample.

Kranbuehl, D. E.↗
DOE OSTI2022

Sparse Data Machine Learning Integration with Theory, Experiment and Uncertainty Quantification: Process-Structure-Property-Performance of Friction Deformation Processing

Computer vision and deep learning tools that advance the ability to establish processing-structure-property-performance (PSPP) relations are presented. The Bayesian binning method for image segmentation enables quantitative analysis of microstructural features in an automated way, while the analysis of shapes and relative orientation of these features reveals local deformation maps indicative of both, material flow and residual stresses due to materials processing. The deep learning method leads to the previous knowledge agnostic mapping of empirically observed microstructural zones in friction stir welding (FSW) process and synthetic microstructure generation capability that is statistically equivalent to experimentally collected data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Development of high temperature containerless processing equipment and the design and evaluation of associated systems required for microgravity materials processing and property measurements

The development of high temperature containerless processing equipment and the design and evaluation of associated systems required for microgravity materials processing and property measurements are discussed. Efforts were directed towards the following task areas: design and development of a High Temperature Acoustic Levitator (HAL) for containerless processing and property measurements at high temperatures; testing of the HAL module to establish this technology for use as a positioning device for microgravity uses; construction and evaluation of a brassboard hot wall Acoustic Levitation Furnace; construction and evaluation of a noncontact temperature measurement (NCTM) system based on AGEMA thermal imaging camera; construction of a prototype Division of Amplitude Polarimetric Pyrometer for NCTM of levitated specimens; evaluation of and recommendations for techniques to control contamination in containerless materials processing chambers; and evaluation of techniques for heating specimens to high temperatures for containerless materials experimentation.

Rey, Charles A.↗
NASA NTRS1991

Particle properties and processes in Uranus' rings

The particle properties and processes in the Uranian rings are analyzed from Voyager observations and ground-based data. Occultation observations of the epsilon ring are interpreted to yield an effective size of the ring particles that exceeds 70 cm, a surface mass density that exceeds 80 g/sq cm, and a ring vertical thickness greater than tens of meters for solid ice particles. The particles forming the classic rings are dark and gray, with albedo of 0.014 +/-0.004. It is argued that the small amount of dust that exists in the classical rings and between the rings in bands is created by erosion of ring particles and unseen satellites resulting from collisions and micrometeoroid bombardment. As proposed for regions of the other known ring systems, new ring material can be continually created by the destruction of small moons near the rings, which may explain the youthful appearance of the Uranian rings.

Esposito, L. W.↗
NASA NTRS1996

Processing and Properties of Fiber Reinforced Polymeric Matrix Composites: Processing Robustness of IM7/PETI Polyimide Composites - Part 2

The processability of a phenylethynyl terminated imide (PETI) resin matrix composite was investigated. Unidirectional prepregs were made by coating an N-methylpyrrolidone solution of the amide acid oligomer onto unsized IM7. Two batches of prepregs were used: one was made by NASA in-house, and the other was from an industrial source. The composite processing robustness was investigated with respect to the effect of B-staging conditions, the prepreg shelf life, and the optimal processing window. Rheological measurements indicated that PETI's processability was only slightly affected over a wide range of B-staging temperatures (from 250 C to 300 C). The open hole compression (OHC) strength values were statistically indistinguishable among specimens consolidated using various B-staging conditions. Prepreg rheology and OHC strengths were also found not to be affected by prolonged (i.e., up to 60 days) ambient storage. An optimal processing window was established using response surface methodology. It was found that IM7/PETI composite is more sensitive to the consolidation temperature than to the consolidation pressure. A good consolidation was achievable at 371 C/100 Psi, which yielded an OHC strength of 62 Ksi at room temperature. However, processability declined dramatically at temperatures below 350 C.

Hou, Tan-Hung↗
DOE OSTI2022

Understanding the role of segmentation on process-structure–property predictions made via machine learning

Here, the present study investigated the effect of porosity surface determination methods on performance of machine learning models used to predict the tensile properties of AlSi10Mg processed by laser powder bed fusion from micro-computed tomography data. Machine learning models applied in this work include support vector machines, neural networks, decision trees, and Bayesian classifiers. The effects of isosurface thresholding and local gradient approaches for porosity segmentation, as well as image filtering schemes, on model precision were evaluated for samples produced under differing levels of global energy density.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Navigating high-dimensional process-structure–property relations in nanocrystalline Pt-Au alloys with machine learning

For decades, materials scientists have relied on the process-structure–property paradigm to guide investigations into material behaviors. Traditional studies often examine a limited number of process-structure–property variables, striving to elucidate mechanisms governing material response. However, this approach is time consuming and can limit exploration, as well as the discovery of process-structure–property relations in novel materials. In this paper, we combined combinatorial sputter deposition and multi-modal high-throughput materials characterization with feedforward neural networks to establish high-dimensional process-structure–property relations in Pt-Au alloys, yielding nanocrystalline alloys with high hardness and low resistivity relevant to electrical contact switch applications. We mapped three indicators of process conditions (composition and two atomic deposition characteristics) onto four indicators of material structure (X-ray diffraction, film thickness, density, and surface roughness) and two indicators of material properties (hardness and resistivity), resulting in 784 unique combinations evaluated over a 13-dimensional space. The neural networks predicted Pt-Au alloys with 18–24 at.% Au, when deposited at specific conditions, to have a nanoindentation hardness up to 7.2 GPa. This high hardness value, comparable to some steels, represents a 3-fold improvement in hardness over “hard gold”, a commonly used electrical contact alloy, while maintaining requisite electrical conductivity. The neural network models provide an avenue to identify expected process windows capable of maximizing material performance.

Electrical contact materials↗
NASA NTRSDate not supplied

Integrated Process-Structure-Property Simulations for Additive Manufacturing Using the Open-Source Materialite Package

The microstructure and properties of additively manufactured (AM) metals are strongly dependent on process conditions. Therefore, process-structure-property (PSP) simulations are a useful tool for exploring process parameter space, studying process variations, and quantifying uncertainty in material properties. However, integrating process-structure and structure-property simulations often involves connecting multiple software packages. Each package may use unique data structures and require substantial domain knowledge. This presentation demonstrates PSP simulation capabilities of Materialite, an open-source package developed at NASA Langley Research Center. Materialite simplifies model linkages by using a common data structure and model interface, enabling straightforward simulation across a PSP model chain. Physics-based models, including kinetic Monte Carlo and crystal plasticity, are implemented within the package. The model interface is also intended to simplify implementation of new models and enable integration with external simulation tools. Example use cases include uncertainty quantification with PSP models and GPU-accelerated powder bed fusion AM process models.

additive manufacturing↗
NASA NTRSDate not supplied

Uncertainty Quantification and Sensitivity Analysis in Process-Structure-Property Simulations for Laser Powder Bed Fusion Additive Manufacturing

Process variations and process-induced defects like porosity cause significant uncertainty in the microstructure and mechanical behavior of additively manufactured metals. Establishing process-structure-property (PSP) relationships and quantifying uncertainty using experiments alone is costly, especially for structural applications where mechanical allowables must be established for qualification and certification. This work presents a PSP simulation framework for laser powder bed fusion with a focus on uncertainty quantification through probabilistic calibration and multi-fidelity uncertainty propagation. Motivated by phenomenological input parameters related to grain nucleation and growth that are difficult to characterize, a global sensitivity analysis (GSA) is completed. Through GSA, the most important input parameters are identified based on their influence on the statistical distributions of microstructural metrics that influence mechanical behavior, including grain size, morphology, and crystallographic texture. The results provide insight on what experiments are necessary to quantify and control PSP uncertainties, particularly those associated with the more challenging input parameters.

additive manufacturing↗
NASA NTRS1988

Experiments on the formation, properties and processing of cosmic dust

The results from various experiments on the formation, properties, and processing of potential silicate components of cosmic dust are reviewed. Consideration is given to the role of evaporation and condensation in grain formation, nucleation experiments using volatile compounds and refractory species, and efforts to produce particles that might represent cosmic grains. Other studies include particle scattering experiments, studies on the growth of clusters, the sputtering process, the impact of temperature on sputtering yield and optical properties, and experimental and theoretical studies of the structure of particulate aggregates.

Donn, B. D.↗
DOE OSTI2023

Exploring the process-structure-property relationship of Aerosol Deposition to phosphor coatings for non-contact thermometry

Full-field, multi-measurand diagnostics provide rich validation data necessary to improve the product life cycle time of nuclear safety components. Thermophosphor digital image correlation (TP+DIC) is a method of simultaneously measuring strain and temperature fields using patterned phosphor coatings deposited with aerosol deposition (AD). While TP+DIC produces a functional diagnostic, the coating’s reproducibility and the effect of the patterned features on the inferred temperature remains uncharacterized. This NSR&D project provided the opportunity to study two areas: 1) the tunability and repeatability of aerosol deposition and 2) the robustness of aerosol deposition phosphor on deforming substrates. The first area explores the process-property relationship of parameters elucidating the significance of each on the coating. The second area explores the relationship between the features’ characteristics (namely thickness) and the phosphor emission and inferred temperature. Together, the results will lead to the improved accuracy and functionality of TP+DIC for qualification testing of nuclear safety components.

36 MATERIALS SCIENCE↗
NASA NTRS1982

Develop, demonstrate, and verify large area composite structural bonding with polyimide adhesives

The technology required to produce graphite-polyimide structural components with operational capability at 598 K (600 F) is considered. A series of polyimide adhesives was screened for mechanical and physical properties and processibility in fabricating large midplane bonded panels and honeycomb sandwich panels in an effort to fabricate a structural test component of the space shuttle aft body flap. From 41 formulations, LaRC-13, FM34B-18, and a modified LaRC-13 adhesive were selected for further evaluation. The LaRC-13 adhesive was rated as the best of the three adhesives in terms of availability, cost, processibility, properties, and ability to produce void fee large area (12" x 12") midplane bonds. Surface treatments and primers for the adhesives were evaluated and processes were developed for the fabrication of honeycomb sandwich panels of very good quality which was evidenced by rupture in the honeycomb core rather than in the facesheet bands on flatwise tensile strength testing. The fabrication of the adhesively bonded honeycomb sandwich cover panels, ribs, and leading edge covers of Celion graphite/LARC-160 polyimide laminates is described.

Bhombal, B. D.↗
NASA NTRS2026

Changes in Arctic and Antarctic Sea-Ice Properties and Processes

Although sea ice covers ~9% of the world’s oceans, its presence, and absence, vastly alter the energetic balance of Earth’s climate. Because of geographic differences, Arctic and Antarctic sea ice have different dominant properties and processes, which produce different responses to natural variability and anthropogenic change. In this Review, we survey changes in sea-ice properties and processes of the Arctic and Antarctic environments. In the Arctic, the melt season has lengthened by ~7.4 days decade −1 (1979-2024). There has been a corresponding decrease in winter sea-ice thickness (1.6 m mean total over 1980-2023), summer surface albedo (0.03 decade −1 over 1979-2020), and spring snow depth (2.5 cm decade −1 over 1954-2024). In comparison, corresponding changes in the Antarctic are small overall due to contrasting regional and temporal trends. From a dynamic perspective, sea-ice motion in both hemispheres has increased, with 0.63 cm s −1 decade −1 in the Arctic (1978-2024) and 0.69 cm s −1 decade −1 in the Antarctic (1982-2024), whereas trends in polynya occurrence differ by region. Future research should prioritize sea-ice observations that can inform how the climate system responds to natural variability and anthropogenic change, be standardized to increase uptake by the broader scientific community, and target process-oriented interactions to support model development.

Melinda A Webster↗