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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
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Variable magnification glancing incidence x ray telescope

A multispectral glancing incidence x ray telescope is disclosed, which capable of broadband, high resolution imaging of solar and stellar x ray and extreme ultraviolet radiation sources includes a primary optical system which focuses the incoming radiation to a primary focus. Two or more ellipsoidal mirrors are positioned behind the primary focus at an inclination to the optical axis, each mirror having a concave surface coated with a multilayer synthetic microstructure coating to reflect a desired wavelength. The ellipsoidal mirrors are segments of respective ellipsoids having a common first focus coincident with the primary focus. A detector such as an x ray sensitive photographic film is positioned at the second focus of each of the ellipsoids so that each of the ellipsoidal mirrors may reflect the image at the first focus to the detector. In one embodiment the mirrors are inclined at different angles and has its respective second focus at a different location, separate detectors being located at the respective second focus. The mirrors are arranged so that the magnification and field of view differ, and a solenoid activated arm may withdraw at least one mirror from the beam to select the mirror upon which the beam is to impinge so that selected magnifications and fields of view may be detected.

Hoover, Richard↗
DOE OSTI2026

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects the microstructural descriptors used in structure-property-processing relationships. A critical challenge is that high-resolution microscopy images (10,000×10,000 pixels) must be tiled for deep learning analysis, fragmenting fibers at boundaries. We demonstrate that segmentation method proves crucial for measurement accuracy. For example, instance segmentation with Slicing Aided Hyper Inference (SAHI) preserves individual fiber integrity across tiles while semantic segmentation prioritizes speed. Comparing against manual measurement of extracted carbon fibers, YOLOv11-SAHI matched manual ground truth (238 μm weighted mean) with 40x speedup (4.5 vs 167 minutes per image). U-Net provides rapid quantification although it is at the cost of reduced accuracy due only reliably measuring stand-alone fibers. Our comparative analysis reveals that instance segmentation with SAHI better preserves length measurements while semantic segmentation prioritizes speed, providing empirical guidance for method selection. The characterization provides essential inputs for mechanical property prediction models and inverse design workflows, accelerating composite materials development cycles.

Additive manufacturing↗
NASA NTRS2005

Unraveling the Material Processing Conditions for Optimizing FSW Process

In friction stir welding (FSW), a rotating threaded pin tool is inserted into a weld seam and literally stirs the edges of the seam together. This environmentally friendly, solid-state technique has been successfully used in the joining of materials that are difficult to fusion weld. To determine optimal processing parameters for producing a defect free weld a better understanding of the resulting metal deformation flow path and velocity is required. In this study the metal flow fields are marked by the use of thin (0.001? tungsten) wires embedded in the weld seam at various locations. X-ray radiographs record the position and segmentation of the wire and are used to elucidate the flow field. Microstructures observed in a FSW cross-section in an aluminum alloy are related to their respective strain-strain rate-temperature histories along their respective flow trajectories. Two kinds of trajectories, each subjecting the weld metal to a distinct thermomechanical process and imparting a distinct microstructure, can be differentiated within the weld structure.

Schneider, Judy↗
NASA NTRS2005

Quantifying the Material Processing Conditions for an Optimized FSW Process

In friction stir welding (FSW), a rotating threaded pin tool is inserted into a weld seam and literally stirs the edgs of the seam together. This environmentally friendly, solid-state technique has been successfully used in the joining of materials that are difficult to fusion weld. To determine optimal processing parameters for producing a defect free weld, a better understanding of the resulting metal deformation flow path and velocity is required. In this study the metal flow fields are marked by the use of thin (0.001 in. tungsten) wires embedded in the weld seam at various locations. X-ray radiographs record the position and segmentation of the wire and are used to elucidate the flow field. Microstructures observed in a FSW cross-section in an aluminum alloy are related to their respective strain-strain rate-temperature histones along their respective flow trajectories. Two kinds of trajectories, each subjecting the weld metal to a distinct thermomechanical process and imparting a distinct microstructure, can be differentiated within the weld structure.

Schneider, Judy↗
NASA NTRS2000

A New High Efficiency Segmented Thermoelectric Unicouple

To achieve high thermal-to-electric energy conversion efficiency, it is desirable to operate thermoelectric generator devices over large temperature gradients and also to maximize the thermoelectric performance of the materials used to build the devices. However, no single thermoelectric material is suitable for use over a very wide range of temperatures (approx. 300 - 1000 K). It is therefore necessary to use different materials in each temperature range where they possess optimum performance. This can be achieved in two ways: 1) multistage thermoelectric generators where each stage operates over a fixed temperature difference and is electrically insulated but thermally in contact with the other stages and 2) segmented generators where the p- and n-legs are formed of different segments joined in series. The concept of integrating new thermoelectric materials developed at the Jet Propulsion Laboratory (JPL) into a segmented thermoelectric generator has been presented in detail in earlier publications . This new generator is expected to operate over a 300-973 K temperature difference and will use novel segmented legs based on a combination of state-of-the-art thermoelectric materials and novel p-type Zn4Sb3, p-type CeFe4Sb12-based alloys and n-type CoSb3-based alloys. An increase in the conversion efficiency of about 60% is expected compared to conventional Bi2Te3- and PbTe-based generators. We present in this paper the latest experimental results from the bonding studies between the different segments of the p-legs, n-legs, and p-leg to n-leg interconnect. Evaluation of the bond quality was done by measuring the contact resistance across the joints as well as by detailed microstructure investigations to reveal any potential interdiffusion. Among the materials investigated as inter-layers between the different segments of the legs, Pd-Ag joining alloys have been found to provide mechanically stable and low electrical resistance bonds.

Caillat, T.↗
DOE OSTI2025

PyCMG-based Simulation of Volumetric Concrete Microstructure

Concrete is a complex, heterogeneous material with a microstructure composed of aggregates, cement paste, and pores spanning multiple length scales. Understanding this microstructure is critical for advancing the performance, durability, and modeling of concrete-based systems. While experimental imaging such as X-ray computed tomography (XCT) provides valuable insights, generating large datasets with detailed ground truth annotations is both costly and labor-intensive due to challenges in segmenting similar phases, such as aggregates and cement paste, that often share similar attenuation properties. To address this, we developed a pipeline to simulate realistic 3D concrete microstructures using the open-source Python package PyCMG. This simulation effort focuses on generating high-fidelity, annotated microstructures that can serve as training or benchmarking datasets for image analysis, segmentation algorithms, and machine learning models, particularly in scenarios where experimental data is scarce.

Ziabari, Amir [Oak Ridge National Laboratory; ORNL↗
NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

Introduction The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗
NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗
DOE OSTI2022

A novel approach for tetrahedral-element-based finite element simulations of anisotropic hyperelastic intervertebral disc behavior

Intervertebral discs are microstructurally complex spinal tissues that add greatly to the flexibility and mechanical strength of the human spine. Attempting to provide an adjustable basis for capturing a wide range of mechanical characteristics and to better address known challenges of numerical modeling of the disc, we present a robust finite-element-based model formulation for spinal segments in a hyperelastic framework using tetrahedral elements. We evaluate the model stability and accuracy using numerical simulations, with particular attention to the degenerated intervertebral discs and their likely skewed and narrowed geometry. To this end, 1) annulus fibrosus is modeled as a fiber-reinforced Mooney-Rivlin type solid for numerical analysis. 2) An adaptive state-variable dependent explicit time step is proposed and utilized here as a computationally efficient alternative to theoretical estimates. 3) Tetrahedral-element-based FE models for spinal segments under various loading conditions are evaluated for their use in robust numerical simulations. For flexion, extension, lateral bending, and axial rotation load cases, numerical simulations reveal that a suitable framework based on tetrahedral elements can provide greater stability and flexibility concerning geometrical meshing over commonly employed hexahedral-element-based ones for representation and study of spinal segments in various stages of degeneration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Multimodal Few-Shot Segmentation of Electron Micrographs

Scanning transmission electron microscopy (STEM) is one of the most used methods of analyzing the chemistry and composition of materials. By analyzing microstructures, these microscopes can help scientists better understand the molecular underpinnings of microelectronics, batteries, and more. However, STEM data can be difficult to interpret, so recent developments have been made in applications of machine learning to analyze these images. The PNNL-developed pyCHIP Classifier has achieved results in segmenting STEM these images via few-shot learning, a method which requires little data and human input, perfect for quickly analysis. In my internship I (Eli Meyers) investigated a multimodal improvement of this classifier by incorporating energy dispersive x-ray spectroscopy (EDS) data into the classification process for a more accurate segmentation. Furthermore, I encoded the spectral data by training a mass spectrometry encoder on the EDS data to extract a more meaningful representation of the data.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A physically based mechanical model for Mullins effect in thermoplastic polyurethanes

Despite decades of research, connecting the chemical and physical structure of thermoplastic polyurethanes to their mechanical properties remains highly challenging. Of particular note are their large-deformation and rate-dependent behaviors, which vary greatly with molecular chemistry, including the type and relative content of soft and hard segments. In this work, we develop a physically motivated mechanical theory for predicting the behavior of thermoplastic polyurethanes. The theory incorporates a representation of microstructural evolution during mechanical deformation, which captures the signatures of stress softening over cyclic loading (commonly referred to as the Mullins effect). There are only eight physically motivated fitting parameters, including a direct dependence on the hard segment fraction. The model predicts that increasing the hard segment fraction leads to higher stiffness and greater energy dissipation, in quantitative agreement with published experimental data. Furthermore, we provide a comprehensive analysis of the model and validate its predictions across several independent datasets focused on mechanical characterization. Direct comparisons to experimental data demonstrate its predictive capability on the effect of loading rate, cyclic deformations, and applied tension or compression. Altogether, this work establishes a predictive framework that connects polymer chemistry and microstructure to emergent mechanical behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Methods development towards automated, physics-informed, quantitative quality control of TRISO-SiC

Tristructural-isotropic (TRISO) fuel particles have been developed as a high-performance fuel for use in high-temperature gas-cooled reactor (HTGR) systems due to their high efficiency and stability under both normal and off-normal conditions. Broader deployment of this technology in advanced nuclear applications may benefit from quantitative quality assurance and quality control (QA/QC) methods that directly link TRISO properties to downstream performance. A key TRISO property is the SiC layer microstructure, which influences fission product retention during irradiation. However, existing QA/QC for the TRISO-SiC microstructure comprises only a qualitative visual inspection; therefore, there is a clear opportunity for the development of quantitative methods for TRISO QA/QC. Here, to this end, previous work has demonstrated an image processing approach to grain boundary (GB) identification and subsequent extraction of microstructural metrics; however, extensive twinning within the SiC layer complicates such analyses because twin GBs significantly influence microstructural metrics but are not expected to contribute to fission product transport. This study presents the initial development, training, and testing of an ML-based image segmentation algorithm designed to identify and remove twin GBs from standard backscattered electron micrographs, providing an industrially applicable, quantitative, and physically meaningful QA/QC approach for the TRISO-SiC microstructure. Although pixel-wise performance metrics for the twin predictions are low, the change in grain area and the number of GB pixels after twin removal predicted by the ML workflow are within 1% of the true values calculated using crystallographic data. This suggests that the model is well capable of predicting overall twin boundary structures and grain morphology, and continued advancement of this approach could enable automated, scalable, and physics-informed QA/QC for TRISO-SiC microstructures, supporting the reliable qualification of coated particle fuels for next-generation reactor systems.

Computer vision↗
NASA NTRS1992

Multispectral variable magnification glancing incidence x ray telescope

A multispectral, variable magnification, glancing incidence, x-ray telescope capable of broadband, high resolution imaging of solar and stellar x-ray and extreme ultraviolet radiation sources is discussed. The telescope includes a primary optical system which focuses the incoming radiation to a primary focus. Two or more rotatable mirror carriers, each providing a different magnification, are positioned behind the primary focus at an inclination to the optical axis. Each carrier has a series of ellipsoidal mirrors, and each mirror has a concave surface covered with a multilayer (layered synthetic microstructure) coating to reflect a different desired wavelength. The mirrors of both carriers are segments of ellipsoids having a common first focus coincident with the primary focus. A detector such as an x-ray sensitive photographic film is positioned at the second respective focus of each mirror so that each mirror may reflect the image at the first focus to the detector at the second focus. The carriers are selectively rotated to position a selected mirror for receiving radiation from the primary optical system, and at least the first carrier may be withdrawn from the path of the radiation to permit a selected mirror on the second carrier to receive the radiation.

Hoover, Richard B.↗
DOE OSTI2024

A mesoscale 3D model of irradiated concrete informed via a 2.5 U-Net semantic segmentation

The concrete biological shield in light-water reactors is exposed to neutron and gamma irradiation, which deteriorates the concrete’s mechanical properties in the long term. To assess the irradiation-induced damage, predictive mechanical models are developed and used in parallel with the characterization of irradiated concrete samples. Realistic 3D simulation domains can drastically improve a model’s prediction. In this work, we utilized x-ray computed tomography (XCT) data of a concrete specimen to reconstruct its 3D microstructure. The XCT data shows low contrast between the concrete’s aggregates and cement paste, resulting in poor image segmentation when using traditional unsupervised techniques. To address this issue, we developed and trained a 2.5D U-Net model on only 24 pre-labeled XCT layers to segment 651 layers of the XCT data. The overall F1-score of the model is approximately 96%. Then, we created a 3D finite element (FE) mesh based on the stack of segmented images. The FE model contains radiation-induced expansion, damage, and creep. The constitutive equations are adapted to each phase (aggregates and cement paste). Here, we simulated the effects of neutron irradiation in the concrete specimen as well as the specimen’s mechanical response to uniaxial compression. Finally, model validation was performed using experimental data on similar concrete specimens in the literature.

2.5D U-Net↗
DOE OSTI2025

Examining Constituent Redistribution in U-19Pu-10Zr Fuel as it Evolves with Local Burnup

While constituent redistribution is a known irradiation behavior in U-Pu-Zr fuel, new data have shown it is more complex than our current understanding and predictive capabilities. The size and composition of redistributed rings evolve as a function of pin composition, burnup, geometry, and irradiation temperature. In this work, we extract microstructural information from optical microscopy conducted on U-19Pu-10Zr pins (irradiated between 1.9 at. % and 11.6 at. % peak burnup). Both manual image analysis techniques and machine learning-assisted segmentation are used to quantify the thicknesses of the cladding, fuel-cladding interaction layers, and rings of fuel constituent redistribution in addition to pore distribution. These microstructural features and individual redistributed regions affect local thermomechanical properties, and identifying the relationship between burnup and constituent redistribution will improve accurate prediction of advanced reactor fuel performance.

Constituent Redistribution↗
DOE OSTI2023

Structural complexity of γ-Al 2 O 3 : The nature of vacancy ordering and the structure of complex antiphase boundaries

The structure of γ-Al2O3 remains largely undetermined despite decades of research. This is due to the high degree of disorder, which poses significant challenges for structural analysis using conventional crystallographic approaches. Herein, we study the structure of γ-Al2O3 with Scanning Transmission Electron Microscopy (STEM) and ab-initio calculations to provide a complete structural description. We show that the microstructure can be understood in terms of two key structural features of nanoscale spinel domains and finite thickness segments termed as complex antiphase boundaries (cAPB) that provide the domain interconnectivity. The spinel domains have a distinctive preference for vacancy ordering, which can be rationalized in terms of a structure with a stacking disorder. Tetragonal P4 1 2 1 2 or monoclinic P2 1 models, all based on the identical motif, can be considered as representative ordered forms. Individual spinel domains are interconnected via cAPBs, which adopt a distinct non-spinel bonding environment of δ-Al 2 O 3 . The most common cAPB consists of a single delta motif with thickness of just 0.6 nm on (001), with the resulting displacement a/4 [101]. Remarkably, the cAPBs are shown to energetically stabilize the spinel domains of γ-Al 2 O 3 explaining their high abundance. We demonstrate how the tetragonal distortions naturally arise in this intricate microstructure and place the proposed model in the context of phase transformations to high temperature transition aluminas.

36 MATERIALS SCIENCE↗
NASA NTRS2015

NASA's Nuclear Thermal Propulsion Project

Space fission power systems can provide a power rich environment anywhere in the solar system, independent of available sunlight. Space fission propulsion offers the potential for enabling rapid, affordable access to any point in the solar system. One type of space fission propulsion is Nuclear Thermal Propulsion (NTP). NTP systems operate by using a fission reactor to heat hydrogen to very high temperature (>2500 K) and expanding the hot hydrogen through a supersonic nozzle. First generation NTP systems are designed to have an Isp of approximately 900 s. The high Isp of NTP enables rapid crew transfer to destinations such as Mars, and can also help reduce mission cost, improve logistics (fewer launches), and provide other benefits. However, for NTP systems to be utilized they must be affordable and viable to develop. NASA's Advanced Exploration Systems (AES) NTP project is a technology development project that will help assess the affordability and viability of NTP. Early work has included fabrication of representative graphite composite fuel element segments, coating of representative graphite composite fuel element segments, fabrication of representative cermet fuel element segments, and testing of fuel element segments in the Compact Fuel Element Environmental Tester (CFEET). Near-term activities will include testing approximately 16" fuel element segments in the Nuclear Thermal Rocket Element Environmental Simulator (NTREES), and ongoing research into improving fuel microstructure and coatings. In addition to recapturing fuels technology, affordable development, qualification, and utilization strategies must be devised. Options such as using low-enriched uranium (LEU) instead of highly-enriched uranium (HEU) are being assessed, although that option requires development of a key technology before it can be applied to NTP in the thrust range of interest. Ground test facilities will be required, especially if NTP is to be used in conjunction with high value or crewed missions. There are potential options for either modifying existing facilities or constructing new ground test facilities. At least three potential options exist for reducing (or eliminating) the release of radioactivity into the environment during ground testing. These include fully containing the NTP exhaust during the ground test, scrubbing the exhaust, or utilizing an existing borehole at the Nevada National Security Site (NNSS) to filter the exhaust. Finally, the project is considering the potential for an early flight demonstration of an engine very similar to one that could be used to support human Mars or other ambitious missions. The flight demonstration could be an important step towards the eventual utilization of NTP.

Houts, Michael↗
NASA NTRS1993

Liquid crystalline order in mucus

Mucus plays an exceptionally wide range of important biological roles. It operates as a protective, exchange, and transport medium in the digestive, respiratory, and reproductive systems of humans and other vertebrates. Mucus is a polymer hydrogel. It is secreted as discrete packages (secretory granules) by specialized secretory cells. Mucus hydrogel is stored in a condensed state inside the secretory granules. Depending upon the architecture of their constituent macromolecules and on the composition of the solvent, polymer gels can form liquid crystalline microstructures, with orientational order being exhibited over optically resolvable distances. Individual mucin molecules consist of alternating rigid segments (heavily glycosylated; hydrophilic) and flexible segments (nonglycosylated; hydrophobic). Polymer molecules consisting of rigid units linked by flexible spacers are frequently associated with liquid crystalline behavior, which again raises the possibility that mucus could form anisotropic fluid phases. Suggestions that mucins may be self-associating in dilute solution have previously been challenged on the basis of sedimentation-equilibrium studies performed on mucus in which potential sites of association were competitively blocked with inhibitors. However, the formation of stable liquid crystalline phases does not depend on the existence of inter- or intramolecular associations; these phases can form on the basis of steric considerations alone.

NASA Discipline Number 40-20↗