SEARCH · Engineering Papers

Results for “3D image processing”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 685 records · Page 38

All sources NASA NTRS DOE OSTI

DOE OSTI2018

Multiphase Model of Semisolid Slurry Generation and Isothermal Holding During Cooling Slope Rheoprocessing of A356 Al Alloy

In the present paper, we present an experimentally validated 3D multiphase and multiscale solidification model to understand the transport processes involved during slurry generation with a cooling slope. In this process, superheated liquid alloy is poured at the top of the cooling slope and allowed to flow along the slope under the influence of gravity. As the melt flows down the slope, it progressively loses its superheat, starts solidifying at the melt/slope interface with formation of solid crystals, and eventually exits the slope as semisolid slurry. In the present simulation, the three phases considered are the parent melt as the primary phase, and the solid grains and air as secondary phases. The air phase forms a definable air/liquid melt interface as the free surface. After exiting the slope, the slurry fills an isothermal holding bath maintained at the slope exit temperature, which promotes further globularization of microstructure. The outcomes of the present model include prediction of volume fractions of the three different phases considered, grain evolution, grain growth, size, sphericity and distribution of solid grains, temperature field, velocity field, macrosegregation and microsegregation. In addition, the model is found to be capable of making predictions of morphological evolution of primary grains at the onset of isothermal coarsening. The results obtained from the present simulations are validated by performing quantitative image analysis of micrographs of the rapidly oil-quenched semisolid slurry samples, collected from strategic locations along the slope and from the isothermal slurry holding bath.

36 MATERIALS SCIENCE↗

DOE OSTI2024

High redshift LBGs from deep broadband imaging for future spectroscopic surveys

Lyman break galaxies (LBGs) are promising probes for clustering measurements at high redshift, z > 2, a region only covered so far by Lyman-α forest measurements. Here, in this paper, we investigate the feasibility of selecting LBGs by exploiting the existence of a strong deficit of flux shortward of the Lyman limit, due to various absorption processes along the line of sight. The target selection relies on deep imaging data from the HSC and CLAUDS surveys in the g, r, z and u bands, respectively, with median depths reaching 27 AB in all bands. The selections were validated by several dedicated spectroscopic observation campaigns with DESI. Visual inspection of spectra has enabled us to develop an automated spectroscopic typing and redshift estimation algorithm specific to LBGs. Based on these data and tools, we assess the efficiency and purity of target selections optimised for different purposes. Selections providing a wide redshift coverage retain 57% of the observed targets after spectroscopic confirmation with DESI, and provide an efficiency for LBGs of 83 ± 3%, for a purity of the selected LBG sample of 90 ± 2%. This would deliver a confirmed LBG density of ~ 620 deg$^{-2}$ in the range 2.3 < z < 3.5 for a r-band limiting magnitude r < 24.2. Selections optimised for high redshift efficiency retain 73% of the observed targets after spectroscopic confirmation, with 89 ± 4% efficiency for 97 ± 2% purity. This would provide a confirmed LBG density of ~ 470 deg$^{-2}$ in the range 2.8 < z < 3.5 for a r-band limiting magnitude r < 24.5.A preliminary study of the LBG sample 3d-clustering properties is also presented and used to estimate the LBG linear bias. A value of b$_{LBG}$ = 3.3 ± 0.2 (stat.) is obtained for a mean redshift of 2.9 and a limiting magnitude in r of 24.2, in agreement with results reported in the literature.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Geometric Interpretation of the Cluster Location Problem Part II: Application to the Pahala, Hawaii, Earthquake Sequence

In the companion “Theory” article, we presented a new framing of the seismic location problem in terms of differential geometry (Harris et al., 2025). From that viewpoint, we developed a “project and correct” approach for estimating the relative locations of earthquakes. Here, in this study, we use project and correct to estimate high-precision relative locations of events from an earthquake sequence beneath the town of Pahala, Hawaii, using high-precision correlation-derived picks. The sequence was active from 2020 through 2022 and produced many highly correlated signals at Hawaii Volcano Observatory (HVO) stations on the island of Hawaii. The data we inverted consisted of 2882 events with observations at 5 HVO stations. For comparison with the travel-time image, we also produced conventional hypocenter solutions using both the Bayesloc program (Myers et al., 2007, 2009) and a purpose-built double-difference code. There were obvious structural elements in the resulting image, the resolution of which we used to test the performance of the project and the correct algorithm. For the projection step, we first produced a 3D local basis using an singular value decomposition (SVD) of the 2882 groups of times. Projection of the travel-time vectors into this basis resulted in an image with structures similar to those produced by our conventional locators, but with distortion as predicted by theory. Removing the distortion requires an inverse operator generated from the metric tensor at the geometric centroid of the events. We compared two approaches to obtaining such an inverse operator. The first uses an estimate of the geographic centroid of the event cloud from the centroid of the travel-time data. The second approach uses the centroid of the conventionally produced locations. The first approach produces a corrected image very similar to the conventional results, but with a rotation. The corrected image produced using the conventionally derived centroid is a near-exact match to the conventional locations.

Dodge, Douglas A. [Lawrence Livermore National Lab↗

NASA NTRS2014

3D Observation of GEMS by Electron Tomography

Amorphous silicates in chondritic porous interplanetary dust particles (CP-IDPs) coming from comets are dominated by glass with embedded metal and sulfides (GEMS). GEMS grains are submicron-sized rounded objects (typically 100-500) nm in diameter) with anaometer-sized (10-50 nm) Fe-Ni metal and sulfide grains embedded in an amorphous silicate matrix. Several formation processes for GEMS grains have been proposed so far, but these models are still being debated [2-5]. Bradley et al. proposed that GEMS grains are interstellar silicate dust that survived various metamorphism or alteration processes in the protoplanetary disk and that they are amorphiation products of crystalline silicates in the interstellar medium by sputter-deposition of cosmic ray irradiation, similar to space weathering [2,4]. This consideration is based on the observation of nano-sized crystals (approximately 10 nm) called relict grains in GEMS grains and their shapes are pseudomorphs to the host GEMS grains. On the other hand, Keller and Messenger proposed that most GEMS formed in the protoplanetary disk as condensates from high temperature gas [3,5]. This model is based on the fact that most GEMS grains have solar isotopic compositions and have extremely heterogeneous and non-solar elemental compositions. Keller and Messenger (2011) also reported that amorphous silicates in GEMS grains are surrounded by sulfide grains, which formed as sulfidization of metallic iron grains located on the GEMS surface. The previous studies were performed with 2D observation by using transmission electron microscopy (TEM) or scanning TEM (STEM). In order to understand the structure of GEMS grains described above more clearly, we observed 3D structure of GEMS grains by electron tomography using a TEM/STEM (JEM-2100F, JEOL) at Kyoto University. Electron tomography gives not only 3D structures but also gives higher spatial resolution (approximately a few nm) than that in conventional 2D image, which is restricted by sample thickness ) approx. or greater than 50 nm). Three cluster IDPs (L2036AA5 cluster4, L2009L8 cluster 13 and W726A2) were used for the observations. ID W726A2 was collected without silicon oil, which is ordinary used to collect IDPs, so this sample has no possibility of contaminations caused by silicon oil or solvent to rinse it [6]. The samples were embedded in epoxy risin and sliced into ultrathin sections (50-300 nm) using an ultramicotome. The sections were observed by BF-TEM and HAADF-STEM (high angle annular dark field-scanning TEM) modes. Images were obtained by rotating the sample tilt angle over a range of +/- 65 deg in 1 deg steps. The obtained images were reconstructed to slice images. Mineral phases in the slice images were estimated by comparing with a 2D elemental map obtained by an EDS (energy dispersive X-ray spectroscopy) system equipped in the TEM/STEM. Careful examination of the slice images confirmed that iron grains are embedded in the amorphous silicate matrix of the GEMS grains, but sulfide grains were mainly present on the surface of the amorphous silicate. These results are consistent with the model that GEMS grains formed as condensates [3,5], although more data are needed to conclude the origin of GEMS grains. The present study is the first successful example adapting the electron tomography to the IDPs. This type of analysis will be important for planetary material sciences in the future.

Matsuno, Junya↗

NASA NTRS2008

Dissemination and Use of NPOESS Data in AWIPS II

Real-time satellite information provides one of many data sources used by NWS forecast offices to diagnose current weather conditions and to assist in short-term forecast preparation. While GOES satellite data provides relatively coarse spatial resolution coverage of the continental U.S. on a 10-15 minute repeat cycle, polar orbiting data has the potential to provide snapshots of weather conditions at high-resolution in many spectral channels. The multispectral polar orbiting satellite capabilities allow for the derivation of image and sounding products not available from geostationary orbit. The utility of these polar orbiting measurements to forecasters has been demonstrated with NASA EOS observations as part of the Short-term Prediction and Research Transition (SPORT) program at Marshall Space Flight Center. SPORT scientists have been providing real-time MODIS data to NWS forecasters on an experimental basis to address a variety of short-term weather forecasting problems since 2003. The launch of the NPOESS Preparatory Project (NPP) satellite in 2009 will extend the continuity of high-resolution data provided by the NASA EOS satellites into future operational weather systems. The NPP data will be available in a timeframe consistent with the early installation of the next generation Advanced Weather Information Processing System (AWIPS) under development by Raytheon for the NWS. The AWIPS II system will be a JAVA-based decision support system which preserves the functionality of the existing systems and offers unique development opportunities for new data sources and applications in the Service Orientated Architecture (SOA) environment. The poster will highlight some of the advanced observing and display- capabilities of these new systems such as plug-ins for NASA and NPP datasets, and the development of local applications which are not well handled in the current AWIPS (e.g., 3D displays of LMA data, generation and display of 3-channel color composites, etc.).

Jedlovec, Gary↗

DOE OSTI2019

3D PRINTED LAYER OF POLYANILINE-BASED CONDUCTIVE POLYMER FOR LIGHTNING STRIKE PROTECTION OF CFRPS

Manufacturing of Carbon Fiber Reinforced Plastics (CFRPs) using additive manufacturing (AM), or 3D printing, has gained popularity in recent years. It is believed that the AM industry has the potential to manufacture CFRP parts in a faster, easier and more economical way. Lightning strike damage to CFRP parts is not rare; therefore, additional lightning strike protection (LSP) technologies are applied on top of CFRP structures. However, there is no report of manufacturing lightning strike protection (LSP) technologies using the AM process. In the present work, the authors applied an electrically conductive layer via additive manufacturing. The material of the electrically conductive layer was a Polyaniline (PANI)-filled thermoset composite. This layer of PANI was deposited on top of the CFRP panels. The PANI-coated CFRP panels were tested against a simulated lightning strike made of a continuous waveform with component A (100 kA), component B (2 kA) and component C (470 A). The highly conductive PANI-layer worked as a capable Faraday cage to safely dissipate the lightning current. In PANI-based LSP, direct contact between PANI chains dominated the conduction behavior, which proved to be a highly efficient way to reduce resistive heating from the incident current. However, poor adhesion between the printed layer and the substrate structure needs to be improved in the future. The results from the thermal camera and the high-speed camera images showed an effective current dissipation through the printed layers. Non-destructive ultrasonic imaging was done to confirm the direct lightning damages to samples. The present work shows that a non-metallic conductive layer can be applied as an LSP of CFRP structures via an additive manufacturing technique.

Kumar, Vipin↗

DOE OSTI2026

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗

DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗

NASA NTRSDate not supplied

Investigation of Lunar-Inspired Geopolymer Concrete Formulations Mixed and Cured in Microgravity on the International Space Station (ISS)

The research outlined in this presentation investigates the use of various lunar regolith simulants in geopolymer lunar concrete mixes mixed and cured on the International Space Station (ISS). The motivation for this work is to study the effects of gravity on the microstructure of alkali-activated materials cured with heat, and to develop materials for the construction of long-term infrastructure on the lunar surface with in-situ resource utilization (ISRU). ISRU for construction materials reduces the cost and mass of payloads related to lunar construction. The advantage of geopolymer concrete as opposed to traditional portland cement concrete is that water acts as a medium for the polymerization reaction and leaves the system throughout the process, reducing its demand. Twelve samples of lunar regolith simulant and a solution composed of sodium hydroxide and sodium silicate were sent to the ISS. The three simulants were OPRH2N, OPRL2N, and JSC-1AF, using only particles less than 53 µm in diameter to increase reactivity of the simulant. Simulant to solution ratios were determined by workability while mixing. The simulant and solution were sealed Burst Pouches® along with 2 other sealed bags to prevent material from leaking. Crew member F-14 conducted testing on the ISS by introducing the solution to the simulant in the Burst Pouch®, mixing the sample with a spatula, and then clamping the specimen in the fresh state to prevent flow inside the Burst Pouch®. These specimens were then put in a thermos heated to 80C via sealed drinking water bags to cure for 24 hours with a temperature logger. The cured specimens remained in microgravity for at least 28 days and were returned from the ISS in February 2025. The specimens were then brought to the NASA Marshall Space Flight Center (MSFC) to analyze. Material characterization consisted of conducting Micro-CT tests of entire samples in their sealed apparatus to a resolution of 25µm. 2D image slices were saved in each orthogonal direction of each specimen at a 0.03 mm step size from the 3D model to conduct analytical porosity calculations. Representative samples from each specimen were sampled to perform helium gas pycnometery and were then mounted in resin for SEM imaging, EDS, and nanoindentation. Porosity was analyzed analytically using micromechanics modelling with the assistance of the NASA Multiscale Analysis Tool (NASMAT), as well as the NASA Advanced Supercomputing (NAS) servers (V. Saseendran & N. Yamamoto, 2024). Density was measured using helium gas pycnometery and was then compared to the theoretical density for experimental porosity calculation. Due to the samples’ non-uniform shape being cured in a pouch, traditional compression and tensile strength testing could not be performed. Nanoindentation was conducted at Clarkson University to determine the microhardness and reduced modulus of elasticity. Results from flight samples can be compared to ground samples currently in DLR’s possession to determine the effect on microstructure from being mixed and cured in microgravity. This study gives further insight and understanding of geopolymer lunar concrete and its viability as a lunar construction material with ISRU.

Adam Johnson↗

DOE OSTI2019

Iterative Joint Ptychography-Tomography with Total Variation Regularization

In order to determine the 3D structure of a thick sample, researchers have recently combined ptychography (for high resolution) and tomography (for 3D imaging) in a single experiment. 2-step methods are usually adopted for reconstruction, where the ptychography and tomography problems are often solved independently. In this paper, we provide a novel model and ADMM-based algorithm to jointly solve the ptychography-tomography problem iteratively, also employing total variation regularization. The proposed method permits large scan stepsizes for the ptychography experiment, requiring less measurements and being more robust to noise with respect to other strategies, while achieving higher reconstruction quality results.

2-step methods↗

DOE OSTI2017

Early-stage reduction of the dendritic complexity in basolateral amygdala of a transgenic mouse model of Alzheimer's disease

Alzheimer's disease is a representative age-related neurodegenerative disease that could result in loss of memory and cognitive deficiency. However, the precise onset time of Alzheimer's disease affecting neuronal circuits and the mechanisms underlying the changes are not clearly known. To address the neuroanatomical changes during the early pathologic developing process, we acquired the neuronal morphological characterization of AD in APP/PS1 double-transgenic mice using the Micro-Optical Sectioning Tomography system. We reconstructed the neurons in 3D datasets with a resolution of 0.32 × 0.32 × 1 μm and used the Sholl method to analyze the anatomical characterization of the dendritic branches. The results showed that, similar to the progressive change in amyloid plaques, the number of dendritic branches were significantly decreased in 9-month-old mice. In addition, a distinct reduction of dendritic complexity occurred in third and fourth-order dendritic branches of 9-month-old mice, while no significant changes were identified in these parameters in 6-month-old mice. At the branch-level, the density distribution of dendritic arbors in the radial direction decreased in the range of 40–90 μm from the neuron soma in 6-month-old mice. These changes in the dendritic complexity suggest that these reductions contribute to the progressive cognitive impairment seen in APP/PS1 mice. This work may yield insights into the early changes in dendritic abnormality and its relevance to dysfunctional mechanisms of learning, memory and emotion in Alzheimer's disease. - Highlights: • Neuron-level, reduction of dendritic complexity in BLA of 9-month-old AD mice. • Specific range of branch decrease in density of 6-month-old AD mice. • 3D imaging with high resolution will provide insights into brain aging.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

High-speed x-ray phase contrast imaging and digital image correlation analysis of microscale shock response of an additively manufactured energetic material simulant

The performance of energetic materials subjected to dynamic loading significantly depends on their micro- and meso-scale structural morphology. The geometric versatility offered by additive manufacturing opens new pathways to tailor the performance of these materials. Additively manufactured energetic materials (AMEMs) have a wide range of structural characteristics with a hierarchy of length scales and process-inherent heterogeneities, which are hitherto difficult to precisely control. It is important to understand how these features affect AMEMs’ response under dynamic/shock loading. Therefore, temporally and spatially resolved measurements of both macroscopic behavior and micro- and meso-level processes influencing macroscopic behavior are required. In this paper, we analyze the shock compression response of an AMEM simulant loaded under several impact conditions and orientations. Furthermore, x-ray phase contrast imaging (PCI) is used to track features across the observed shock front and determine the linear shock velocity vs particle velocity equation of state, as well as to quantify the interior deformation fields via digital image correlation (DIC) analyses. Photon Doppler velocimetry is simultaneously used to measure the particle velocities of the specimens, which are consistent with those obtained from x-ray PCI. The DIC analyses provide an assessment of the average strain fields inside the material, showing that the average axial strain depends on the loading intensity and reaches as high as 0.23 for impact velocities up to 1.5 km/s. The overall results demonstrate the utility of x-ray PCI for probing “in-material” equation of state and interior strains associated with dynamic shock compression behavior of the AMEM simulant.

3D printing↗

DOE OSTI2022

A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media

Physical processes that occur within porous materials have wide-ranging applications including - but not limited to - carbon sequestration, battery technology, membranes, oil and gas, geothermal energy, nuclear waste disposal, water resource management. The equations that describe these physical processes have been studied extensively; however, approximating them numerically requires immense computational resources due to the complex behavior that arises from the geometrically-intricate solid boundary conditions in porous materials. Here, we introduce a new dataset of unprecedented scale and breadth, DRP-372: a catalog of 3D geometries, simulation results, and structural properties of samples hosted on the Digital Rocks Portal. The dataset includes 1736 flow and electrical simulation results on 217 samples, which required more than 500 core years of computation. This data can be used for many purposes, such as constructing empirical models, validating new simulation codes, and developing machine learning algorithms that closely match the extensive purely-physical simulation. This article offers a detailed description of the contents of the dataset including the data collection, simulation schemes, and data validation.

3D images↗

NASA NTRS2024

Three-Dimensional Atmospheric Dynamics of Jupiter from Ground-Based Doppler Imaging Spectroscopy in the Visible

We present three-dimensional (3D) maps of Jupiter’s atmospheric circulation at cloud-top level from Doppler-imaging data obtained in the visible domain with JIVE, the second node of the JOVIAL network, which is mounted on the Dunn Solar Telescope at Sunspot, New Mexico. We report on 12 nights of observations between May 4 and May 30, 2018, representing a total of about 80 hours. Firstly, the average zonal wind profile derived from our data is compatible with that derived from cloud-tracking measurements performed on Hubble Space Telescope images obtained in April 2018 from the Outer Planet Atmospheres Legacy (OPAL) program. Secondly, we present the first ever two-dimensional maps of Jupiter’s atmospheric circulation from Doppler measurements. The zonal velocity map highlights well-known atmospheric features, such as the equatorial hot spots and the Great Red Spot (GRS). In addition to zonal winds, we derive meridional and vertical velocity fields from the Doppler data. The motions attributed to vertical flows are mainly located at the boundary between the equatorial belts and tropical zones, which could indicate active motion in these regions. Qualitatively, these results compare well to recent Juno data that have unveiled the three-dimensional structure of Jupiter’s wind field. To the contrary, the motions attributed to meridional circulation are very different from what is obtained by cloud tracking, except at the GRS. Because of limitations with data resolution and processing techniques, we acknowledge that our measurement of vertical or meridional flows of Jupiter are still to be confirmed.

Francois-Xavier Schmider↗

DOE OSTI2022

Advances in physics and applications of 3D magnetic perturbations on the J-TEXT tokamak

In the last two years, three major technical improvements have been made on J-TEXT in supporting of the expanded operation regions and diagnostic capabilities. (1) The successful commission of the 105 GHz/500 kW/1 s electron cyclotron resonance heating (ECRH) system increasing the core electron temperature from 0.9 keV up to around 1.5 keV. (2) The poloidal divertor configuration with an X-point in the high-field side has been achieved. In particular, the 400 kW electron cyclotron wave has also been successfully injected into the diverted plasma. (3) A 256-channel electron cyclotron emission imaging diagnostic system and two sets of four-channel Doppler backscattering diagnostics have been successfully developed on J-TEXT, allowing detailed measurement of the electron temperature and density fluctuations for turbulence and MHD research. The locked mode (LM), especially the 2/1 LM, is one of the biggest threats to the plasma operation. Both the thresholds of 2/1 and 3/1 LM are observed to vary non-monotonically on electron density. The electrode biasing was applied successfully to unlock the LM from either a rotating or static resonant magnetic perturbation (RMP) field. In the presence of 2/1 LM, three kinds of standing wave (SW) structures have been observed to share a similar connection to the island structure, i.e. the nodes of the SWs locate around the O- or X-points of the 2/1 island. The control and mitigation of disruption is essential to the safe operation of ITER, and it has been systematically studied by applying a RMP field, massive gas injection (MGI) and shattered pellet injection on J-TEXT. When the RMP-induced 2/1 LM is larger than a critical width, the MGI shutdown process can be significantly influenced. If the phase difference between the O-point of LM and the MGI valve is +90° (or –90°), the penetration depth and the assimilation of impurities can be enhanced (or suppressed) during the pre-thermal quench (TQ) phase and result in a faster (or slower) TQ. A secondary MGI can also suppress the runaway electron (RE) generation, if the additional high-Z impurity gas arrives at the plasma edge before TQ. When the secondary MGI has been applied after the formation of the RE current plateau, the RE current can be dissipated, and the dissipation rate increases with the injected impurity quantity but saturates with a maximum of 28 MA s –1 . The non-local transport is experimentally observed in the ion transport channel. The electron thermal diffusivity significantly increases with the ECRH power. Theoretical work shows that significant intrinsic current can be driven by electromagnetic turbulence, and the robust formation mechanism of the E × B staircase is identified from the Hasegawa–Wakatani system.

divertor↗

NASA NTRSDate not supplied

Predictive Modeling of Carbon Ablators

Efforts to build a Predictive Material Modeling (PMM) framework from the micro-scale to the macro-scale are presented in this abstract. To reduce the need for extensive testing, accelerate the design cycle process, and reduce uncertainty margins applied to final designs, NASA is developing simulation and modeling tools that enable characterization of material properties and response to high-enthalpy environments. The Porous Microstructure Analysis (PuMA) code has been developed for computing macroscale (volume averaged) properties of porous materials using microscale images from micro-computed tomography (micro-CT). Microscale modeling requires a realistic representation of a material microstructure; these are obtained either synthetically during the design of the material or through X-ray micro-CT. Volume averaged properties are then used to inform macroscale material response models, such as those implemented in the Porous-material Analysis Toolbox based on OpenFOAM (PATO) software, also actively developed by NASA. The computational model in PATO is a generic heat and mass transfer model for porous reactive materials containing several solid phases and a single gas phase. The detailed chemical interactions occurring between the solid phases and the gas phase are modeled at the pore scale assuming local thermal equilibrium. These tools were developed to efficiently interface with other pre-existing codes such as SPARTA (direct simulation Monte Carlo), DPLR (hypersonic CFD), NEQAIR (radiative transport) and DAKOTA (uncertainty quantification and optimization). Detailed flight data (Mars Science Laboratory [MSL] Entry Descent and Landing Instrument [MEDLI]) is critical for validating these computational tools for NASA applications. Examples of modeling ablative material response using these codes will be presented including 3D simulations of the full-scale heatshield of the MSL capsule. The simulations demonstrate the ability of the modern material response code, PATO, to handle the material response of geometrically complex and large domains, through the use of massively parallel computations.

Thermal Protection Systems↗

NASA NTRSDate not supplied

Predictive Modeling of Carbon Ablators Using Micro and Macro-Scale Modeling

Thermal Protection Systems↗

DOE OSTI2025

X-ray Computed Tomography Data of Dense Metallic Components

The data shared in here are X-ray computed tomography (XCT) scans of a hexagonal fuel nozzle in 3 sections with the Metrotom 800 system at the Manufacturing Demonstration Facility (MDF) at Oak Ridge National Laboratory. The data are used in the paper "Tomographic Sparse View Selection using the View Covariance Loss, by Lin et al. (doi:10.1109/TPAMI.2025.36000720), accepted to the international conference on computational imaging (ICCP 2025). Figures 4-7 in the paper describe the part/XCT scan. File name Descriptions: Bottom section: TCR- Single Channeled SRC L 2019-3-18 12-26-41.hdf5 Medium section: TCR- Single Channeled SRC M 2019-3-18 13-8-9.hdf5 Top section: TCR- Single Channeled SRC T 2019-3-18 13-45-39.hdf5 Each hdf5 file contains projection data, and all the relevant X-ray CT scan setting. The full list of included attributes: distance_unit: Units of all distances specified angle_unit : Units of the angles angles: Array of all angles used voxel_size_xy: Baseline recon (if any) has this voxel size in the in-plane direction voxel_size_z: Baseline recon (if any) has this voxel size in the cross-plane direction det_pixel_size_col: Size of the detector pixels in the column dimension det_pixel_size_row: Size of the detector pixels in the row dimension src_iso_dist: Source to iso-center distance iso_det_dist: Iso-center to detector distance det_angle: If the detector is rotated/tilted, this angle corresponds to that value det_row_offset: Center of rotation offset in the vertical direction det_col_offset: Center of rotation offset in the horizontal direction reconstruction: A baseline reconstruction stored as 3D array BHC params: Beam-hardening parameters - Van De Casteel Model - if it has been used to pre-process the projections We also provided a python script (hdf_io.py) that allows the user to read the relevant data from each hdf5 file.

Ziabari, Amir [Oak Ridge National Laboratory]↗