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NASA Tech Briefs, December 2009

Topics include: A Deep Space Network Portable Radio Science Receiver; Detecting Phase Boundaries in Hard-Sphere Suspensions; Low-Complexity Lossless and Near-Lossless Data Compression Technique for Multispectral Imagery; Very-Long-Distance Remote Hearing and Vibrometry; Using GPS to Detect Imminent Tsunamis; Stream Flow Prediction by Remote Sensing and Genetic Programming; Pilotless Frame Synchronization Using LDPC Code Constraints; Radiometer on a Chip; Measuring Luminescence Lifetime With Help of a DSP; Modulation Based on Probability Density Functions; Ku Telemetry Modulator for Suborbital Vehicles; Photonic Links for High-Performance Arraying of Antennas; Reconfigurable, Bi-Directional Flexfet Level Shifter for Low-Power, Rad-Hard Integration; Hardware-Efficient Monitoring of I/O Signals; Video System for Viewing From a Remote or Windowless Cockpit; Spacesuit Data Display and Management System; IEEE 1394 Hub With Fault Containment; Compact, Miniature MMIC Receiver Modules for an MMIC Array Spectrograph; Waveguide Transition for Submillimeter-Wave MMICs; Magnetic-Field-Tunable Superconducting Rectifier; Bonded Invar Clip Removal Using Foil Heaters; Fabricating Radial Groove Gratings Using Projection Photolithography; Gratings Fabricated on Flat Surfaces and Reproduced on Non-Flat Substrates; Method for Measuring the Volume-Scattering Function of Water; Method of Heating a Foam-Based Catalyst Bed; Small Deflection Energy Analyzer for Energy and Angular Distributions; Polymeric Bladder for Storing Liquid Oxygen; Pyrotechnic Simulator/Stray-Voltage Detector; Inventions Utilizing Microfluidics and Colloidal Particles; RuO2 Thermometer for Ultra-Low Temperatures; Ultra-Compact, High-Resolution LADAR System for 3D Imaging; Dual-Channel Multi-Purpose Telescope; Objective Lens Optimized for Wavefront Delivery, Pupil Imaging, and Pupil Ghosting; CMOS Camera Array With Onboard Memory; Quickly Approximating the Distance Between Two Objects; Processing Images of Craters for Spacecraft Navigation; Adaptive Morphological Feature-Based Object Classifier for a Color Imaging System; Rover Slip Validation and Prediction Algorithm; Safety and Quality Training Simulator; Supply-Chain Optimization Template; Algorithm for Computing Particle/Surface Interactions; Cryogenic Pupil Alignment Test Architecture for Aberrated Pupil Images; and Thermal Transport Model for Heat Sink Design.

Source record↗

Neurovascular Responses to Simulated Deep Space Radiation in a Human Organ-on-a-Chip Model

A major health risk for human deep space exploration is central nervous system (CNS) damage by galactic cosmic ray radiation. Simulated galactic cosmic rays or their components, especially the high-linear energy transfer (LET) particles such as 56Fe ions, have been shown to cause CNS damage, neuroinflammation and cognitive dysfunction in rodent models, but their effects on human CNS remain to be investigated. CNS damage from any insult, including ionizing radiation, is partially mediated by the blood-brain barrier (BBB), which regulates interactions between CNS and the rest of the body. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuroinflammation. However, there have been few studies on BBB and astrocyte functions in regulating CNS responses, especially in human tissue analogs. Therefore, we utilized a high-throughput 3D organ-on-a-chip system, seeded with human induced pluripotent stem cell-derived astrocytes and brain endothelial cells, or brain endothelial cells alone, to study human neurovascular responses to simulated deep space radiation. We investigated the permeability and morphology of vascular structures formed by endothelial cells, as well as oxidative stress and secreted cytokines and chemokine levels over 1-7 days after irradiation with 0.25 – 0.5 Gy 5-ion simplified simulated galactic cosmic rays or 0.3 – 0.8 Gy high-LET 600 MeV/n 56Fe particles, and compared the outcomes to low-LET X-ray irradiation. We observed that simulated deep space radiation caused delayed astrocyte activation in a pattern resembling CNS responses to brain injury, caused oxidative stress and the production of inflammatory cytokines, and compromised BBB integrity by damaging tight junctions, thus increasing vascular permeability. Furthermore, our results indicate that astrocytes have a dual role in regulating radiation responses: they exacerbate blood-brain barrier permeability early after irradiation, followed by switching to a more protective scar-like phenotype by reducing oxidative stress and pro-inflammatory cytokine and chemokine secretion. In a follow-up study using the same platform, we investigated the dose-rate effects of ionizing radiation, by exposing our model to chronic, low dose-rate, gamma radiation. Our model was significantly improved by adding additional cell types composing the BBB, modelling immune cell infiltration into the brain, and studying the effect of an antioxidant, to measure more complex outcomes and model more closely the effect of deep space radiation on the human BBB. In summary, our results present a human neurovascular model for space radiation studies and potential future automated payload adaptation, and suggest astrocyte regulatory mechanisms as targets for countermeasures to mitigate human neurovascular impairments during deep space exploration.

Ionizing radiation↗

Impact Craters on Mars: Natural 3D Exploration Probes of Geological Evolution

Introduction: The population of impact craters preserved on the surface of Mars offers fundamental constraints on the three- dimensional mechanical characteristics of the martian crust, its volatile abundance, and on the styles of erosion that have operated during essentially all epochs of martian geological history. On the basis of the present- day wealth of morphologic and geometric observations of impact landforms on Mars [ 1-31, an emerging understanding of the three-dimensional physical properties of the martian uppermost crust in space and time is at hand. In this summary, the current basis of understanding of the relatively non- degraded population of impact landforms on Mars is reviewed, and new Mars Global Surveyor (MGS)-based (MOLA) measurements of global geometric properties are summarized in the context of upcoming observations by Mars Reconnaissance Orbiter (MRO).

Garvin, James B.↗

Observations of Total Lightning Associated with Severe Convection During the Wet Season in Central Florida

This paper will discuss findings of a collaborative lightning research project between National Aeronautics and Space Administration, the Massachusetts Institute of Technology and the National Weather Service office In Melbourne Florida. In August 1996, NWS/MLB received a workstation which incorporates data from the KMLB WSR-88D, Cloud to Ground (CG) stroke data from the National Lightning Detection Network (NLDN), and 3D volumetric lightning data collected from the Kennedy Space Centers' Lightning Detection And Ranging (LDAR) lightning system. The two primary objectives of this lightning workstation, called Lightning Imaging Sensor Data Applications Display (USDAD), are to: observe how total lightning relates to severe convective storm morphology over central Florida, and compare ground based total lightning data (LDAR) to a satellite based lightning detection system. This presentation will focus on objective #1. The LISDAD system continuously displays CG and total lighting activity overlaid on top of the KMLB composite reflectivity product. This allows forecasters to monitor total lightning activity associated with convective cells occurring over the central Florida peninsula and adjacent coastal waters. The LISDAD system also keeps track of the amount of total lightning data, and associated KMLB radar products with individual convective cells occurring over the region. By clicking on an individual cell, a history table displays flash rate information (CG and total lightning) in one minute increments, along with radar parameter trends (echo tops, maximum dBz and height of maximum dBz) every 5 minutes. This history table Is updated continuously, without user intervention, as long as the cell is identified. Reviewing data collected during the 1997 wet season (21 cases) revealed that storms which produced severe weather (hall greater or = 0.75 in. or wind damage) typically showed a rapid rise In total lightning prior to the onset of severe weather. On average, flash rate increases of 25 FPM per minute over a time scale of approximately 5 minutes were common. These pulse severe storms typically reached values of 150 to 200 FPM with some cells exceeding 400 FPM. One finding which could have a direct application to the warning process is that the rapid increase in lightning typically occurred in advance of the warning issuance time. Comparisons between the ending time of the rapid rate increase and the time of when the warning was issued by NWS/MLB meteorologist exhibited a lead time of 8 minutes. It is conceivable that if close monitoring of the LISDAD system by operational meteorologist is routinely performed, warnings for pulse severe storms could be issued up to 4 to 6 minutes earlier than what is issued currently.

Sharp, D.↗

Innovative Applications of Laser Scanning and Rapid Prototype Printing to Rock Breakdown Experiments

We present the novel application of two technologies for use in rock breakdown experiments, i.e. close-range, ground-based 3D triangulation scanning and rapid prototype printing. These techniques aid analyses of form-process interactions across the range of scales relevant to breakdown (micron-m). This is achieved through (a) the creation of DEMs (which permit quantitative description and analysis of rock surface morphology and morphological change) and (b) the production of more realistically-shaped experimental blocks. We illustrate the use of these techniques, alongside appropriate data analysis routines, in experiments designed to investigate the persistence of fluvially-derived features in the face of subsequent wind abrasion and weathering. These techniques have a range of potential applications in experimental field and lab-based geomorphic studies beyond those specifically outlined here.

Bourke, Mary↗

Surface Processes of Faceted Growth

Atomic force microscopy and high precision optical interferometry allow to analyze the processes that are in the core of our present understanding of faceted crystal growth. Some of these processes will be reviewed. Recent experiments suggest that the Gibbs-Thomson Law (GTL) may not be applicable to the weakly fluctuating strongly polygonized steps, with low kink density. Propagation rate of a straight short step segment changes with the segment length much steeper than predicted by GTL. If the step fluctuations are still well developed, the typical transition length may be determined just by the radius of rounded comers of the polygonized step. If fluctuations do not have enough time to develop, the kinetic effects may be essential. Indeed, 'communications' between comers of a short straight step segment may occur and, thus, the GTL may be implemented only via kink exchange. E.g., dissolutions of this short segment at macroscopic equilibrium occurs as follows: The kinks are split from one comer as a result of fluctuations, and annihilate with kinks of the opposite sign generated by another comer. Similarly, an exchange via chain of kinks on a rough step is the mechanism to implement the GT Law. If there is a supersaturation with respect to a large crystal, the kinks not only diffuse along the step, but move back the generating comers. This 'wind' prevents communication between the comers and places upper limit supersaturation only below which GTL is applicable. Steps replace kinks in the 3D case, though, of course, another dimensionality brings about another physics. Another specific problem to think about is if fluctuations are always fast enough to provide enough kinks for linear dependence of step rate on supersaturation. Increasing azimuthal polygonization of growth hillocks is a sign of insufficient fluctuation rate. Morphological stability of vicinal faces is usually considered on the basis of mutually parallel steps. Azimuthal anisotropy and interlacing of step bunches inducing the well known bunch splitting is another challenge. Among other challenging problems are: existence of surface diffusion on the crystal/so1ution interface, step interaction in solutions, achievement of step flow modes from liquids, impurity effects. New phenomena essential in biomacromolecular crystallization is another interesting area.

Chernov, A.↗

Analysis of stratospheric ozone, temperature, and minor constituent data

The objective of this research is to use available satellite measurements of temperature and constituent concentrations to test the conceptual picture of stratospheric chemistry and transport. This was originally broken down into two sub-goals: first, to use the constituent data to search for critical tests of our understanding of stratospheric chemistry and second, to examine constituent transport processes emphasizing interactions with chemistry on various time scales. A third important goal which has evolved is to use the available solar backscattered ultraviolet (SBUV) and Total Ozone Mapping Spectrometer (TOMS) data from Nimbus 7 to describe the morphology of recent changes in Antarctic and global ozone with emphasis on searching for constraints to theories. The major effort now being pursued relative to the two original goals is our effort as a theoretical team for the Arctic Airborne Stratospheric Expedition (AASE). Our effort for the AASE is based on the 3D transport and chemistry model at Goddard. Our goal is to use this model to place the results from the mission data in a regional and global context. Specifically, we set out to make model runs starting in late December and running through March of 1989, both with and without heterogeneous chemistry. The transport is to be carried out using dynamical fields from a 4D data assimilation model being developed under separate funding from this task. We have successfully carried out a series of single constituent transport experiments. One of the things demonstrated by these runs was the difficulty in obtaining observed low N2O abundances in the vortex without simultaneously obtaining very high ozone values. Because the runs start in late December, this difficulty arises in the attempt to define consistent initial conditions for the 3D model. To accomplish a consistent set of initial conditions, we are using the 2D photochemistry-transport model of Jackman and Douglass and mapping in potential temperature, potential vorticity space as developed by Schoeberl and coworkers.

Stolarski, Richard S.↗

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net↗

NeMO-Net The Neural Multi-Modal Observation Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Remote Sensin↗

VESGEN Mapping of Bioactive Protection against Intestinal Inflammation: Application to Human Spaceflight and ISS Experiments

Challenges to successful space exploration and colonization include adverse physiological reactions to micro gravity and space radiation factors. Constant remodeling of the microvasculature is critical for tissue preservation, wound healing, and recovery after ischemia. Regulation of the vascular system in the intestine is particularly important to enable nutrient absorption while maintaining barrier function and mucosal defense against micro biota. Although tremendous progress has been made in understanding the molecular circuits regulating neovascularization, our knowledge of the adaptations of the vascular system to environmental challenges in the intestine remains incomplete. This is in part because of the lack of methods to observe and quantify the complex processes associated with vascular responses in vivo. Developed by GRC as a mature beta version, pre-release research software, VESsel GENeration Analysis (VESGEN) maps and quantifies the fractal-based complexity of vascular branching for novel insights into the cytokine, transgenic and therapeutic regulation of angiogenesis, lymphangiogenesis and microvascular remodeling. Here we demonstrate that VESGEN can be used to characterize the dynamic vascular responses to acute intestinal inflammation and mucosal recovery from in vivo confocal microscopic 3D image series. We induced transient intestinal inflammation in mice by DSS treatment and investigated whether the ability of the pro biotic yeast Saccharomyces boulardii (Sb) to protect against intestinal inflammation was due to regulation of vascular remodeling. A primary characteristic of inflammation is excessive neovascularization (angiogenesis) resulting in fragile vessels prone to bleeding. Morphological parameters for triplicate specimens revealed that Sb treatment greatly reduced the inflammatory response of vascular networks by an average of 78%. This resulted from Sb inhibition of vascular endothelial growth factor receptor signaling, a major angiogenesis signaling pathway. It needs to be determined whether pro biotic yeast represents a promising approach to GI protection in space. GRC performed only the VESGEN post-testing analysis.

Parsons-Wingerter, P. A.↗

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was implemented to offer an efficient framework for determining material characteristics from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enable parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM). SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography or other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was created to offer an efficient framework for determining material properties from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enables parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM) into our image segmentation workflow. SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography and other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗

Mineralogical, Elemental, and Tomographic Reconnaissance Investigation for CLPS (Metric)

Geological solids are characterized by their mineral structure, elemental composition, and morphology. The Mineralogical, Elemental, and Tomographic Reconnaissance Investigation for CLPS (METRIC) is an instrument payload that will quantify all three. METRIC comprises a suite of instruments in a lander to perform X-ray diffraction (XRD) for mineral structure, X-ray fluorescence (XRF) for elemental composition, and X-ray Micro Computed Tomography (XCT) for 3D internal micromorphology. The instruments are accompanied by an Infrared Spectrometer (IRS) provide geologic context. A Honeybee Robotics pneumatic sampling and transfer system [e.g., 1] will be positioned under the lander to deliver sieved regolith to the X-ray instruments for analysis. This payload is envisioned for deployment to the lunar surface on a Commercial Lunar Payload Services (CLPS) lander but could be carried on a lander or rover to any solid surface in the solar system.

E B Rampe↗

Impact of Simulated Microgravity on Mesenchymal Stem Cell Proliferation

Background Long term exposure to microgravity has adverse effects on human body such as bone loss. Due to the vital role of mesenchymal stem cell (MSC) in bone regeneration, studying MSC under microgravity conditions has been of interest during the past decade. However, high cost and limited access to space flight can dampen enthusiasm of researchers. Microgravity simulators provide a way to investigate the effects of microgravity in human physiology. Methods In this study, we compared MSC cultures under simulated microgravity using random positioning machine (RPM) and Gravite 3D simulators. Two culture durations, 1 week and 2 weeks, were selected for MSC cultures without media change. To evaluate impact of simulated microgravity on cell proliferation, cell counting was performed using trypan blue exclusion assay. Additionally, RNA samples and conditioned media were collected for further analysis. Results After 1 week and 2 weeks, no cell morphology change was observed from RPM and Gravite cultures compared to control. Notably, distinct lower cell confluence at the edge of the flasks on the RPM was observed, which could be caused by fluid sheer forces. MSCs cultured on both microgravity simulators showed decreased cell proliferation after 1-week culture. After 2-week culture, cells grown on the RPM showed no significant difference in cell proliferation compared with control while cells cultured on the Gravite bioreactor showed significantly enhanced MSC proliferation. Conclusion Type of microgravity simulator and duration of culture significantly affect MSC proliferation. Further investigation into how simulated microgravity influences MSC gene expression and cytokine secretion related to bone loss is currently on going in our lab.

Cuiping Zhang↗

The extended atmosphere and circumstellar environment of the cool evolved star VX Sagittarii as seen by MATISSE

Context. VX Sgr is a cool, evolved, and luminous red star whose stellar parameters are difficult to determine, which affects its classification. Aims. We aim to spatially resolve the photospheric extent as well as the circumstellar environment. Methods. We used interferometric observations obtained with the MATISSE instrument in the L (3–4 μm), M (4.5–5 μm), and N (8–13 μm) bands. We reconstructed monochromatic images using the MIRA software. We used 3D radiation-hydrodynamics simulations carried out with CO5BOLD and a uniform disc model to estimate the apparent diameter and interpret the stellar surface structures. Moreover, we employed the radiative transfer codes OPTIM3D and RADMC3D to compute the spectral energy distribution for the L, M, and N bands, respectively. Results. MATISSE observations unveil, for the first time, the morphology of VX Sgr across the L, M, and N bands. The reconstructed images show a complex morphology with brighter areas whose characteristics depend on the wavelength probed. We measured the angular diameter as a function of the wavelength and showed that the photospheric extent in the L and M bands depends on the opacity through the atmosphere. In addition to this, we also concluded that the observed photospheric inhomogeneities can be interpreted as convection-related surface structures. The comparison in the N band yielded a qualitative agreement between the N-band spectrum and simple dust radiative transfer simulations. However, it is not possible to firmly conclude on the interpretation of the current data because of the difficulty in constraing the model parameters using the limited accuracy of our absolute flux calibration. Conclusions. MATISSE observations and the derived reconstructed images unveil the appearance of VX Sgr’s stellar surface and circumstellar environment across a very large spectral domain for the first time.

stars: atmospheres↗

Multi-Scale Thermo-Mechanical Modeling of Porous 3D Woven TPS Materials

This work summarizes the process to compute and analyze the thermal conductivity and mechanical properties of 3D woven TPS materials such as 3MDCP (3D Mid-Density Carbon-Phenolic). The PuMA software, developed at NASA Ames, was used to characterize different 3MDCP samples from their constituents' data, averaging their thermal conductivity and elastic properties in the three main directions to obtain their effective orthotropic thermo-mechanical properties. This was performed in multiple steps: firstly, TPS samples were digitally reconstructed using micro computed tomography (µCT) and their constituents were segmented; then, the porous matrix phase was analyzed at the micro-scale and these results were used, along with the fibers’ constituents information, to model the tows at the meso-scale; finally, results from the constituents were homogenized and used to model the thermo-mechanical behavior of the unit cell at the macro-scale. Additionally, to gain a better understanding of the tows’ morphology and distribution of the carbon-phenolic blended fibers, microscopy images of the tows’ cross-section were segmented using deep learning techniques and analyzed with PuMA. This workflow can be applied to any TPS material to computationally obtain its thermo-mechanical properties, enabling more informed TPS design and manufacturing choices.

Multi-Scale↗

Multi-Scale Thermo-Mechanical Modeling of Porous 3D Woven TPS Materials

This work summarizes the process to compute and analyze the thermal conductivity and mechanical properties of 3D woven TPS materials such as 3MDCP (3D Mid-Density Carbon-Phenolic). The PuMA [1,2] software, developed at NASA Ames, was used to characterize different 3MDCP samples from their constituents' data, averaging their thermal conductivity and elastic properties in the three main directions to obtain their effective orthotropic thermo-mechanical properties. This was performed in multiple steps: firstly, TPS samples were digitally reconstructed using micro computed tomography (µCT) and their constituents were segmented; then, the porous matrix phase was analyzed at the micro-scale and these results were used, along with the fibers’ constituents information, to model the tows at the meso-scale; finally, results from the constituents were homogenized and used to model the thermo-mechanical behavior of the unit cell at the macro-scale. Additionally, to gain a better understanding of the tows’ morphology and distribution of the carbon-phenolic blended fibers, microscopy images of the tows’ cross-section were segmented using deep learning techniques and analyzed with PuMA. This workflow can be applied to any TPS material to computationally obtain its thermo-mechanical properties, enabling more informed TPS design and manufacturing choices.

Multi-Scale↗

Correlations Among Microstructure, Morphology, Chemistry, and Isotopic Systematics of Hibonite in CM Chondrites

Introduction: Hibonite is a primary refractory phase occurring in many CAIs, typically with spinel and perovskite. Our microstructural studies of CAIs from carbonaceous chondrites reveal a range of stacking defect densities and correlated non-stoichiometry in hibonite. We also conducted a series of annealing experiments, demonstrating that the Mg-Al substitution stabilized the formation of defect-structured hibonite. Here, we continue a detailed TEM analysis of hibonite-bearing inclusions from CM chondrites that have been well-characterized isotopically. We examine possible correlations of microstructure, morphology, mineralogy, and chemical and isotopic systematics of CM hibonites in order to better understand the formation history of hibonite in the early solar nebula. Methods: Fifteen hibonite-bearing inclusions from the Paris CM chondrite were analyzed using a JEOL 7600F SEM and a JEOL 8530F electron microprobe. In addition to three hibonite-bearing inclusions from the Murchison CM chondrite previously reported, we selected three inclusions from Paris, Pmt1-6, 1-9, and 1-10, representing a range of 26Al/27Al ratios and minor element concentrations for a detailed TEM study. We extracted TEM sections from hibonite grains using a FEI Quanta 3D field emission gun SEM/FIB. The sections were then examined using a JEOL 2500SE field-emission scanning TEM equipped with a Thermo-Noran thin window EDX spectrometer. Results and Discussion: A total of six hibonite-bearing inclusions, including two platy hibonite crystals (PLACs) and four spinel-hibonite inclusions (SHIBs), were studied. There are notable differences in chemical and isotopic compositions between the inclusions (Table 1), indicative of their different formation environment or timing. Our TEM observations show perfectly-ordered, stoichiometric hibonite crystals without stacking defects in two PLACs, 2-7-1 and 2-8-2, and in three SHIBs, Pmt1-6, 1-9, and 1-10. In contrast, SHIB 1-9-5 hibonite grains contain a low density of stacking defects linked to an increase in MgO contents, indicating complex, disordered intergrowths of stoichiometric and MgO-enriched hibonites. From the data collected to date, we find no clear correlation between the microstructures of hibonite and its morphological and mineralogical types that reflect distinct chemical and isotopic systematics [6-8,10]. Interestingly, the presence of no or few stacking defects in hibonite from the PLACs and SHIBs are in contrast to our experimental studies that produced very high densities of stacking defects in hibonite [3-5]. Unlike our experi-ments, electron microprobe data from the PLACs and SHIBs hibonite grains show a strong correlation between (Ti4++Si4+) and Mg2+ cations, suggesting that coupled substitutions of (Ti4++Mg2+) and (Si4++Mg2+) for 2Al3+ inhibit the formation of defect-structured hibonite. However, our experimental studies suggest that kinetics (e.g., cooling rate) or other thermal effects also exert a strong control on the microstructures and chemical compositions of hibonite. In Pmt1-6, elongated perovskite grains present at the hibonite grain boundaries display (121) twinning, indicative of a fast cooling (>50degC/min) after high-temperature events. Therefore, the nebular microstructural characteristics of hibonite, at least in this inclusion, would not have destroyed by subsequent high-temperature annealing. Conclusions: Our TEM observations thus far show no clear correlation in microstructures, morphological and mineralogical characteristics, and chemical and isotopic systematics of hibonites from CM chondrites. The observed variation in stacking defect densities in the hibonites may be controlled by thermal processes in the early solar nebula. A detailed TEM analysis of additional CM hibonite samples is underway to evaluate this hypothesis.

Han, J.↗