Results for “3d reconstruction” — Page 4

NASA NTRSDate not supplied

Design of a Lunar Plume-Surface Interaction Measurement System

Plume-surface interactions between a rocket plume and the lunar surface will be studied in-situ during two of NASA’s upcoming Commercial Lunar Payload Services Program missions. The payload, Stereo Cameras for Lunar Plume-Surface Studies (SCALPSS), will employ a multiple-camera photogrammetry system to obtain stereo images of the lunar regolith before, during, and after significant erosion and subsequent crater formation. The evaluation of measurement system capabilities and design process of the payload is informed by computational fluid dynamics predictions, accuracy modeling based on experimental data, camera simulation, and lander design, all of which are combined in the Virtual Diagnostic Interface. The second SCALPSS mission, traveling to the moon on Firefly Aerospace’s Blue Ghost lander in early 2023, aims to build on the design and complexity of the first payload, which is launching in early 2022 on Intuitive Machines’ Nova-C lander. The Blue Ghost SCALPSS mission will include two additional cameras and a total of three different lens focal lengths which will target specific points in the vehicle’s descent to obtain quantitative and accurate 3D reconstruction of the lunar surface both prior to and after crater formation.

photogrammetry↗

NASA NTRSDate not supplied

Mineralogical, Elemental and Tomographic Reconnaissance Investigation for CLPS (“METRIC”)

METRIC comprises a suite of two instruments in a Lunar lander that 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 optical-near IR cameras to provide local geologic context. The Honeybee Robotics PlanetVac pneumatic sampling and transfer system [1],positioned on a lander footpad, will deliver sieved regolith to the X-ray instruments for analysis. The instrument suite is intended for delivery to the lunar surface on a Commercial Lunar Payload Services (CLPS) lander. The METRICXRD/F instrument draws on heritage from the Mars Science Laboratory CheMin instrument [2] and improves upon the design in multiple ways [3]. Like CheMin, Rietveld refinement and full-pattern fitting of METRIC XRD data can identify minerals at a detection limit of ~1 wt.%, quantify their abundances when present at >3 wt.%, and determine mineral composition (e.g., Fo#in olivine) from lattice parameters for minerals present at >5 wt.%[4,5]. An optimized XRF geometry provides for improved detection and quantification of major, minor and trace elements. The METRIC XCT instrument is a miniaturized X-ray Computed Tomography scanner[6]. Lunar regolith is delivered to a 3 mm diameter, 10 mm long graphite tube inside the instrument. The tube is rotated through 360°in 0.9deg.incrementsand a divergent point source X-ray beam is directed through the material. A Charge Coupled Device (CCD)records attenuation images whose brightness and contrast area function of average atomic number and density. Quantitative data, including particle and void sizes, 3D particle shape parameters, modal volumes and pore geometry can be derived from the resulting 3D reconstructions(voxel resolution: 30 μm). Crystal morphologies derived from METRIC XCT data complement the bulk mineralogy determined by the METRIC XRD/F and provide a measure of grain size distribution for the different phases. Taken together, the METRIC instrument suite determines crystal structure, elemental composition and morphology, three principal characteristics of geological materials that are highly useful in determining the origin and subsequent processing of lunar regolith.

Moon↗

NASA NTRSDate not supplied

Atom Probe Tomography and Three-Dimensional Atomic Scale Characterisation of Interplanetary Dust Particles: Inorganic and Organic, Hydrous and Anhydrous Assemblages

Interplanetary dust particles (IDPs)preserve primordial fragments from our Solar System and external stellar systems, sampled from a vast range of dust forming bodies that often display smaller degrees of parent body processing than is seen in meteorites. IDPs preserve some of the smallest astromaterials from our Solar System, many of which are believed to be among the most important materials for studying physical and chemical processing, and formation mechanisms occurring within the interstellar medium (ISM), Solar Nebula and external planetary systems[1]. However, their formation processes and provenance are poorly constrained, owing in part to spatial resolution limitations of traditional analytical techniques. Atom probe tomography (APT) uses a pulsed laser to field-evaporate material at the atomic scale from needle-shaped samples, and time-of-flight spectrometry for 3D reconstruction of element and isotope distribution in samples after data acquisition. This technique has the highest spatial resolution available of any technique used within the geoscience field[2]. However, measuring multi-phase specimens and porous media in APT can be challenging, two primary characteristics of IDPs. Here we present a custom method for APT needle design and the first results of a 3Datomic scale study of interplanetary dust particles, salt crystals and extraterrestrial insoluble and soluble organic matter designed to overcome the challenges of studying IDP-like materials.

N D Nevill↗

NASA NTRS2023

Three Eruptions Observed by Remote Sensing Instruments Onboard Solar Orbiter

On February 21 and March 21 – 22, 2021, the Extreme Ultraviolet Imager (EUI) onboard Solar Orbiter observed three prominence eruptions. The eruptions were associated with coronal mass ejections (CMEs) observed by Metis, Solar Orbiter’s coronagraph. All three eruptions were also observed by instruments onboard the Solar–TErrestrial RElations Observatory (Ahead; STEREO-A), the Solar Dynamics Observatory (SDO), and the Solar and Heliospheric Observatory (SOHO). Here we present an analysis of these eruptions. We investigate their morphology, direction of propagation, and 3D properties. We demonstrate the success of applying two 3D reconstruction methods to three CMEs and their corresponding prominences observed from three perspectives and different distances from the Sun. This allows us to analyze the evolution of the events, from the erupting prominences low in the corona to the corresponding CMEs high in the corona. We also study the changes in the global magnetic field before and after the eruptions and the magnetic field configuration at the site of the eruptions using magnetic field extrapolation methods. This work highlights the importance of multi-perspective observations in studying the morphology of the erupting prominences, their source regions, and associated CMEs. The upcoming Solar Orbiter observations from higher latitudes will help to constrain this kind of study better.

Coronal mass ejections↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface. In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha-Ray↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

NASA NTRS2023

Toward Physics-informed Neural Networks for 3D Multi-layer Cloud Mask Reconstruction

Three-dimensional (3D) cloud retrievals are critical for understanding their impact on climate and other applications such as aviation safety, weather prediction, and remote sensing. However, obtaining high-resolution and accurate vertical representation of clouds remains unsolved due to the limitations imposed by satellite instrumentation, viewing conditions, and the complexity of cloud dynamics. Cloud masks are essential for comprehending various cloud vertical properties, but deriving accurate 3D cloud masks from 2D satellite imagery data is a challenging task. To tackle these challenges, we introduce a physics-informed loss function for training deep learning models that can extend 2D cloud images into 3D cloud masks. The proposed loss, called CloudMask Loss, is composed of two domain knowledge-informed loss terms: one for evaluating cloud position and thickness, and the other for measuring the number of layers. By combining these loss terms, we improve the trainability of the deep learning models for more accurate and meaningful results. We apply the proposed loss function to different neural networks and demonstrate significant improvements in multi-layer cloud mask reconstruction. Utilizing the same neural network architecture, our proposed loss outperforms standard binary crossentropy loss in terms of multi-layer cloud classification accuracy, number of layers accuracy, and thickness mean absolute error (MAE). The proposed loss function can be readily integrated into various neural network architectures, resulting in substantial performance gains in 3D cloud mask generation.

multi-layer clouds↗

NASA NTRS1999

3D-Stereoscopic Analysis of Solar Active Region Loops: SoHo/EIT Observations at Temperatures of 1.5-2.5 MK - 2

In this paper we study the three-dimensional (3D) structure of hot (T(sub e) approximately equals 1.5 - 2.5 MK) loops in solar active region NOAA 7986, observed on 1996 August 30 with the Extreme-ultraviolet Imaging Telescope (EIT) onboard the Solar and Heliospheric Observatory (SoHO). This complements a first study on cooler (T(sub e) approximately equals 1.0 - 1.5 MK) loops of the same active region, using the same method of Dynamic Stereoscopy to reconstruct the 3D geometry. We reconstruct the 3D-coordinates x(s), y(s), z(s), the density n(sub e)(s), and temperature profile T(sub e)(s) of 35 individual loop segments (as function of the loop coordinate s) using EIT 195 A and 284 A images. The major findings are: (1) All loops are found to be in hydrostatic equilibrium, in the entire temperature regime of T(sub e) = 1.0 - 2.5 MK; (2) The analyzed loops have a height of 2-3 scale heights, and thus only segments extending over about one vertical scale height have sufficient emission measure contrast for detection; (3) The temperature gradient over the lowest scale height is of order dT/ds is approximately 1 - 4 K/km; (4) The radiative loss rate is found to exceed the conductive loss rate by about two orders or magnitude, making thermal conduction negligible to explain the temperature structure of the loops; (5) A steady-state can only be achieved when the heating rate E(sub H) matches the radiative loss rate in hydrostatic equilibrium, requiring a heat deposition length lambda(sub H) of the half density scale height lambda, predicting a scaling law with the loop base pressure, EH varies as p(sub 0 exp 2). This favors coronal heating mechanisms that operate near the loop footpoints; (6) We find a reciprocal correlation between the loop pressure p(sub 0) and loop length L, i.e. p(sub 0) varies as 1/L, implying a scaling law of the steady-state requirement with loop length, i.e. E(sub H ) varies as 1/L(exp 2). The heating rate shows no correlation with the loop-aligned magnetic field component B(sub z) at the footpoints, but is correlated with the azimuthal field B(sub phi) = Bz(RDelta Phi/L) of a twisted loop, and is thus consistent with heating mechanisms based on field-aligned currents.

Aschwanden, Markus J.↗

NASA NTRS1998

3D-Stereoscopic Analysis of Solar Active Region Loops: I: SoHo/EIT Observations at Temperatures of 1.0-1.5 MK

The three-dimensional (3D) structure of solar active region NOAA 7986 observed on 1996 August 30 with the Extrem-ultraviolet Imaging Telescope (EIT) onboard the Solar and Heliospheric Observatory (SoHO) is analyzed. We develop a new method of Dynamic Stereoscopy to reconstruct the 3D geometry of dynamically changing loops, which allows us to determine the orientation of the loop plane with respect to the line-of-sight, a prerequisite to correct properly for projection effects in 3D loop models. With this method and the filter-ratio technique applied to EIT 171 A and 195 A images we determine the 3D coordinates (x(s), y(s), z(s)), the loop width) w(s), the electron density n(sub e)(s), and the electron temperature T(sub e)(s) as function of the loop length s for 30 loop segments. Fitting the loop densities with an exponential density model n(sub e)(h) we find that the so inferred scale height temperatures, T(sub e)(sup lambda) = 1.22 +/- 0.23 MK, match closely the EIT filter-ratio temperatures, T(sub e)(sup FIT) = 1.21 +/- 0.06 MK. We conclude that these rather large-scale loops (with heights of h approx. equals 50 - 200 Mm) that dominate EIT 171 A images are close to thermal equilibrium. Most of the loops show no significant thickness variation w(s), but many exhibit a trend of increasing temperature (dT/ds greater than 0) above the footpoint.

Aschwanden, Markus J.↗

NASA NTRS2011

Relation Between the 3D-Geometry of the Coronal Wave and Associated CME During the 26 April 2008 Event

We study the kinematical characteristics and 3D geometry of a large-scale coronal wave that occurred in association with the 26 April 2008 flare-CME event. The wave was observed with the EUVI instruments aboard both STEREO spacecraft (STEREO-A and STEREO-B) with a mean speed of approx 240 km/s. The wave is more pronounced in the eastern propagation direction, and is thus, better observable in STEREO-B images. From STEREO-B observations we derive two separate initiation centers for the wave, and their locations fit with the coronal dimming regions. Assuming a simple geometry of the wave we reconstruct its 3D nature from combined STEREO-A and STEREO-B observations. We find that the wave structure is asymmetric with an inclination toward East. The associated CME has a deprojected speed of approx 750 +/- 50 km/s, and it shows a non-radial outward motion toward the East with respect to the underlying source region location. Applying the forward fitting model developed by Thernisien, Howard, and Vourlidas we derive the CME flux rope position on the solar surface to be close to the dimming regions. We conclude that the expanding flanks of the CME most likely drive and shape the coronal wave.

CMEs↗

NASA NTRSDate not supplied

3D Geolocation of Simulated Lightning Sources from Low-Earth Orbit

The recent removal of the Lightning Imaging Sensor from the International Space Station has left an observational gap in lightning detection from low-Earth orbit (LEO). However, new studies have demonstrated the potential for 3D geolocation of lightning sources using orbiting sensors. The Cubespark mission concept aims to take advantage of these developments by deploying a constellation of satellites with radio frequency (RF) sensors and optical imagers to not only map lightning locations, but also to collect bi-spectral flash images. These new capabilities include mapping storm charge structure, flash channel structure, and distinguishing microphysical processes throughout flash development, helping link microphysics and convective processes with overall flash and storm structure around the globe from LEO. In this study, we simulate lightning RF sources in the very high frequency (VHF) band, extrapolate their signals to space-based detection using an improved ionospheric model, and reconstruct their 3D locations using a time-of-arrival (TOA) minimization algorithm. Various constellation configurations, locations, and atmospheric conditions are considered in order to identify and quantify the three main sources of geolocation error: geometric, ionospheric, and instrumental effects. The promising results of this study emphasize the potential of space-based 3D lightning mapping under diverse conditions. 3D resolution is shown to be better than 1-2 km in many cases, enabling new global applications in meteorology and climate sciences. Here we present a selection of these geolocation results as seen from space alongside recent advancements, paving the way for a future generation of LEO lightning mappers.

CubeSpark↗

NASA NTRS2011

Orthographic Stereo Correlator on the Terrain Model for Apollo Metric Images

A stereo correlation method on the object domain is proposed to generate the accurate and dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce high-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. Given camera parameters of an image pair from bundle adjustment in ASP, a correlation window is defined on the terrain with the predefined surface normal of a post rather than image domain. The squared error of back-projected images on the local terrain is minimized with respect to the post elevation. This single dimensional optimization is solved efficiently and improves the accuracy of the elevation estimate.

Terrain Model↗

NASA NTRS1990

Hierarchical approach to reconstruct surfaces by using iteratively rectified imagery

A new approach to reconstruct the 3D surface of the object space from digital images is described. All the object points obtained by an automatic orientation procedure lead to a first approximation of the surface. Edges are computed for one image and matched to the other image by grey level correlation or least-squares matching through the scale space. To every discrete step in the scale space there exists the digital stereopair (image pyramid), the corresponding surface digital elevation model (DEM), and the warped images. The warped images in this discrete scale space representation correspond to digital orthophotos obtained from the DEMs that result from matching the image pyramid. The warped images will be used on every successive level in the image pyramid in order to reduce the foreshortening problems associated with any area-based matching method.

Schenk, Toni↗

NASA NTRS1999

The Effect of Spaceflight on Bone Cell Cultures

Understanding the response of bone to mechanical loading (unloading) is extremely important in defining the means of adaptation of the body to a variety of environmental conditions such as during heightened physical activity or in extended explorations of space or the sea floor. The mechanisms of the adaptive response of bone are not well defined, but undoubtedly they involve changes occurring at the cellular level of bone structure. This proposal has intended to examine the hypothesis that the loading (unloading) response of bone is mediated by specific cells through modifications of their activity cytoskeletal elements, and/or elaboration of their extracellular matrices. For this purpose, this laboratory has utilized the results of a number of previous studies defining molecular biological, biochemical, morphological, and ultrastructural events of the reproducible mineralization of a primary bone cell (osteoblast) culture system under normal loading (1G gravity level). These data and the culture system then were examined following the use of the cultures in two NASA shuttle flights, STS-59 and STS-63. The cells collected from each of the flights were compared to respective synchronous ground (1G) control cells examined as the flight samples were simultaneously analyzed and to other control cells maintained at 1G until the time of shuttle launch, at which point they were terminated and studied (defined as basal cells). Each of the cell cultures was assayed in terms of metabolic markers- gene expression; synthesis and secretion of collagen and non-collagenous proteins, including certain cytoskeletal components; assembly of collagen into macrostructural arrays- formation of mineral; and interaction of collagen and mineral crystals during calcification of the cultures. The work has utilized a combination of biochemical techniques (radiolabeling, electrophoresis, fluorography, Western and Northern Blotting, and light microscopic immunofluorescence) and structural methods (conventional and high voltage electron microscopy, inununocytochemistry, stereomicroscopy, and 3D image reconstruction). The studies have provided new knowledge of aspects of bone cell development and structural regulation, extracellular matrix assembly, and mineralization during spaceflight and under normal gravity. The information has contributed to insights into the means in general by which cells respond and adapt to different conditions of gravity (loading). The data may as well have suggested an underlying basis for the observed loss of bone by vertebrates, including man, in microgravity; and these scientific results may have implications for understanding bone loss following fracture healing and extended periods of inactivity such as during long-term bedrest.

Landis, William J.↗

NASA NTRS1999

Autonomous Image Analysis for Future Mars Missions

To explore high priority landing sites and to prepare for eventual human exploration, future Mars missions will involve rovers capable of traversing tens of kilometers. However, the current process by which scientists interact with a rover does not scale to such distances. Specifically, numerous command cycles are required to complete even simple tasks, such as, pointing the spectrometer at a variety of nearby rocks. In addition, the time required by scientists to interpret image data before new commands can be given and the limited amount of data that can be downlinked during a given command cycle constrain rover mobility and achievement of science goals. Experience with rover tests on Earth supports these concerns. As a result, traverses to science sites as identified in orbital images would require numerous science command cycles over a period of many weeks, months or even years, perhaps exceeding rover design life and other constraints. Autonomous onboard science analysis can address these problems in two ways. First, it will allow the rover to preferentially transmit "interesting" images, defined as those likely to have higher science content. Second, the rover will be able to anticipate future commands. For example, a rover might autonomously acquire and return spectra of "interesting" rocks along with a high-resolution image of those rocks in addition to returning the context images in which they were detected. Such approaches, coupled with appropriate navigational software, help to address both the data volume and command cycle bottlenecks that limit both rover mobility and science yield. We are developing fast, autonomous algorithms to enable such intelligent on-board decision making by spacecraft. Autonomous algorithms developed to date have the ability to identify rocks and layers in a scene, locate the horizon, and compress multi-spectral image data. We are currently investigating the possibility of reconstructing a 3D surface from a sequence of images acquired by a robotic arm camera. This would then allow the return of a single completely in focus image constructed only from those portions of individual images that lie within the camera's depth of field. Output from these algorithms could be used to autonomously obtain rock spectra, determine which images should be transmitted to the ground, or to aid in image compression. We will discuss these algorithms and their performance during a recent rover field test.

Gulick, V. C.↗

NASA NTRS1999

An overview of vertebrate mineralization with emphasis on collagen-mineral interaction

The nucleation, growth, and development of mineral crystals through their interaction principally with collagen in normal bone and calcifying tendon have been elaborated by applying a number of different techniques for analysis of the inorganic and organic constituents of these tissues. The methods have included conventional and high voltage electron microscopy, electron diffraction, microscopic tomography and 3D image reconstruction, and atomic force microscopy. This summary presents results of these studies that have now characterized the size, shape, and aspects of the chemical nature of the crystals as well as their orientation, alignment, location, and distribution with respect to collagen. These data have provided the means for understanding more completely the formation and strength of the collagen-mineral composite present in most vertebrate calcifying tissues and, from that information, a basis for the adaptation of such tissues under mechanical constraints. In the context of the latter point, other data are given showing effects on collagen in bone cell cultures subjected to the unloading parameters of spaceflight. Implications of these results may be particularly relevant to explaining loss of bone by humans and other vertebrate animals during missions in space, during situations of extended fracture healing, long-term bedrest, physical immobilization, and related conditions. In a broader sense, the data speak to the response of bone and mineralized vertebrate tissues to changes in gravitational loading and applied mechanical forces in general.

Non-NASA Center↗