Results for “structure reconstruction” — Page 5

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 NTRS2011

Reconstruction of Ares I-X Integrated Vehicle Rollout Loads

The measurements taken during the Ares I-X test flight provided a unique opportunity to assess the accuracy of the models and methods used to analyze the loads and accelerations present in the planned Ares I vehicle. During the rollout of the integrated vehicle from the Vehicle Assembly Building (VAB) to the launch pad, the vehicle and its supporting structure are subjected to wind loads and the vibrations produced by the crawler-transporter (CT) that is carrying it. While the loads induced on the vehicle during this period are generally low relative to those experienced in flight, the rollout is a period of operation of primary interest to those designing both the ground support equipment and the interfaces between the launch vehicle and its supporting structure. In this paper, the methods used for reconstructing the loads during the rollout phase are described. The results generated are compared to measured values, leading to insight into the accuracy of the Ares I assessment techniques.

Chamberlain, Matthew K.↗

NASA NTRS2011

Reconstruction of Ares I-X Integrated Vehicle Rollout Loads

The measurements taken during the Ares I-X test flight provided a unique opportunity to assess the accuracy of the models and methods used to analyze the loads and accelerations present in the planned Ares I vehicle. During the rollout of the integrated vehicle from the Vehicle Assembly Building (VAB) to the launch pad, the vehicle and its supporting structure are subjected to wind loads and the vibrations produced by the crawler-transporter (CT) that is carrying it. While the loads induced on the vehicle during this period are generally low relative to those experienced in flight, the rollout is a period of operation of primary interest to those designing both the ground support equipment and the interfaces between the launch vehicle and its supporting structure. In this paper, the methods used for reconstructing the loads during the rollout phase are described. The results generated are compared to measured values, leading to insight into the accuracy of the Ares I assessment techniques.

Chamberlain, Matthew K.↗

NASA NTRS1984

Coordination of Fe, Ga and Ge in high pressure glasses by Moessbauer, Raman and X-ray absorption spectroscopy, and geological implications

For some time, it has been recognized that the structure of silicate liquids has a great bearing on such magma properties as viscosity, diffusivity, and thermal expansion and on the extrapolation of thermodynamic quantities outside of the experimentally measurable range. In this connection it is vital to know if pressure imposes changes in melt structure similar to the pressure-induced reconstructive transformations in crystals. In the present study on 1 bar and high pressure glasses, an investigation is conducted regarding the coordination of Fe(3+) in Fe silicate glasses by Moessbauer spectroscopy. Raman spectroscopy is employed to explore the coordinations of Ge(4+) in GeO2 glasses and of Ga(3+) in NaGa silicate glasses, while the coordination of Ga(3+) in NaGaSiO4 glasses is studied with the aid of methods of X-ray absorption spectroscopy.

Fleet, M. E.↗

NASA NTRS1985

The scaling of complex craters

The empirical relation between the transient crater diameter (Dg) and final crater diameter (Dr) of complex craters and basins is estimated using cumulative terrace widths, central uplift diameters, continuous ejecta radii, and transient crater reconstructions determined from lunar and terrestrial impact structures. The ratio Dg/Dr is a power law function of Dr, decreasing uniformly from unity at the diameter of the simple-complex crater morphology transition to about 0.5 for large multiring basins like Imbrium on the moon. The empirical constants in the Dg/Dr relation are interpreted physically to mean that the position of the final rim relative to the transient crater, and hence the extent of collapse, is controlled or greatly influenced by the properties of the zone of dissociated material produced by the impact shock. The continuity of the Dg/Dr relation over the entire spectrum of morphologic types from complex craters to multiring basins implies that the rims of all these structures form in the same tectonic environment despite morphologic differences.

Croft, S. K.↗

NASA NTRS1992

An Announcement by Dan Goldin

Daniel S. Goldin (NASA Administrator) announces the reconstruction of several NASA programs and management structural changes. The upcoming developments for Space Station Freedom, the Office of Space Science Applications (OSSA), and the field of Aeronautics are discussed.

Source record↗

NASA NTRS2022

Optimizing Terrain Mapping and Landing Site Detection for Autonomous UAVs

The next generation of Mars rotorcrafts requires on-board autonomous hazard avoidance landing. To this end, this work proposes a system that performs continuous multi- resolution height map reconstruction and safe landing spot detection. Structure-from-Motion measurements are aggregated in a pyramid structure using a novel Optimal Mixture of Gaus- sians formulation that provides a comprehensive uncertainty model. Our multiresolution pyramid is built more efficiently and accurately than past work by decoupling pyramid filling from the measurement updates of different resolutions.To detect the safest landing location, after an optimized hazard segmentation, we use a mean shift algorithm on multiple distance transform peaks to account for terrain roughness and uncertainty. The benefits of our contributions are evaluated on real and synthetic flight data.

Brockers, Roland↗

NASA NTRS1994

Structural analysis of airborne flux estimates over a region

Aircraft-based observations of turbulence fields of velocity, moisture, and temperature are used to study coherent turbulent structures that dominate turbulent transfer of moisture and heat above three different eco-systems. Flux traces are defragmented, to reconstruct the presumed full size (along the sampled transect) of these structures, and flux traces are simplified by elimination of those that contribute negligibly to the flux estimate. Structures are analyzed in terms of size, spatial distribution, and contribution to the flux, in the four 'quadrant' modes of eddy-covariance transfer (excess up/down and deficit up/down). The effect of nonlinear detrending of moisture and temperature data on this 'structural analysis,' over surfaces with heterogeneous surface wetness, is also examined. Results over grassland, wetland, and moist and dry agricultural land, show that nonlinear detrending may provide a more physically realistic description of structures. Significant differences are observed between structure size and associated relative flux contribution, between moist and dry areas, with smaller structures playing a more important role over the moist areas. Structure size generally increases with height, as spatial reorganization from smaller structures into larger ones takes place. This coincides with a gradual loss of surface 'signature' (position and clustering of plumes above localized source areas). The data are expected to provide a basis for an eventual statistical description of boundary-layer transfer events , and help to interpret the link between boundary-layer transfer and hydrological surface conditions.

Caramori, Paulo↗

NASA NTRSDate not supplied

Using Machine Learning to Infer Material Properties of Debris Fragments from X-ray Images in the DebriSat Project

The DebriSat project is a collaboration effort with the NASA Orbital Debris Program Office, the U.S. Space Force Space Systems Command Center, The Aerospace Corporation, and the University of Florida. To date, over 200,000 fragments from this ground-based, hypervelocity impact experiment have been collected, and processing is underway to determine their physical characteristics, such as material, shape, color, characteristic length, and average cross-sectional area. The x-ray process is primarily used to identify the location of the fragments and estimated size for extraction, so that these physical characteristics can be assessed. This paper proposes a machine learning-based approach to characterize materials from x-ray images of debris fragments embedded in soft-catch foam used in the DebriSat project. The novel methodology discussed in this paper will highlight the use of x-ray imagery data to characterize these fragments without extraction or a human-in-the-loop. Both supervised and unsupervised machine learning techniques are utilized with this approach to infer the physical parameters of the fragments embedded in the soft-catch foam panels used in the impact experiment based on x-ray images of the foam panels. Additionally, 3D reconstructions of the extracted fragments are created with images taken from two different angles using the structure from motion (SfM) method. The characteristic lengths and shape from the 3D reconstruction, alongside the physical characteristics of the debris, are used in the inference of the material type. To develop and test the approach, a dataset of x-ray images of debris fragments of varying sizes and materials is collected. Supervised learning methods such as convolutional neural networks (CNNs), support vector machines (SVM), decision trees, and random forest classifiers are used due to the high-dimensional feature spaces of the debris and nonlinear decision boundaries for material categorization. Given the limited pre-labeled data of embedded debris materials smaller than 10 mm, unsupervised machine learning techniques such as clustering algorithms and autoencoders are used, in addition to supervised learning methods. The clustering algorithms group similar fragments together based on their physical properties, and autoencoders reduce the dimensionality of the x ray images and extract relevant features. The performance of the proposed approach's is analyzed using a range of statistical methods, including confusion matrices, receiver operating characteristic curves, and precision-recall curves. The results are compared with those obtained using a baseline approach that relies on manual identification and classification of debris fragments. To evaluate the effectiveness of different machine learning methods, statistical tests such as t-tests, ANOVA, and cross-validation are performed, comparing the performance of CNNs, SVMs, clustering algorithms, and autoencoders. Additional analysis needs to be conducted to identify any sources of bias or variability that may affect the results, such as variations in imaging conditions or fragmentation patterns. Other topics explored are limitations, refinements, and the potential use of semi-supervised learning techniques, such as self-training to label unlabeled datasets and co-training using x-ray images taken from two different angles as two different models.

Saik Anam Siam↗

NASA NTRS2023

Using Machine Learning to Infer Material Properties of Debris Fragments from X-ray Images in the DebriSat Project

The DebriSat project is a collaboration effort with the NASA Orbital Debris Program Office, the U.S. Space Force Space Systems Command Center, The Aerospace Corporation, and the University of Florida. To date, over 200,000 fragments from this ground-based, hypervelocity impact experiment have been collected, and processing is underway to determine their physical characteristics, such as material, shape, color, characteristic length, and average cross-sectional area. The x-ray process is primarily used to identify the location of the fragments and estimated size for extraction, so that these physical characteristics can be assessed. This paper proposes a machine learning-based approach to characterize materials from x-ray images of debris fragments embedded in soft-catch foam used in the DebriSat project. The novel methodology discussed in this paper will highlight the use of x-ray imagery data to characterize these fragments without extraction or a human-in-the-loop. Both supervised and unsupervised machine learning techniques are utilized with this approach to infer the physical parameters of the fragments embedded in the soft-catch foam panels used in the impact experiment based on x-ray images of the foam panels. Additionally, 3D reconstructions of the extracted fragments are created with images taken from two different angles using the structure from motion (SfM) method. The characteristic lengths and shape from the 3D reconstruction, alongside the physical characteristics of the debris, are used in the inference of the material type. To develop and test the approach, a dataset of x-ray images of debris fragments of varying sizes and materials is collected. Supervised learning methods such as convolutional neural networks (CNNs), support vector machines (SVM), decision trees, and random forest classifiers are used due to the high-dimensional feature spaces of the debris and nonlinear decision boundaries for material categorization. Given the limited pre-labeled data of embedded debris materials smaller than 10 mm, unsupervised machine learning techniques such as clustering algorithms and autoencoders are used, in addition to supervised learning methods. The clustering algorithms group similar fragments together based on their physical properties, and autoencoders reduce the dimensionality of the x ray images and extract relevant features. The performance of the proposed approach's is analyzed using a range of statistical methods, including confusion matrices, receiver operating characteristic curves, and precision-recall curves. The results are compared with those obtained using a baseline approach that relies on manual identification and classification of debris fragments. To evaluate the effectiveness of different machine learning methods, statistical tests such as t-tests, ANOVA, and cross-validation are performed, comparing the performance of CNNs, SVMs, clustering algorithms, and autoencoders. Additional analysis needs to be conducted to identify any sources of bias or variability that may affect the results, such as variations in imaging conditions or fragmentation patterns. Other topics explored are limitations, refinements, and the potential use of semi-supervised learning techniques, such as self-training to label unlabeled datasets and co-training using x-ray images taken from two different angles as two different models.

Saik Anam Siam↗

NASA NTRS2024

A Feasibility Study of 4-D Tomography of Soft X-ray Magnetosheath Emissivities Using Multi-Spacecraft Measurements

Upcoming heliophysics missions utilize state-of-the-art wide field-of-view (FOV) imaging technology to measure and investigate the space plasma environment on a global scale. At Earth, remote sensing of soft X-ray emissions, which are generated via the charge exchange interaction between heavy solar wind ions and exospheric neutral atoms, is a promising means to investigate the global magnetosheath structure, its response to varying solar wind conditions, and the spatiotemporal properties of the dayside magnetic reconnection. Data analysis techniques such as optical tomography can provide additional structural and time-varying information from the observed target and thus enhance the mission’s scientific return. In this work, we simulate multiple and simultaneous observations of the dayside magnetosphere using soft X-ray imagers located at long-distance vantage points to reconstruct the time-dependent, three-dimensional (3-D) structure of the magnetosheath using a dynamic tomographic approach. The OpenGCCM MHD model is used to simulate the time-varying response of the magnetosheath to solar wind conditions and, subsequently, generate synthetic soft X-ray images from multiple spacecraft vantage points separated along a common orbit. A detailed analysis is then performed to identify the nominal set of spacecraft that produces the highest fidelity tomographic reconstruction of the magnetopause. This work aims to (i) demonstrate, for the first time, the use of dynamic tomography to retrieve the time-varying magnetosheath structure and (ii) identify a nominal mission design for multi-spacecraft configurations aiming for optical tomography.

3-D/4_d tomography↗

NASA NTRS2016

SIRENA Software for Athena X-IFU Event Reconstruction

The X-ray Observatory Athena was proposed in April 2014 as the mission to implement the science theme "The Hot and Energetic Universe" selected by ESA for L2 (the second Large-class mission in ESAs Cosmic Vision science programme). One of the two X-ray detectors designed to be onboard Athena is X-IFU, a cryogenic microcalorimeter based on Transition Edge Sensor (TES) technology that will provide spatially resolved high-resolution spectroscopy. X-IFU will be developed by an international consortium led by IRAP (PI), SRON (co-PI) and IAPS/INAF (co-PI) and involving ESA Member States, Japan and the United States. In Spain, IFCA (CSIC-UC) has an anticipated contribution to X-IFU through the Digital Readout Electronics (DRE) unit, in particular in the Event Processor Subsytem. For this purpose and in collaboration with the Athena end-to-end simulations team, we are currently developing the SIRENA package as part of the publicly available SIXTE end-to-end simulator. SIRENA comprises a set of processing algorithms aimed at recognizing, from a noisy signal, the intensity pulses generated by the absorption of the X-ray photons, to lately reconstruct their energy, position and arrival time. This poster describes the structure of the package and the different algorithms currently implemented as well as their comparative performance in the energy resolution achieved in the reconstruction of the instrument events.

M T Ceballos↗

NASA NTRS1979

State and model error estimation for distributed parameter systems

In-flight estimation of large structure model errors in order to detect inevitable deficiencies in large structure controller/estimator models is discussed. Such an estimation process is particularly applicable in the area of shape control system design required to maintain a prescribed static structural shape and, in addition, suppress dynamic disturbances due to the vehicle vibrational modes. The paper outlines a solution to the problem of static shape estimation where the vehicle shape must be reconstructed from a set of measurements discretely located throughout the structure. The estimation process is based on the principle of least-squares that inherently contains the definition and explicit computation of model error estimates that are optimal in some sense. Consequently, a solution is provided for the problem of estimation of static model errors (e.g., external loads). A generalized formulation applicable to distributed parameters systems is first worked out and then applied to a one-dimensional beam-like structural configuration.

Rodriguez, G.↗

NASA NTRS1993

Mathmatical modeling for diffractive optics

We consider a 'diffractive optic' to be a biperiodic surface separating two half-spaces, each having constant constitutive parameters; within a unit cell of the periodic surface and across the transition zone between the two half-spaces, the constitutive parameters can be a continuous, complex-valued function. Mathematical models for diffractive optics have been developed, and implemented as numerical codes, both for the 'direct' problem and for the 'inverse' problem. In problems of the 'direct' class, the diffractive optic is specified, and the full set of Maxwell's equations is cast in a variational form and solved numerically by a finite element approach. This approach is well-posed in the sense that existence and uniqueness of the solution can be proved and specific convergence conditions can be derived. An example of a metallic grating at a Wood anomaly is presented as a case where other approaches are known to have convergence problems. In problems of the 'inverse' class, some information about the diffracted field (e.g., the far-field intensity) is given, and the problem is to find the periodic structure in some optimal sense. Two approaches are described: phase reconstruction in the far-field approximation; and relaxed optimal design based on the Helmholtz equation. Practical examples are discussed for each approach to the inverse problem, including array generators in the far-field case and antireflective structures for the relaxed optimal design.

Dobson, David↗

NASA NTRS2012

Longitudinal Differences of Ionospheric Vertical Density Distribution and Equatorial Electrodynamics

Accurate estimation of global vertical distribution of ionospheric and plasmaspheric density as a function of local time, season, and magnetic activity is required to improve the operation of space-based navigation and communication systems. The vertical density distribution, especially at low and equatorial latitudes, is governed by the equatorial electrodynamics that produces a vertical driving force. The vertical structure of the equatorial density distribution can be observed by using tomographic reconstruction techniques on ground-based global positioning system (GPS) total electron content (TEC). Similarly, the vertical drift, which is one of the driving mechanisms that govern equatorial electrodynamics and strongly affect the structure and dynamics of the ionosphere in the low/midlatitude region, can be estimated using ground magnetometer observations. We present tomographically reconstructed density distribution and the corresponding vertical drifts at two different longitudes: the East African and west South American sectors. Chains of GPS stations in the east African and west South American longitudinal sectors, covering the equatorial anomaly region of meridian approx. 37 deg and 290 deg E, respectively, are used to reconstruct the vertical density distribution. Similarly, magnetometer sites of African Meridian B-field Education and Research (AMBER) and INTERMAGNET for the east African sector and South American Meridional B-field Array (SAMBA) and Low Latitude Ionospheric Sensor Network (LISN) are used to estimate the vertical drift velocity at two distinct longitudes. The comparison between the reconstructed and Jicamarca Incoherent Scatter Radar (ISR) measured density profiles shows excellent agreement, demonstrating the usefulness of tomographic reconstruction technique in providing the vertical density distribution at different longitudes. Similarly, the comparison between magnetometer estimated vertical drift and other independent drift observation, such as from VEFI onboard Communication/Navigation Outage Forecasting System (C/NOFS) satellite and JULIA radar, is equally promising. The observations at different longitudes suggest that the vertical drift velocities and the vertical density distribution have significant longitudinal differences; especially the equatorial anomaly peaks expand to higher latitudes more in American sector than the African sector, indicating that the vertical drift in the American sector is stronger than the African sector.

total electron content↗

NASA NTRS1973

Some digital techniques for enhancing ERTS imagery

In addition to the use of simple contrast stretching to improve visibility of detail, axis rotation and ratioing have been found useful for certain applications. These processes allow a considerably greater contrast stretch than is possible on normal images, with consequent increased separability of different materials. They have inherent advantages over classifier techniques for geologic studies, as they allow the interpreter to take into account other factors such as context and structure before interpreting boundaries between units. Color images reconstructed from these pictures display color variations among various materials unattainable by any combination of normal photography.

Billingsley, F. C.↗

NASA NTRS1976

Cardiovascular and pulmonary dynamics by quantitative imaging

The accuracy and range of studies on cardiovascular and pulmonary functions can be greatly facilitated if the motions of the underlying organ systems throughout individual cycles can be directly visualized and readily measured with minimum or preferably no effect on these motions. Achievement of this objective requires development of techniques for quantitative noninvasive or minimally invasive dynamic and stop-action imaging of the organ systems. A review of advances in dynamic quantitative imaging of moving organs reveals that the revolutionary value of cross-sectional and three-dimensional images produced by various types of radiant energy such as X-rays and gamma rays, positrons, electrons, protons, light, and ultrasound for clinical diagnostic and biomedical research applications is just beginning to be realized. The fabrication of a clinically useful cross-section reconstruction device with sensing capabilities for both anatomical structural composition and chemical composition may be possible and awaits future development.

Wood, E. H.↗

NASA NTRS1981

MAGSAT anomaly map and continental drift

Anomaly maps of high quality are needed to display unambiguously the so called long wave length anomalies. The anomalies were analyzed in terms of continental drift and the nature of their sources is discussed. The map presented confirms the thinness of the oceanic magnetized layer. Continental magnetic anomalies are characterized by elongated structures generally of east-west trend. Paleomagnetic reconstruction shows that the anomalies found in India, Australia, and Antarctic exhibit a fair consistency with the African anomalies. It is also shown that anomalies are locked under the continents and have a fixed geometry.

Lemouel, J. L.↗