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At least 541 records · Page 30

Validation of POLDER/ADEOS data using a ground-based lidar network: Preliminary results for semi-transparent and cirrus clouds

At mid and tropical latitudes, cirrus clouds are present more than 50% of the time in satellites observations. Due to their large spatial and temporal coverage, and associated low temperatures, cirrus clouds have a major influence on the Earth-Ocean-Atmosphere energy balance through their effects on the incoming solar radiation and outgoing infrared radiation. At present the impact of cirrus clouds on climate is well recognized but remains to be asserted more precisely, for their optical and radiative properties are not very well known. In order to understand the effects of cirrus clouds on climate, their optical and radiative characteristics of these clouds need to be determined accurately at different scales in different locations i.e. latitude. Lidars are well suited to observe cirrus clouds, they can detect very thin and semi-transparent layers, and retrieve the clouds geometrical properties i.e. altitude and multilayers, as well as radiative properties i.e. optical depth, backscattering phase functions of ice crystals. Moreover the linear depolarization ratio can give information on the ice crystal shape. In addition, the data collected with an airborne version of POLDER (POLarization and Directionality of Earth Reflectances) instrument have shown that bidirectional polarized measurements can provide information on cirrus cloud microphysical properties (crystal shapes, preferred orientation in space). The spaceborne version of POLDER-1 has been flown on ADEOS-1 platform during 8 months (October 96 - June 97), and the next POLDER-2 instrument will be launched in 2000 on ADEOS-2. The POLDER-1 cloud inversion algorithms are currently under validation. For cirrus clouds, a validation based on comparisons between cloud properties retrieved from POLDER-1 data and cloud properties inferred from a ground-based lidar network is currently under consideration. We present the first results of the validation.

Chepfer, H.↗

Characterization of Quantum Frequency Processors

Frequency-bin qubits possess unique synergies with wavelength-multiplexed lightwave communications, suggesting valuable opportunities for quantum networking with the existing fiber-optic infrastructure. Although the coherent manipulation of frequency-bin states requires highly controllable multi-spectral-mode interference, the quantum frequency processor (QFP) provides a scalable path for gate synthesis leveraging standard telecom components. Here, we summarize the state of the art in experimental QFP characterization. Distinguishing between physically motivated “open box” approaches that treat the QFP as a multiport interferometer, and “black box” approaches that view the QFP as a general quantum operation, we highlight the assumptions and results of multiple techniques, including quantum process tomography of a tunable beamsplitter—to our knowledge the first full process tomography of any frequency-bin operation. Our findings should inform future characterization efforts as the QFP increasingly moves beyond proof-of-principle tabletop demonstrations toward integrated devices and deployed quantum networking experiments.

42 ENGINEERING↗

Fuzzy set methods for object recognition in space applications

Progress on the following tasks is reported: (1) fuzzy set-based decision making methodologies; (2) feature calculation; (3) clustering for curve and surface fitting; and (4) acquisition of images. The general structure for networks based on fuzzy set connectives which are being used for information fusion and decision making in space applications is described. The structure and training techniques for such networks consisting of generalized means and gamma-operators are described. The use of other hybrid operators in multicriteria decision making is currently being examined. Numerous classical features on image regions such as gray level statistics, edge and curve primitives, texture measures from cooccurrance matrix, and size and shape parameters were implemented. Several fractal geometric features which may have a considerable impact on characterizing cluttered background, such as clouds, dense star patterns, or some planetary surfaces, were used. A new approach to a fuzzy C-shell algorithm is addressed. NASA personnel are in the process of acquiring suitable simulation data and hopefully videotaped actual shuttle imagery. Photographs have been digitized to use in the algorithms. Also, a model of the shuttle was assembled and a mechanism to orient this model in 3-D to digitize for experiments on pose estimation is being constructed.

Keller, James M.↗

Meteorological analysis of the November 25 FIRE cirrus-2 case: A well-defined ridge-crest cirrus system over Oklahoma

On the morning of 25 Nov. 1991, a cirrus cloud system formed in a region extending eastward from the continental divide into central Oklahoma and southwestern Kansas. The system moved slowly eastward during the day and maintained a relatively constant scale and shape. From the satellite perspective, this cloud system had a number of morphological similarities to the 27-28 Oct. FIRE (First International Satellite Cloud Climatology Project Regional Experiment) Cirrus-1 case analyzed by Starr and Wylie. By comparison, the present case had much better rawinsonde coverage. The rawinsonde network was much more extensive and the cloud system was relatively slow moving and well-located with respect to the enhanced sounding network and the National Weather Service (NWS) Wind Profiler Network. In addition to the rawinsonde soundings (1200 and 1800 UTC on 25 Nov. and 0000 and 0600 UTC on 26 Nov.) and satellite observations, four aircraft sorties were flown in the northern portion of this cirrus cloud system from mid-morning to mid afternoon. These included microphysical-radiation profiling missions by the NCAR Sabreliner near Tulsa (about midway between COF and OUN) and the NCAR King Air near Ponca City (about 80 km upwind of Tulsa), a microphysical profiling mission by the UND Citation near Tulsa, and a NASA ER-2 overflight. Thus, very good data are available for this case although, unfortunately, the cloud system remained south of the FIRE Hub site at Coffeyville (COF) where extensive ground-based remote sensor was located. The northern edge of the cloud system was visible from COF during most of the day. Given the wealth of available in situ and remote sensing observations, the similarity to the FIRE Cirrus-1 focal case study, and the particularly good match in scale and location of the cloud system with the rawinsonde and profiler networks, analysis of this case may yield very useful results on the life-cycle of this cirrus cloud system. The quality of the meteorological description for this case was assessed based on our preliminary analysis of the rawinsonde observations.

Starr, David↗

Mechanical behavior in living cells consistent with the tensegrity model

Alternative models of cell mechanics depict the living cell as a simple mechanical continuum, porous filament gel, tensed cortical membrane, or tensegrity network that maintains a stabilizing prestress through incorporation of discrete structural elements that bear compression. Real-time microscopic analysis of cells containing GFP-labeled microtubules and associated mitochondria revealed that living cells behave like discrete structures composed of an interconnected network of actin microfilaments and microtubules when mechanical stresses are applied to cell surface integrin receptors. Quantitation of cell tractional forces and cellular prestress by using traction force microscopy confirmed that microtubules bear compression and are responsible for a significant portion of the cytoskeletal prestress that determines cell shape stability under conditions in which myosin light chain phosphorylation and intracellular calcium remained unchanged. Quantitative measurements of both static and dynamic mechanical behaviors in cells also were consistent with specific a priori predictions of the tensegrity model. These findings suggest that tensegrity represents a unified model of cell mechanics that may help to explain how mechanical behaviors emerge through collective interactions among different cytoskeletal filaments and extracellular adhesions in living cells.

NASA Discipline Cell Biology↗

A Process Model of Interpersonal Relationship Formation in Isolated and Confined Environments

Future space crews will face several challenges such as living and working in a confined environment, isolated from others. These circumstances increase the importance of interpersonal compatibility, teamwork, and team performance. The interpersonal compatibility of space crews has been and continues to be of interest to both NASA and the Institute of Biomedical Problems (IBMP), whose research informs operations for Roscosmos. In NASA-sponsored research, interpersonal compatibility has been examined in terms of how the combination of team members’ personality traits, values, and demographics shape team member relationships and team performance overtime. IBMP-sponsored research mostly has moved away from trait-based approaches toward an idiographic (in-depth, heavily descriptive) approach to researching crew interpersonal relations. This research uses software such as Personal Self-Perception and Attitudes (PSPA), network approaches to team member relations, and content analysis of interactions to assess interpersonal compatibility, and infer states and team dynamics. Our research program integrated these ideas. Our primary research aim was to develop and empirically test a process model of interpersonal relationship formation in isolated and confinement environments. We created a model, collected data from teams in an isolated and confined environment, and applied a novel analytical strategy that combines trait, state, and interaction data (i.e., relational events). We focused specifically on the formation of strained relationships in isolation and confinement—or with whom fellow crewmembers find it difficult to work.

S T Bell↗

Correlating processing variables to material properties in recycled polypropylene: A data‐driven approach

Abstract Polypropylene (PP) is one of the most widely used plastics, yet its recycling remains limited, with less than 1% of solid waste PP being reprocessed. Mechanical recycling through extrusion is the most practical method, but inconsistent reprocessing conditions introduce variability in material properties. While temperature, screw speed, and residence time influence the thermomechanical stress applied during reprocessing, there are no standardized guidelines for optimizing these parameters. This study examines how these factors shape the properties of recycled PP, using conditions designed to mimic post‐industrial recycled (PIR) scrap. Residence time was measured using colorimetric tracking and correlated with molecular weight, viscosity, and mechanical properties over multiple extrusion cycles. Data‐driven modeling, including response surface methodology, support vector machines, and artificial neural networks, identified processing temperature as the dominant factor in material degradation, followed by residence time. Mechanical properties remained stable, while viscosity decreased predictably with increasing residence time. By linking reprocessing conditions to property evolution, this study provides a method to optimize processing parameters and reduce variability in recycled PP. These findings help manufacturers improve process control, making recycled PP more predictable for reuse in manufacturing. Highlights Study of PIR‐quality PP without additives or compatibilizers. Residence time analysis shows processing temperature drives PP property changes. Mark‐Houwink enables quick molecular weight checks for quality control. Models predict mechanical and rheological shifts in reprocessing. Optimized processing parameters minimize property degradation in recycling.

Estela‐García, John E. [Polymer Engineering Center↗

Seeking regularity from irregularity: unveiling the synthesis–nanomorphology relationships of heterogeneous nanomaterials using unsupervised machine learning

Nanoscale morphology of functional materials determines their chemical and physical properties. However, despite increasing use of transmission electron microscopy (TEM) to directly image nanomorphology, it remains challenging to quantify the information embedded in TEM data sets, and to use nanomorphology to link synthesis and processing conditions to properties. We develop an automated, descriptor-free analysis workflow for TEM data that utilizes convolutional neural networks and unsupervised learning to quantify and classify nanomorphology, and thereby reveal synthesis–nanomorphology relationships in three different systems. While TEM records nanomorphology readily in two-dimensional (2D) images or three-dimensional (3D) tomograms, we advance the analysis of these images by identifying and applying a universal shape fingerprint function to characterize nanomorphology. After dimensionality reduction through principal component analysis, this function then serves as the input for morphology grouping through unsupervised learning. We demonstrate the wide applicability of our workflow to both 2D and 3D TEM data sets, and to both inorganic and organic nanomaterials, including tetrahedral gold nanoparticles mixed with irregularly shaped impurities, hybrid polymer-patched gold nanoprisms, and polyamide membranes with irregular and heterogeneous 3D crumple structures. In each of these systems, unsupervised nanomorphology grouping identifies both the diversity and the similarity of the nanomaterial across different synthesis conditions, revealing how synthetic parameters guide nanomorphology development. Our work opens possibilities for enhancing synthesis of nanomaterials through artificial intelligence and for understanding and controlling complex nanomorphology, both for 2D systems and in the far less explored case of 3D structures, such as those with embedded voids or hidden interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanical continuity and reversible chromosome disassembly within intact genomes removed from living cells

Chromatin is thought to be structurally discontinuous because it is packaged into morphologically distinct chromosomes that appear physically isolated from one another in metaphase preparations used for cytogenetic studies. However, analysis of chromosome positioning and movement suggest that different chromosomes often behave as if they were physically connected in interphase as well as mitosis. To address this paradox directly, we used a microsurgical technique to physically remove nucleoplasm or chromosomes from living cells under isotonic conditions. Using this approach, we found that pulling a single nucleolus or chromosome out from interphase or mitotic cells resulted in sequential removal of the remaining nucleoli and chromosomes, interconnected by a continuous elastic thread. Enzymatic treatments of interphase nucleoplasm and chromosome chains held under tension revealed that mechanical continuity within the chromatin was mediated by elements sensitive to DNase or micrococcal nuclease, but not RNases, formamide at high temperature, or proteases. In contrast, mechanical coupling between mitotic chromosomes and the surrounding cytoplasm appeared to be mediated by gelsolin-sensitive microfilaments. Furthermore, when ion concentrations were raised and lowered, both the chromosomes and the interconnecting strands underwent multiple rounds of decondensation and recondensation. As a result of these dynamic structural alterations, the mitotic chains also became sensitive to disruption by restriction enzymes. Ion-induced chromosome decondensation could be blocked by treatment with DNA binding dyes, agents that reduce protein disulfide linkages within nuclear matrix, or an antibody directed against histones. Fully decondensed chromatin strands also could be induced to recondense into chromosomes with pre-existing size, shape, number, and position by adding anti-histone antibodies. Conversely, removal of histones by proteolysis or heparin treatment produced chromosome decondensation which could be reversed by addition of histone H1, but not histones H2b or H3. These data suggest that DNA, its associated protein scaffolds, and surrounding cytoskeletal networks function as a structurally-unified system. Mechanical coupling within the nucleoplasm may coordinate dynamic alterations in chromatin structure, guide chromosome movement, and ensure fidelity of mitosis.

NASA Discipline Cell Biology↗

Developing Flexible, High Performance Polymers with Self-Healing Capabilities

Flexible, high performance polymers such as polyimides are often employed in aerospace applications. They typically find uses in areas where improved physical characteristics such as fire resistance, long term thermal stability, and solvent resistance are required. It is anticipated that such polymers could find uses in future long duration exploration missions as well. Their use would be even more advantageous if self-healing capability or mechanisms could be incorporated into these polymers. Such innovative approaches are currently being studied at the NASA Kennedy Space Center for use in high performance wiring systems or inflatable and habitation structures. Self-healing or self-sealing capability would significantly reduce maintenance requirements, and increase the safety and reliability performance of the systems into which these polymers would be incorporated. Many unique challenges need to be overcome in order to incorporate a self-healing mechanism into flexible, high performance polymers. Significant research into the incorporation of a self-healing mechanism into structural composites has been carried out over the past decade by a number of groups, notable among them being the University of I1linois [I]. Various mechanisms for the introduction of self-healing have been investigated. Examples of these are: 1) Microcapsule-based healant delivery. 2) Vascular network delivery. 3) Damage induced triggering of latent substrate properties. Successful self-healing has been demonstrated in structural epoxy systems with almost complete reestablishment of composite strength being achieved through the use of microcapsulation technology. However, the incorporation of a self-healing mechanism into a system in which the material is flexible, or a thin film, is much more challenging. In the case of using microencapsulation, healant core content must be small enough to reside in films less than 0.1 millimeters thick, and must overcome significant capillary and surface tension forces to flow, mix and react to achieve healing. Vascular networks small enough to fit into such films must also overcome these same flow limitations. Self-healing has also been demonstrated in ionomeric substrates such as Surlyn , wherein the heat generated by a projectile impact triggers the latent ability of this substrate to flow back to its original shape. Recent work using Diels-Alder reactions have shown promise in bringing about actual reforming of broken chemical bonds to achieve self-healing [2]. All self-healing mechanisms that rely on the use of inherent latent substrate properties require some degree of polymer chain flow to achieve any significant level of healing.

Jolley, Scott T.↗

Y-shaped tricatenar azobenzenes – functional liquid crystals with synclinic–anticlinic transitions and spontaneous helix formation

A series of achiral tricatenar rod-like molecules with a 3,5-disubstitution pattern at one end and a single alkyl chain at the other end of a rod-like azobenzene derived core is reported. Depending on temperature and alkyl chain length, these Y-shaped compounds self-assemble into different types of liquid crystalline (LC) phases, ranging from non-tilted and synclinic tilted hexatic, via non-tilted and anticlinic tilted smectic and bicontinuous cubic LC phases, to a spontaneous mirror symmetry broken isotropic liquid (Iso 1 [*]) or a related achiral liquid network phase (Iso 1 ). An additional tilted, but uniaxial smectic phase was observed at the transition between anticlinic and synclinic tilt correlation and was investigated by soft resonant X-ray scattering with respect to possible helix formation. This work provides a new concept for the design of technological interesting azobenzene based LC materials with anticlinic tilted smectic C phases (SmC a ) and with azobenzene units organized in the long range or short range helical network structures of bicontinuous cubic and chiral isotropic liquid phases, respectively. Core fluorination removes all lamellar phases, leaving only the cubic phase over wide temperature ranges, even at ambient temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure of amorphous materials in the NASICON system Na 1+x Ti 2 Si x P 3−x O 12

Abstract The structure of glasses in the sodium (Na) super-ionic conductor (NASICON) system Na 1 + x Ti 2 Si x P 3 − x O 12 with x = 0.8 and x = 1.0 was explored by combining neutron and high-energy x-ray diffraction with 29 Si, 31 P and 23 Na solid-state nuclear magnetic resonance (NMR) spectroscopy. The 29 Si magic angle spinning (MAS) NMR spectra reveal that the silica component remains fully polymerized in the form of Si 4 units, i.e. the silicon atoms are bound to four bridging oxygen atoms. The 31 P{ 23 Na} rotational echo adiabatic passage double resonance (REAPDOR) NMR data suggest that the 31 P MAS NMR line shape originates from four-coordinated P n units, where n = 1, 2 or 3 is the number of bridging oxygen atoms per phosphorus atom. These sites differ in their 31 P- 23 Na dipolar coupling strengths. The results support an intermediate range order scenario of a phosphosilicate mixed network-former glass in which the phosphate groups selectively attract the Na + modifier ions. Titanium takes a sub-octahedral coordination environment with a mean Ti–O coordination number of 5.17(4) for x = 0.8 and 4.86(4) for x = 1.0. A mismatch between the P–O and Si–O bond lengths of 8% is likely to inhibit the incorporation of silicon into the phosphorus sites of the NASICON crystal structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Learning Optimal Aerodynamic Designs

This project created a framework for efficient, accurate, and scalable deep neural network representations of design optimization problem solutions. The inputs to these DNN representations are the vector of design requirement parameters, the outputs are the optimal design variables, and the goal is to learn the map from inputs to outputs (i.e., inverse design). The team addressed the problem of the optimal shape design of aerodynamic lifting surfaces—in particular aircraft wings—using a Reynolds-Average Navier Stokes model to govern the CFD-based aerodynamic shape optimization. The inverse design map for such problems is very complex and high-dimensional, involving inputs and outputs on the order of 1000s. To approximate this inverse design map, the team developed algorithms to construct parsimonious DNN architectures, which automatically identify low-dimensional manifolds in which design requirements affect optimal shape parameters, and trained these architectures with multifidelity optimization methods. The resulting methodology accurately and automatically designs optimal aerodynamic lifting surfaces with very high accuracy (99%) at interactive speeds, of the order of milliseconds, resulting in factors of one million or more speedup relative to CFD-based design optimization.

97 MATHEMATICS AND COMPUTING↗

Comments on ocean circulation with regard to satellite altimetry

Basic features of sea surface topography are reviewed, to show those oceanographic results which may be of value to a geodetic satellite program: (1) the shape and magnitude of the large scale features of the mean sea surface, relative to a level surface; (2) the position and magnitude of the slopes across the western boundary currents, from a variety of data; (3) an estimate of the position of the geoid, tied into the U.S. leveling network; and (4) a documented change of 60 to 70 cm in mean sea level, with respect to the geoid, between the U.S. east and west coasts.

Sturges, W.↗

Report of the panel on plate motion and deformation, section 2

Given here is a panel report on the goals and objectives, requirements and recommendations for the investigation of plate motion and deformation. The goals are to refine our knowledge of plate motions, study regional and local deformation, and contribute to the solution of important societal problems. The requirements include basic space-positioning measurements, the use of global and regional data sets obtained with space-based techniques, topographic and geoid data to help characterize the internal processes that shape the planet, gravity data to study the density structure at depth and help determine the driving mechanisms for plate tectonics, and satellite images to map lithology, structure and morphology. The most important recommendation of the panel is for the implementation of a world-wide space-geodetic fiducial network to provide a systematic and uniform measure of global strain.

Bock, Yehuda↗

A Dichroic Plate with Rounded Corners for NASA’s 34m Beam Waveguide Antenna

A S/K-band frequency selective surface (FSS) or a dichroic plate is designed, manufactured and tested for use in NASA’s Deep Space Network (DSN) 34m beam waveguide (BWG) antennas. Due to its large size, the proposed dichroic incorporates a new design feature, waveguides with rounded corners to cut cost and allow ease of manufacturing the plate. The dichroic is designed using an analysis that combines the Finite Element Method (FEM) for arbitrarily shaped guides with the Method of Moments and Floquet mode theory for periodic structures. The software was verified by comparison with previously measured and computed dichroic plates. The large plate was manufactured with end-mill machining. Their RF performance was measured and is in excellent agreement with the analytical results. The dichroic has been successfully installed and in operational at three NASA Deep Space Stations.

Imbriale, William↗

Simultaneous control of the electron temperature and safety factor profiles in DIII-D using model-based optimal control techniques

Future tokamak power plants will likely operate using a single, well-defined plasma scenario, either in steady state or for very long pulse lengths. In order to enhance the robustness of the scenario, feedback controllers for a variety of plasma properties will be necessary to counteract any disturbances and ensure safe operation. However, only a limited set of actuators will be available to control many different quantities. Because of this, it is necessary to develop controllers that are able to regulate multiple plasma properties using a limited set of actuators. To this end, a controller has been developed for the simultaneous regulation of both the electron temperature and safety factor profiles in DIII-D. This algorithm uses a linear quadratic integral control synthesis approach based on a linearized model of the dynamics of the two profiles. Two neural network surrogate models, NubeamNet and MMMnet, are included to improve the fidelity of the model. Furthermore, the controller has been tested in simulation using COTSIM, and has demonstrated the ability to simultaneously track changes in both the electron temperature and safety factor targets, including changes in both the magnitude and the shape of the profiles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components. Third Annual Progress Report

Additive manufacturing (AM) of high-strength corrosion resistance alloys for nuclear energy applications, such as stainless steel and Inconel, is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Probability of crack initiation at the pore depends on size, shape, and orientation of the defect. Pulsed Infrared Thermography Imaging (PIT) provides a capability for non-destructive evaluation (NDE) of sub-surface defects in arbitrary size structures. The PIT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PIT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PIT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PIT capabilities in detecting microscopic subsurface defects in metals, and classifying shapes and orientation of pores in thermal images. For detection of microscopic defects in PIT imaging data, we have developed Spatial Temporal Denoised Thermal Source Separation (STDTSS) unsupervised machine learning (ML) image processing algorithm. We show that flat bottom hole (FBH) defects as small as 200µm in SS316 and IN718 specimens, can be detected with STDTSS algorithm. To the best of our knowledge, these are the smallest detected defects which are reported in literature. For classification of defects shapes, we have previously developed thermal tomography (TT) algorithm to obtain depth reconstructions of material defects from data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗