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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14

Architecture of Pseudomonas aeruginosa glutamyl-tRNA synthetase defines a subfamily of dimeric class Ib aminoacyl-tRNA synthetases

The aminoacyl-tRNA synthetases (AaRSs) are an ancient family of structurally diverse enzymes that are divided into two major classes. The functionalities of most AaRSs are inextricably linked to their oligomeric states. While GluRSs were previously classified as monomers, the current investigation reveals that the form expressed in Pseudomonas aeruginosa is a rotationally pseudosymmetrical homodimer featuring intersubunit tRNA binding sites. Both subunits display a highly bent, "pipe strap" conformation, with the anticodon binding domain directed toward the active site. The tRNA binding sites are similar in shape to those of the monomeric GluRSs, but are formed through an approximately 180-degree rotation of the anticodon binding domains and dimerization via the anticodon and D-arm binding domains. As a result, each anticodon binding domain is poised to recognize the anticodon loop of a tRNA bound to the adjacent protomer. Additionally, the anticodon binding domain has an α-helical C-terminal extension containing a conserved lysine-rich consensus motif positioned near the predicted location of the acceptor arm, suggesting dual functions in tRNA recognition. The unique architecture of PaGluRS broadens the structural diversity of the GluRS family, and member synthetases of all bacterial AaRS subclasses have now been identified that exhibit oligomerization.

Fenwick, Michael K↗

Application of ERTS and EREP images to geologic investigations of the basin and range: Colorado Plateau boundary in northwestern and north central Arizona

The author has identified the following significant results. Regional mapping using ERTS-1 images has led to the recognition of two parallel northeast-trending systems of normal faults, the Bright Angel and Mesa Butte fault systems, each of which can be traced at least 100 miles. Many eruptive centers appear to be localized along these fault systems or along their extensions. The faults are chiefly observed in Phanerozoic rocks and have minor displacement, but are interpreted to reflect fault zones of major displacement in the crystalline Precambrian basement. The location of epicenters of recent earthquakes and reports of earthquakes by residents in the region suggest that the Bright Angel and Mesa Butte fault systems are currently active.

Goetz, A. F. H.↗

Market Assessment of Forward-Looking Turbulence Sensing Systems

In recognition of the importance of turbulence mitigation as a tool to improve aviation safety, NASA's Aviation Safety Program developed a Turbulence Detection and Mitigation Sub-element. The objective of this effort is to develop highly reliable turbulence detection technologies for commercial transport aircraft to sense dangerous turbulence with sufficient time warning so that defensive measures can be implemented and prevent passenger and crew injuries. Current research involves three forward sensing products to improve the cockpit awareness of possible turbulence hazards. X-band radar enhancements will improve the capabilities of current weather radar to detect turbulence associated with convective activity. LIDAR (Light Detection and Ranging) is a laser-based technology that is capable of detecting turbulence in clear air. Finally, a possible Radar-LIDAR hybrid sensor is envisioned to detect the full range of convective and clear air turbulence. To support decisions relating to the development of these three forward-looking turbulence sensor technologies, the objective of this study was defined as examination of cost and implementation metrics. Tasks performed included the identification of cost factors and certification issues, the development and application of an implementation model, and the development of cost budget/targets for installing the turbulence sensor and associated software devices into the commercial transport fleet.

Kauffmann, Paul↗

Self Diagnostic Accelerometer Testing on the C-17 Aircraft

The self diagnostic accelerometer (SDA) developed by the NASA Glenn Research Center was tested for the first time in an aircraft engine environment as part of the Vehicle Integrated Propulsion Research (VIPR) program. The VIPR program includes testing multiple critical flight sensor technologies. One such sensor, the accelerometer, measures vibrations to detect faults in the engine. In order to rely upon the accelerometer, the health of the accelerometer must be ensured. The SDA is a sensor system designed to actively determine the accelerometer structural health and attachment condition, in addition to vibration measurements. The SDA uses a signal conditioning unit that sends an electrical chirp to the accelerometer and recognizes changes in the response due to changes in the accelerometer health and attachment condition. To demonstrate the SDAs flight worthiness and robustness, multiple SDAs were mounted and tested on a C-17 aircraft engine. The engine test conditions varied from engine off, to idle, to maximum power. The SDA attachment conditions were varied from fully tight to loose. The newly developed SDA health algorithm described herein uses cross correlation pattern recognition to discriminate a healthy from a faulty SDA. The VIPR test results demonstrate for the first.

Tokars, Roger P.↗

An optimal sensing strategy for recognition and localization of 3-D natural quadric objects

An optimal sensing strategy for an optical proximity sensor system engaged in the recognition and localization of 3-D natural quadric objects is presented. The optimal sensing strategy consists of the selection of an optimal beam orientation and the determination of an optimal probing plane that compose an optimal data collection operation known as an optimal probing. The decision of an optimal probing is based on the measure of discrimination power of a cluster of surfaces on a multiple interpretation image (MII), where the measure of discrimination power is defined in terms of a utility function computing the expected number of interpretations that can be pruned out by a probing. An object representation suitable for active sensing based on a surface description vector (SDV) distribution graph and hierarchical tables is presented. Experimental results are shown.

Lee, Sukhan↗

An evaluation of three-dimensional sensors for the extravehicular activity helper/retreiver

The Extravehicular Activity Retriever/Helper (EVAHR) is a robotic device currently under development at the NASA Johnson Space Center that is designed to fetch objects or to assist in retrieving an astronaut who may have become inadvertently de-tethered. The EVAHR will be required to exhibit a high degree of intelligent autonomous operation and will base much of its reasoning upon information obtained from one or more three-dimensional sensors that it will carry and control. At the highest level of visual cognition and reasoning, the EVAHR will be required to detect objects, recognize them, and estimate their spatial orientation and location. The recognition phase and estimation of spatial pose will depend on the ability of the vision system to reliably extract geometric features of the objects such as whether the surface topologies observed are planar or curved and the spatial relationships between the component surfaces. In order to achieve these tasks, accurate sensing of the operational environment and objects in the environment will therefore be critical. The qualitative and quantitative results of empirical studies of three sensors that are capable of providing three-dimensional information to the EVAHR, but using completely different hardware approaches are documented. The first of these devices is a phase shift laser with an effective operating range (ambiguity interval) of approximately 15 meters. The second sensor is a laser triangulation system designed to operate at much closer range and to provide higher resolution images. The third sensor is a dual camera stereo imaging system from which range images can also be obtained. The remainder of the report characterizes the strengths and weaknesses of each of these systems relative to quality of data extracted and how different object characteristics affect sensor operation.

Magee, Michael↗

Switchable client specificity in a dual functional chaperone coordinates light-harvesting complex biogenesis

The proper assembly of light-harvesting complexes (LHCs) is critical for photosynthesis and requires the biogenesis of light-harvesting chlorophylla,b-binding proteins (LHCPs) to be coordinated with chlorophyll (Chl) biosynthesis. The mechanism underlying this coordination is not well understood. Here, we show that a conserved molecular chaperone, chloroplast signal recognition particle 43-kDa protein (cpSRP43), provides a molecular thermostat that helps maintain this coordination. cpSRP43 undergoes a conformational rearrangement between a well-folded closed state and a partially disordered open state. Closed cpSRP43 is dedicated to the biogenesis of LHCPs, whereas open cpSRP43 protects multiple Chl biosynthesis enzymes from heat-induced destabilization. Rising temperature shifts cpSRP43 to the open state, enabling it to protect heat-destabilized Chl biosynthesis enzymes. Our results reveal the molecular basis of a posttranslational mechanism for the thermoadaptation of LHC biogenesis. They also demonstrate how an adenosine triphosphate–independent chaperone uses conformational dynamics to switch its activity and client selectivity, thereby adapting to different proteostatic demands under shifting environmental conditions.

Science & Technology - Other Topics↗

Spiking Neurons for Analysis of Patterns

Artificial neural networks comprising spiking neurons of a novel type have been conceived as improved pattern-analysis and pattern-recognition computational systems. These neurons are represented by a mathematical model denoted the state-variable model (SVM), which among other things, exploits a computational parallelism inherent in spiking-neuron geometry. Networks of SVM neurons offer advantages of speed and computational efficiency, relative to traditional artificial neural networks. The SVM also overcomes some of the limitations of prior spiking-neuron models. There are numerous potential pattern-recognition, tracking, and data-reduction (data preprocessing) applications for these SVM neural networks on Earth and in exploration of remote planets. Spiking neurons imitate biological neurons more closely than do the neurons of traditional artificial neural networks. A spiking neuron includes a central cell body (soma) surrounded by a tree-like interconnection network (dendrites). Spiking neurons are so named because they generate trains of output pulses (spikes) in response to inputs received from sensors or from other neurons. They gain their speed advantage over traditional neural networks by using the timing of individual spikes for computation, whereas traditional artificial neurons use averages of activity levels over time. Moreover, spiking neurons use the delays inherent in dendritic processing in order to efficiently encode the information content of incoming signals. Because traditional artificial neurons fail to capture this encoding, they have less processing capability, and so it is necessary to use more gates when implementing traditional artificial neurons in electronic circuitry. Such higher-order functions as dynamic tasking are effected by use of pools (collections) of spiking neurons interconnected by spike-transmitting fibers. The SVM includes adaptive thresholds and submodels of transport of ions (in imitation of such transport in biological neurons). These features enable the neurons to adapt their responses to high-rate inputs from sensors, and to adapt their firing thresholds to mitigate noise or effects of potential sensor failure. The mathematical derivation of the SVM starts from a prior model, known in the art as the point soma model, which captures all of the salient properties of neuronal response while keeping the computational cost low. The point-soma latency time is modified to be an exponentially decaying function of the strength of the applied potential. Choosing computational efficiency over biological fidelity, the dendrites surrounding a neuron are represented by simplified compartmental submodels and there are no dendritic spines. Updates to the dendritic potential, calcium-ion concentrations and conductances, and potassium-ion conductances are done by use of equations similar to those of the point soma. Diffusion processes in dendrites are modeled by averaging among nearest-neighbor compartments. Inputs to each of the dendritic compartments come from sensors. Alternatively or in addition, when an affected neuron is part of a pool, inputs can come from other spiking neurons. At present, SVM neural networks are implemented by computational simulation, using algorithms that encode the SVM and its submodels. However, it should be possible to implement these neural networks in hardware: The differential equations for the dendritic and cellular processes in the SVM model of spiking neurons map to equivalent circuits that can be implemented directly in analog very-large-scale integrated (VLSI) circuits.

Huntsberger, Terrance↗

Self Diagnostic Accelerometer Ground Testing on a C-17 Aircraft Engine

The self diagnostic accelerometer (SDA) developed by the NASA Glenn Research Center was tested for the first time in an aircraft engine environment as part of the Vehicle Integrated Propulsion Research (VIPR) program. The VIPR program includes testing multiple critical flight sensor technologies. One such sensor, the accelerometer, measures vibrations to detect faults in the engine. In order to rely upon the accelerometer, the health of the accelerometer must be ensured. Sensor system malfunction is a significant contributor to propulsion in flight shutdowns (IFSD) which can lead to aircraft accidents when the issue is compounded with an inappropriate crew response. The development of the SDA is important for both reducing the IFSD rate, and hence reducing the rate at which this component failure type can put an aircraft in jeopardy, and also as a critical enabling technology for future automated malfunction diagnostic systems. The SDA is a sensor system designed to actively determine the accelerometer structural health and attachment condition, in addition to making vibration measurements. The SDA uses a signal conditioning unit that sends an electrical chirp to the accelerometer and recognizes changes in the response due to changes in the accelerometer health and attachment condition. In an effort toward demonstrating the SDAs flight worthiness and robustness, multiple SDAs were mounted and tested on a C-17 aircraft engine. The engine test conditions varied from engine off, to idle, to maximum power. The two SDA attachment conditions used were fully tight and loose. The newly developed SDA health algorithm described herein uses cross correlation pattern recognition to discriminate a healthy from a faulty SDA. The VIPR test results demonstrate for the first time the robustness of the SDA in an engine environment characterized by high vibration levels.

Tokars, Roger P.↗

A Decade of Neural Networks: Practical Applications and Prospects

The Jet Propulsion Laboratory Neural Network Workshop, sponsored by NASA and DOD, brings together sponsoring agencies, active researchers, and the user community to formulate a vision for the next decade of neural network research and application prospects. While the speed and computing power of microprocessors continue to grow at an ever-increasing pace, the demand to intelligently and adaptively deal with the complex, fuzzy, and often ill-defined world around us remains to a large extent unaddressed. Powerful, highly parallel computing paradigms such as neural networks promise to have a major impact in addressing these needs. Papers in the workshop proceedings highlight benefits of neural networks in real-world applications compared to conventional computing techniques. Topics include fault diagnosis, pattern recognition, and multiparameter optimization.

Kemeny, Sabrina E.↗

Anomalous meridional thermospheric neutral winds in the AE-E NATE data: Effects of the equatorial nighttime pressure bulge

The work described here makes it possible to identify anomalous wind behavior such as the nighttime meridional wind abatements that occur at F-region heights. A new analysis technique uses a simple empirical wind model to simulate measurements of 'normal' winds (as measured by the Neutral Atmosphere and Temperature Experiment (NATE) that flew on the Atmosphere Explorer-E (AE-E)) to highlight anomalous wind measurements made by the satellite while in circular orbits at 270-290 km altitude. Our approach is based on the recognition that the 'in orbit' wind variation must show the combined effects of the diurnal wind variation as seen from the ground with the latitude variation of the satellite orbit. For the data period 77250-78035 examined thus far, the wind abatement always occurred with a corresponding pressure or temperature maximum, and was detected on 12 out of the 36 nights with data. This study has revealed that the wind abatement occur only during or shortly after increases in solar extreme ultraviolet (EUV) flux, as indicated by daily radio flux measurements. In the past, nighttime wind reversals at mid-latitudes have been associated with increased geomagnetic activity. This study indicates that intensified solar EUV heating may be responsible for anomalous thermospheric nighttime winds at mid-latitudes.

Goembel, L.↗

Template switching between PNA and RNA oligonucleotides

The origin of the RNA world is not easily understood, as effective prebiotic syntheses of the components of RNA, the beta-ribofuranoside-5'-phosphates, are hard to envisage. Recognition of this difficulty has led to the proposal that other genetic systems, the components of which are more easily formed, may have preceded RNA. This raises the question of how transitions between one genetic system and another could occur. Peptide nucleic acid (PNA) resembles RNA in its ability to form double-helical complexes stabilized by Watson-Crick hydrogen bonding between adenine and thymine and between cytosine and guanine, but has a backbone that is held together by amide rather than by phosphodiester bonds. Oligonucleotides bases on RNA are known to act as templates that catalyse the non-enzymatic synthesis of their complements from activated mononucleotides, we now show that RNA oligonucleotides facilitate the synthesis of complementary PNA strands and vice versa. This suggests that a transition between different genetic systems can occur without loss of information.

NASA Discipline Exobiology↗

Structural Analysis of 23S rRNA Methylating Enzyme Cfr Reveals RNA-Binding Determinants for Methylation Regiospecificity and Antibiotic Resistance

The 23S rRNA methylating enzyme Cfr, found in pathogens including Staphylococcus aureus, Clostridium difficile, Escherichia coli, and Klebsiella pneumoniae, confers resistance to phenicols, lincosamides, oxazolidinones (including linezolid), pleuromutilins, and streptogramins A (the PhLOPS A phenotype). Cfr catalyzes methylation of the C8 position of the A2503 base in 23S rRNA, the recognition site of the above antibiotic classes. Along with the RlmN housekeeping enzyme, Cfr can also promote methylation of the C2 position of the same base. The molecular and structural basis of Cfr’s dual substrate specificity is not known, which hinders our ability to design Cfr-targeting inhibitors necessary to curb PhLOPS A resistance. Here, we present the first crystal structure of Cfr and a detailed analysis of its possible interactions with rRNA. Using structure-guided mutagenesis, mass spectrometry analysis of in cellulo 23S rRNA methylated species, and in cellulo resistance studies, we identify the key amino acids essential for Cfr methylation and multidrug resistance activity. In particular, we found that Cfr’s Q329 residue is important for C8- specific methylation. These data provide a framework for further studies of the biochemistry, structure, and inhibition of this important resistance determinant.

AlphaFold↗

Understanding and Verifying Neural Networks

Deep Neural Networks (DNNs) have gained immense popularity in recent times and have widespread use in applications such as image classification, sentiment analysis, speech recognition and also in safety-critical applications such as autonomous driving. However, they suffer limitations such as lack of explainability and robustness which raise safety and security concerns in their usage. Further, the complex structure and large input spaces of DNNs act as an impediment to thorough verification and testing. The SafeDNN project at the Robust Software Engineering (RSE) group at NASA aims at exploring techniques to ensure that systems that use deep neural networks are safe, robust and interpretable. In this talk, I will be presenting our technique Prophecy that automatically infers formal properties of deep neural network models. The tool extracts patterns based on neuron activations as preconditions that imply certain desirable output properties of the model. I would be highlighting case studies that use Prophecy in obtaining explanations for network decisions, understanding correct and incorrect behavior, providing formal guarantees wrt safety and robustness, and debugging neural network models. We have applied the tool on image classification networks, neural network controllers providing turn advisories in unmanned aircrafts, regression models used for autonomous center-line tracking in aircrafts and neural network object detectors

Deep Neural Networks↗

Arctic and Antarctic Analogs for Planetary Surface Traverses

The proposed paper summarizes the workshop presentations and discusses several of the key findings or lessons including: (1) A recognition that NASA s current approach for long duration planetary surface operations has fundamental differences from any of the operational approaches described by the invited speakers. These approaches drive the crew size and skill mix to accomplish basic objectives and, in turn, drive the logistical pyramid needed to support these operations. NASA will review the operational approaches of the organizations represented to understand the differentiating factors. NASA will then decide if it should alter its current approach to surface exploration. (2) There are potential parallels between key characteristics of the systems used for exploration in these environments, such as heated volume as an analog for pressurized volume or energy usage for various activities. NASA will look at these characteristics to identify which could help with preliminary planning and gather raw data from the presenters to model these characteristics. (3) New technologies are being applied and design approaches are being tailored to take advantage of these technologies on both side. Interactions between these two communities has begun or is expanding to understand how these new technologies are being leveraged: NASA habitation designers are exchanging ideas and approaches with the Antarctic station designers; Antarctic support

Hoffman, Stephen J.↗

NASA Tech Briefs, January 2011

The topics include: 1) Distributed Aerodynamic Sensing and Processing Toolbox; 2) Collaborative Supervised Learning for Sensor Networks; 3) Hazard Detection Software for Lunar Landing; 4) Onboard Nonlinear Engine Sensor and Component Fault Diagnosis and Isolation Scheme; 5) Network-Capable Application Process and Wireless Intelligent Sensors for ISHM; 6) Interface Supports Multiple Broadcast Transceivers for Flight Applications; 7) FPGA Sequencer for Radar Altimeter Applications; 8) Miniature Sapphire Acoustic Resonator - MSAR; 9) Process-Hardened, Multi-Analyte Sensor for Characterizing Rocket Plume Constituents; 10) SAD5 Stereo Correlation Line-Striping in an FPGA; 11) Hybrid Composite Cryogenic Tank Structure; 12) Nanoscale Deformable Optics; 13) Reliability-Based Design Optimization of a Composite Airframe Component; 14) Zinc Oxide Nanowire Interphase for Enhanced Lightweight Polymer Fiber Composites; 15) Plasma Igniter for Reliable Ignition of Combustion in Rocket Engines; 16) Wire Test Grip Fixture; 17) A Sub-Hertz, Low-Frequency Vibration Isolation Platform; 18) Carbon Nanofibers Synthesized on Selective Substrates for Nonvolatile Memory and 3D Electronics; 19) Nanoparticle/Polymer Nanocomposite Bond Coat or Coating; 20) High-Resolution Wind Measurements for Offshore Wind Energy Development; 21) Spring Tire; 22) Marsviewer 2008; 23) Mission Services Evolution Center Message Bus; 24) Major Constituents Analysis for the Vehicle Cabin Atmosphere Monitor; 25) Astronaut Health Participant Summary Application; 26) Adaption of the AMDIS Method to Flight Status on the VCAM Instrument; 27) Natural Language Interface for Safety Certification of Safety-Critical Software; 28) Cryogenic Caging for Science Instrumentation; 29) Wide-Range Neutron Detector for Space Nuclear Applications; 30) In Situ Guided Wave Structural Health Monitoring System; 31) Multiplexed Energy Coupler for Rotating Equipment; 32) Attitude Estimation in Fractionated Spacecraft Cluster Systems; 33) Full Piezoelectric Multilayer-Stacked Hybrid Actuation/Transduction Systems; 34) Active Flow Effectors for Noise and Separation Control; 35) Method and System for Temporal Filtering in Video Compression Systems; 36) Apparatus for Measuring Total Emissivity of Small, Low-Emissivity Samples; 37) Multiple-Zone Diffractive Optic Element for Laser Ranging Applications; 38) Simplified Architecture for Precise Aiming of a Deep-Space Communication Laser Transceiver; 39) Two-Photon-Absorption Scheme for Optical Beam Tracking; 40) High-Sensitivity, Broad-Range Vacuum Gauge Using Nanotubes for Micromachined Cavities; 41) Wide-Field Optic for Autonomous Acquisition of Laser Link; 42) Extracting Zero-Gravity Surface Figure of a Mirror; 43) Modeling Electromagnetic Scattering From Complex Inhomogeneous Objects; 44) Visual Object Recognition and Tracking of Tools; 45) Method for Implementing Optical Phase Adjustment; 46) Visual SLAM Using Variance Grid Maps; 47) Rapid Calculation of Spacecraft Trajectories Using Efficient Taylor Series Integration; 48) Efficient Kriging Algorithms; 49) Predicting Spacecraft Trajectories by the WeavEncke Method; 50) An Augmentation of G-Guidance Algorithms; 51) Comparison of Aircraft Icing Growth Assessment Software; 52) Silicon-Germanium Voltage-Controlled Oscillator at 105 GHz; 53) Estimation of Coriolis Force and Torque Acting on Ares-1; 54) Null Lens Assembly for X-Ray Mirror Segments; and 55) High-Precision Pulse Generator.

Source record↗

Entropy-defect synergy for dual luminescence mechanism in spinel: Time-resolved anti-counterfeiting and fingerprint visualization

Multimodal luminescent materials, while promising for anti-counterfeiting, often lack dynamic time-dependent responses and controllable spatial distribution, limiting their encryption capabilities in the spatiotemporal dimension. Here, this work presents a coordinated control strategy based on entropy and defect engineering, and uses a backpropagation (BP) neural network for material screening to successfully prepare spinel Mg 0.8 (Fe 0.04 Co 0.04 Ni 0.04 Cu 0.04 Zn 0.04 )Cr 2 O 4 (MgA 5 CO) phosphors with time-dependent dynamic luminescence behavior. This phosphor simultaneously activated the d-d transition luminescence (∼618 nm) derived from Co 2+ /Cr 3+ and the defect luminescence (∼398 nm) related to zinc vacancies (V Zn ) in a single-phase solid solution. The phosphor exhibits a time-dependent color evolution from pink to purple under fixed-wavelength excitation, due to the different excited-state dynamics and decay lifetimes associated with the d-d transition and defect luminescence. Structural characterization and spectral analysis confirmed the existence of V Zn and its significant role in defect luminescence process. The fluorescent and dynamic luminescent properties of entropy-based spinel oxide enable its use in advanced anti-counterfeiting applications like fingerprint recognition and color-changing dedicated anti-counterfeiting mark, showing promise in high-end and time-dynamic anti-counterfeiting fields. This research not only developed a new type of fluorescent dynamic anti-counterfeiting material, but also provided a new idea for constructing advanced optical functional materials with multiple luminescence mechanisms.

Defect project↗

NASA total quality management 1989 accomplishments report

NASA and contractor employees achieved many notable improvements in 1989. The highlights of those improvements, described in this seventh annual Accomplishments Report, demonstrate that the people who support NASA's activities are getting more involved in quality and continuous improvement efforts. Their gains solidly support NASA's and this Nation's goal to remain a leader in space exploration and in world-wide market competition, and, when communicated to others through avenues such as this report, foster improvement efforts across government and industry. The principles in practice which led to these process refinements are important cultural elements to any organization's productivity and quality efforts. The categories in this report reflect NASA principles set forth in the 1980's and are more commonly known today as Total Quality Management (TQM): top management leadership and support; strategic planning; focus on the customer; employee training and recognition; employee empowerment and teamwork; measurement and analysis; and quality assurance.

Tai, Betty P.↗