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At least 271 records · Page 15

Computation of the radiation characteristics of a generalized phased array

With the advent of monolithic microwave integrated circuit (MMIC) technology, the phased array has become a key component in the design of advanced antenna systems. Array-fed antennas are used extensively in today's multiple beam satellite antennas. A computer program based on a very efficient numerical technique for calculating the radiated power (Romberg integration), directivity, and radiation pattern of a phased array is described. The formulation developed is very general, and takes into account arbitrary element polarization, E- and H-plane element pattern, element location, and complex element excitation. For comparison purposes sample cases have been presented. Excellent agreement has been obtained for all cases. Also included are a user guide and a copy of the computer program.

Acosta, R. J.↗

Evaluation of Machine Learning and Deep Learning Algorithms for Fire Prediction in Southeast Asia

Vegetation fires are prevalent in South/Southeast Asian countries, making fire prediction crucial due to their potential environmental, economic, and social impacts. Accurate predictions of fires facilitate timely interventions, helping to mitigate uncontrolled fires that can lead to biodiversity loss and air quality issues. In this study, we utilize VIIRS satellite-derived fire data alongside six machine learning and deep learning models—Simple Persistence, Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), CNN-LSTM, and ConvLSTM—to determine the most effective fire prediction model, using Root Mean Square Error (RMSE) as the metric. Our results indicate that the CNN model is the most reliable in regions with spatial dependencies, such as Brunei, Indonesia, Malaysia, the Philippines, Timor-Leste, and Thailand. Conversely, the ConvLSTM model excels in countries with complex spatiotemporal dynamics like Laos, Myanmar, and Vietnam. The CNN-LSTM hybrid model also performed well in Cambodia, suggesting a need for a balanced approach in areas requiring both spatial and temporal feature extraction. Furthermore, simpler models like Persistence and MLP showed limitations in capturing dynamic patterns and temporal dependencies. Our findings highlight the importance of evaluating models before implementing any decision support systems (DSS) in fire management. By tailoring models to specific regional fire data, we can enhance prediction accuracy and responsiveness, ultimately improving fire risk management in Southeast Asia and beyond.

Deep learning↗

Remote sounding of tropospheric minor constituents

The etalon interferometer, or Fabry-Perot interferometer (FPI), with its high throughput and high spectral resolution was widely used in the remote-sensing measurements of the earth's atmospheric composition, winds, and temperatures. The most recent satellite instruments include the Fabry-Perot interferometer flown on the Dynamics Explorer-2 (DE-2) and the High Resolution Doppler Imager (HRDI) to be flown on the Upper Atmosphere Research Satellite (UARS). These instruments measure the Doppler line profiles of the emission and absorption of certain atmospheric species (such as atomic oxygen) in the visible spectral region. The successful space flight of DE-FPI and the test and delivery of UARS-HRDI demonstrated the extremely high spectral resolution and ruggedness of the etalon system for the remote sensing of earth and planetary atmospheres. Recently, an innovative FPI focal plane detection technique called the Circle-to-Line Interferometer Optical (CLIO) system was invented at the Space Physics Research Laboratory (SPRL). The CLIO simplifies the FPI focal plane detection process by converting the circular rings or fringes into a linear pattern similar to that produced by a conventional spectrometer, while retaining the throughput advantage of the etalon interferometer. CLIO makes the use of linear array detectors more practical and efficient with FPI, the combination of FPI and CLIO represents a very promising new technique for the remote sensing of the lower atmospheres of Earth, Mars, Venus, Neptune, and other planets. The Multiorder Etalon Spectrometer (MOES), as a combination of the rugged etalon and the CLIO, compares very favorably to other spaceborne optical instruments in terms of performance versus complexity. The feasibility of an advanced etalon spectrometer for the remote sensing of tropospheric trace species, particularly carbon monoxide (CO), nitrous oxide (N2O), and methane (CH4) was discussed. The etalon atmospheric spectroscopy techniques are described, instrument design and related technical issues are discussed. The primary objective is to establish the concept of atmospheric spectroscopy with the CLIO and etalon system and its applications for the measurements of tropospheric trace species analyze system requirements and performance, determine the feasibility of components and subsystem implementation with available technology, and develop inversion algorithm for retrieval simulation and data analysis.

Drayson, S. Roland↗

The NIST Real-Time Control System (RCS): A Reference Model Architecture for Computational Intelligence

The Real-time Control System (RCS) developed at NIST and elsewhere over the past two decades defines a reference model architecture for design and analysis of complex intelligent control systems. The RCS architecture consists of a hierarchically layered set of functional processing modules connected by a network of communication pathways. The primary distinguishing feature of the layers is the bandwidth of the control loops. The characteristic bandwidth of each level is determined by the spatial and temporal integration window of filters, the temporal frequency of signals and events, the spatial frequency of patterns, and the planning horizon and granularity of the planners that operate at each level. At each level, tasks are decomposed into sequential subtasks, to be performed by cooperating sets of subordinate agents. At each level, signals from sensors are filtered and correlated with spatial and temporal features that are relevant to the control function being implemented at that level.

Albus, James S.↗

Supporting Crew Medical Decisions on Deep Space Missions: A Real-Time Performance Monitoring

Crewed missions into deep space will require astronauts to respond autonomously to safety- and time-critical anomalies. These and other potential issues will require the continuous monitoring and recognition of potentially subtle, but complex, anomalous data patterns. NASA continues to investigate real-time metrics for Extravehicular Operations1 and for providing feedback to improve performance2. Since it is unknown how long-term exposure to deep space will affect crew health, continuous monitoring of clinical and subclinical status is warranted. NASA is characterizing crew medical decision-support needs and identifying the recommended requirements of a Clinical Decision Support System (CDSS) within the Exploration Medical Capability Element (ExMC) of the Human Research Program3. Early detection, and continuous monitoring, of performance may provide an effective prognostic capability for assessing crew health state, and the identified requirements could be provided for an in-vehicle CDSS that acts as an assistant for delivering optimal health and performance and medical care during exploration missions. There is evidence to suggest that automatic, unobtrusive collection of keystroke features, such as alphanumeric key latencies, backspaces or typing rhythm, could be a valuable performance screening tool. Keystroke features show significant differences between control subjects and patients with overt clinical illness, such as multiple sclerosis4 and Parkinson’s disease5, as well as behavioral health and performance issues, such as mild cognitive impairment6 and depression7. This work is exploring a capability for the assessment of early task performance decline in crew as they perform daily activities. Timestamped keyboard entries are continuously collected and stored. Nominal keystroke interactions are compared to those obtained after exposure to spaceflight stressors, e.g., fatigue, to determine the methods sensitivity. This work will pave the way toward an objective detection tool that may be deployed in a spaceflight setting.

clinical↗

Laboratory Studies of Fischer-Tropsch-Type Reactions and Their Implications for Organics in Asteroids and Comets

We have been studying Fischer-Tropsch type (FTT) reactions as a source for organic materials both in the gas phase of the solar nebula and incorporated into primitive comets and asteroids for almost 10 years, and over this time our concept has evolved greatly from the standard "catalytic" model to a much more robust chemical scenario. Our simulations have been conducted at temperatures that are much higher than we like, primarily for practical reasons such as the timescale of individual reactions, and we are just starting a series of measurements to allow us to measure reaction rates at temperatures from 873K down to as low as 373K. We have preliminary data on the carbon (d13C = -50) & nitrogen (d15N = +9.5) isotopic fractionation at 873K, but not on materials produced at lower temperature. Isotope values are on the VPDB scale for carbon and vs. Air for nitrogen. We have also investigated the noble gas trapping efficiency of the FTT process by adding a small amount of a noble gas mix to our standard synthesis mix. The noble gas ratio is 49:49:1:1::Ne:Ar:Kr:Xe. Xe and Kr are trapped at 873K and are more efficiently trapped at 673K with no isotopic fractionation at either temperature. Ar trapping is detected at 673K, but not at 873K. Ne has not yet been observed in our samples. The solar nebula was an extremely complex system, mixing materials from the innermost regions out to well into the zones where comets formed and thus mixing highly processed nebular materials with grains and coatings formed before the nebula began to collapse. Laboratory studies may provide the means to separate such diverse components based on carbon or nitrogen isotopic fractionation or the quantities of noble gases trapped in grain coatings and their thermal release patterns, among other observables. The ultimate goal of laboratory synthesis of nebular analogs is to provide the means to identifY the conditions under which natural samples were formed and the signatures of subsequent metamorphic events.

Nuth, Joseph↗

Combined pressure and temperature distortion effects on internal flow of a turbofan engine

An additional data base for improving and verifying a computer simulation developed by an engine manufacturer was obtained. The multisegment parallel compressor simulation was designed to predict the effects of steady-state circumferential inlet total-pressure and total-temperature distortions on the flows into and through a turbofan compression system. It also predicts the degree of distortion that will result in surge of the compressor. The effect of combined 180 deg square-wave distortion patterns of total pressure and total temperature in various relative positions is reported. The observed effects of the combined distortion on a unitary bypass ratio turbofan engine are presented in terms of total and static pressure profiles and total temperature profiles at stations ahead of the inlet guide vanes as well as through the fan-compressor system. These observed profiles are compared with those predicted by the complex multisegment model. The effects of relative position of the two components comprising the combined distortion on the degree resulting in surge are discussed. Certain relative positions required less combined distortion than either a temperature or pressure distortion by itself.

Braithwaite, W. M.↗

Purification of the small mechanosensitive channel of Escherichia coli (MscS): the subunit structure, conduction, and gating characteristics in liposomes

The small mechanosensitive channel, MscS, is a part of the turgor-driven solute efflux system that protects bacteria from lysis in the event of osmotic downshift. It has been identified in Escherichia coli as a product of the orphan yggB gene, now called mscS (Levina et al., 1999, EMBO J. 18:1730). Here I show that that the isolated 31-kDa MscS protein is sufficient to form a functional mechanosensitive channel gated directly by tension in the lipid bilayer. MscS-6His complexes purified in the presence of octylglucoside and lipids migrate in a high-resolution gel-filtration column as particles of approximately 200 kDa. Consistent with that, the protein cross-linking patterns predict a hexamer. The channel reconstituted in soybean asolectin liposomes was activated by pressures of 20-60 mm Hg and displayed the same asymmetric I-V curve and slight anionic preference as in situ. At the same time, the single-channel conductance is proportional to the buffer conductivity in a wide range of salt concentrations. The rate of channel activation in response to increasing pressure gradient across the patch was slower than the rate of closure in response to decreasing steps of pressure gradient. Therefore, the open probability curves were recorded with descending series of pressures. Determination of the curvature of patches by video imaging permitted measurements of the channel activity as a function of membrane tension (gamma). Po(gamma) curves had the midpoint at 5.5 +/- 0.1 dyne/cm and gave estimates for the energy of opening DeltaG = 11.4 +/- 0.5 kT, and the transition-related area change DeltaA = 8.4 +/- 0.4 nm(2) when fitted with a two-state Boltzmann model. The correspondence between channel properties in the native and reconstituted systems is discussed.

NASA Discipline Cell Biology↗

Two-dimensional simulation of a two-phase, regenerative pumped radiator loop utilizing direct contact heat transfer with phase change

An innovative pumped loop concept for 600 K space power system radiators utilizing direct contact heat transfer, which facilitates repeated startup/shutdown of the power system without complex and time-consuming coolant thawing during power startup, is under development. The heat transfer process with melting/freezing of Li in an NaK flow was studied through two-dimensional time-dependent numerical simulations to characterize and predict the Li/NaK radiator performance during startup (thawing) and shutdown (cold-trapping). Effects of system parameters and the criteria for the plugging domain are presented together with temperature distribution patterns in solid Li and subsequent melting surface profile variations in time.

Rhee, Hyop S.↗

Subtle alternating electrocardiographic morphology as an indicator of decreased cardiac electrical stability

Observations from finite-element computer models, together with analytic developments based on percolation theory have suggested that subtle fluctuations of ECG morphology might serve as an indicator diminished cardiac electrical stability. With fixed-rate atrial pacing in canines, we have previously observed a pattern of alternation in T wave energy which correlated with cardiac electrical stability. We report here on a series of 20 canine experiments in which cardiac electrical stability (measured via Ventricular Fibrillation Threshold determination) was compared to a non-degenerate, multidimensional measurement of the degree of alternating activity present in the ECG complex morphology. The decrease in cardiac electrical stability brought on by both coronary artery occlusion and systemic hypothermia was consistently accompanied by subtle alternation in ECG morphology, with the absolute degree of alternating activity being significantly (negatively) correlated with cardiac electrical stability.

Ventricular Fibrillation↗

Vestibular stimulation leads to distinct hemodynamic patterning

Previous studies demonstrated that responses of a particular sympathetic nerve to vestibular stimulation depend on the type of tissue the nerve innervates as well as its anatomic location. In the present study, we sought to determine whether such precise patterning of vestibulosympathetic reflexes could lead to specific hemodynamic alterations in response to vestibular afferent activation. We simultaneously measured changes in systemic blood pressure and blood flow (with the use of Doppler flowmetry) to the hindlimb (femoral artery), forelimb (brachial artery), and kidney (renal artery) in chloralose-urethane-anesthetized, baroreceptor-denervated cats. Electrical vestibular stimulation led to depressor responses, 8 +/- 2 mmHg (mean +/- SE) in magnitude, that were accompanied by decreases in femoral vasoconstriction (23 +/- 4% decrease in vascular resistance or 36 +/- 7% increase in vascular conductance) and increases in brachial vascular tone (resistance increase of 10 +/- 6% and conductance decrease of 11 +/- 4%). Relatively small changes (<5%) in renal vascular tone were observed. In contrast, electrical stimulation of muscle and cutaneous afferents produced pressor responses (20 +/- 6 mmHg) that were accompanied by vasoconstriction in all three beds. These data suggest that vestibular inputs lead to a complex pattern of cardiovascular changes that is distinct from that which occurs in response to activation of other types of somatic afferents.

NASA Discipline Neuroscience↗

Effect of scanline orientation on ventricular flow propagation: assessment using high frame-rate color Doppler echocardiography

Color M-mode echocardiography has recently been utilized to describe diastolic flow propagation velocity (Vp) in the left ventricle. While increasing temporal resolution from 15 to 200 Hz, this M-mode technique requires the user to select a single scanline, potentially limiting quantification of Vp due to the complex three-dimensional inflow pattern. We previously performed computational fluid dynamics simulations to demonstrate the insignificance of the scanline orientation, however geometric complexity was limited. The purpose of this study was to utilize high frame-rate 2D color Doppler images to investigate the importance of scanline selection in patients for the quantification of Vp. 2D color Doppler images were digitally acquired at 50 frames/s in 6 subjects from the apical 4-chamber window (System 5, GE/Vingmed, Milwaukee, WI). Vp was determined for a set of scanlines positioned through 5 locations across the mitral annulus (from the anterior to posterior mitral annulus). An analysis of variance was performed to examine the differences in Vp as a function of scanline position. Vp was not effected by scanline position in sampled locations from the center of the mitral valve towards the posterior annulus. Although not statistically significant, there was a trend to slower propagation velocities on the anterior side of the valve (60.8 +/- 16.7 vs. 54.4 +/- 13.6 cm/s). This study clinically validates our previous numerical experiment showing that Vp is insensitive to small perturbations of the scanline through the mitral valve. However, further investigation is necessary to examine the impact of ventricular geometry in pathologies including dilated cardiomyopathy.

Non-NASA Center↗

Training Knowledge Bots for Physics-Based Simulations Using Artificial Neural Networks

Millions of complex physics-based simulations are required for design of an aerospace vehicle. These simulations are usually performed by highly trained and skilled analysts, who execute, monitor, and steer each simulation. Analysts rely heavily on their broad experience that may have taken 20-30 years to accumulate. In addition, the simulation software is complex in nature, requiring significant computational resources. Simulations of system of systems become even more complex and are beyond human capacity to effectively learn their behavior. IBM has developed machines that can learn and compete successfully with a chess grandmaster and most successful jeopardy contestants. These machines are capable of learning some complex problems much faster than humans can learn. In this paper, we propose using artificial neural network to train knowledge bots to identify the idiosyncrasies of simulation software and recognize patterns that can lead to successful simulations. We examine the use of knowledge bots for applications of computational fluid dynamics (CFD), trajectory analysis, commercial finite-element analysis software, and slosh propellant dynamics. We will show that machine learning algorithms can be used to learn the idiosyncrasies of computational simulations and identify regions of instability without including any additional information about their mathematical form or applied discretization approaches.

Samareh, Jamshid A.↗

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↗

Airspace Complexity and its Application in Air Traffic Management

The United States Air Traffic Management (ATM) system provides services to enable safe, orderly and efficient aircraft operations within the airspace over the continental United States and over large portions of the Pacific and Atlantic Oceans, and the Gulf of Mexico. It consists of two components, Air Traffic Control (ATC) and Traffic Flow Management (TFM). The ATC function ensures that the aircraft within the airspace are separated at all times while the TFM function organizes the aircraft into a flow pattern to ensure their safe and efficient movement. In order to accomplish the ATC and TFM functions, the airspace over United States is organized into 22 Air Route Traffic Control Centers (ARTCCs). The Center airspace is stratified into low-altitude, high-altitude and super-high altitude groups of Sectors. Each vertical layer is further partitioned into several horizontal Sectors. A typical ARTCC airspace is partitioned into 20 to 80 Sectors. These Sectors are the basic control units within the ATM system.

Sridhar, Banavar↗

Active Array Measurements using the Portable Laser Guided Robotic Metrology System

In this paper, we will discuss the impact of mounting structures on the installed performance of phased arrays. In particular, performance data for the Conformal, Lightweight Antennas for Aeronautical Communications Technology (CLAS-ACT) antenna will be presented. Performance data from a series of mounting configurations will show that null depth and location is particularly susceptible while the main beam steering angle remain relatively stable. In addition, the Portable Laser Guided Robotic antenna range (PLGR) will be discussed as a suitable instrument for measuring antenna patterns in complex or difficult locations that are challenging for traditional ranges. The PLGR antenna range was recently developed at the National Aeronautics and Space Administration's (NASA) Glenn Research Center (GRC) and deployed to measure in situ antenna patterns.

Piasecki, Marie↗

Wide-Angle-Scanning Reflectarray Antennas Actuated by MEMS

An effort to develop large-aperture, wide-angle-scanning reflectarray antennas for microwave radar and communication systems is underway. In an antenna of this type as envisioned, scanning of the radiated or incident microwave beam would be effected through mechanical rotation of the passive (reflective) patch antenna elements, using microelectromechanical systems (MEMS) stepping rotary actuators typified by piezoelectric micromotors. It is anticipated that the cost, mass, and complexity of such an antenna would be less than, and the reliability greater than, those of an electronically scanned phased-array antenna of comparable beam-scanning capability and angular resolution. In the design and operation of a reflectarray, one seeks to position and orient an array of passive patch elements in a geometric pattern such that, through constructive interference of the reflections from them, they collectively act as an efficient single reflector of radio waves within a desired frequency band. Typically, the patches lie in a common plane and radiation is incident upon them from a feed horn.

Fang, Houfei↗

Continuous monitoring of the lunar or Martian subsurface using on-board pattern recognition and neural processing of Rover geophysical data

The ultimate goal is to create an extraterrestrial unmanned system for subsurface mapping and exploration. Neural networks are to be used to recognize anomalies in the profiles that correspond to potentially exploitable subsurface features. The ground penetrating radar (GPR) techniques are likewise identical. Hence, the preliminary research focus on GPR systems will be directly applicable to seismic systems once such systems can be designed for continuous operation. The original GPR profile may be very complex due to electrical behavior of the background, targets, and antennas, much as the seismic record is made complex by multiple reflections, ghosting, and ringing. Because the format of the GPR data is similar to the format of seismic data, seismic processing software may be applied to GPR data to help enhance the data. A neural network may then be trained to more accurately identify anomalies from the processed record than from the original record.

Mcgill, J. W.↗