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NASA NTRS2010

Methods of Using a Magnetic Field Response Sensor Within Closed, Electrically Conductive Containers

Magnetic field response sensors are a class of sensors that are powered via oscillating magnetic fields, and when electrically active, respond with their own magnetic fields with attributes dependent upon the magnitude of the physical quantity being measured. A magnetic field response recorder powers and interrogates the magnetic sensors [see Magnetic-Field-Response Measurement- Acquisition System, NASA Tech Briefs Vol. 30, No, 6 (June 2006, page 28)]. Electrically conductive containers have low transmissivity for radio frequency (RF) energy and thus present problems for magnetic field response sensors. It is necessary in some applications to have a magnetic field response sensor s capacitor placed in these containers. Proximity to conductive surfaces alters the inductance and capacitance of the sensors. As the sensor gets closer to a conductive surface, the electric field and magnetic field energy of the sensor is reduced due to eddy currents being induced in the conductive surface. Therefore, the capacitors and inductors cannot be affixed to a conductive surface or embedded in a conductive material. It is necessary to have a fixed separation away from the conductive material. The minimum distance for separation is determined by the desired sensor response signal to noise ratio. Although the inductance is less than what it would be if it were not in proximity to the conductive surface, the inductance is fixed. As long as the inductance is fixed, all variations of the magnetic field response are due to capacitance changes. Numerous variations of inductor mounting can be utilized, such as providing a housing that provides separation from the conductive material as well as protection from impact damage. The sensor can be on the same flexible substrate with a narrow throat portion of the sensor between the inductor and the capacitor, Figure 1. The throat is of sufficient length to allow the capacitor to be appropriately placed within the container and the inductor placed outside the container. The throat is fed through the orifice in the container wall (e.g., fuel tank opening) and connects to the inductor and capacitor via electrical leads to form a closed circuit, Figure 2. Another embodiment is to have the inductor and capacitor fabricated as separate units. In this embodiment, the inductor is mounted external to the container, and the capacitor is mounted internal to the container, Figure 1. Electrical leads are fed through the orifice to connect the inductor and capacitor, Figure 2. When a container holding multiple sensors is made of a conductive material, an antenna can be placed internal to the container. An internal antenna allows all components of the sensors to reside inside the container. The antenna must be separated from the container wall s conductive surface. Additionally, the inductors must be maintained in a fixed position relative to and separated from the container

Woodward, Stanley E.↗

NASA NTRS2010

Ambiguity of Quality in Remote Sensing Data

This slide presentation reviews some of the issues in quality of remote sensing data. Data "quality" is used in several different contexts in remote sensing data, with quite different meanings. At the pixel level, quality typically refers to a quality control process exercised by the processing algorithm, not an explicit declaration of accuracy or precision. File level quality is usually a statistical summary of the pixel-level quality but is of doubtful use for scenes covering large areal extents. Quality at the dataset or product level, on the other hand, usually refers to how accurately the dataset is believed to represent the physical quantities it purports to measure. This assessment often bears but an indirect relationship at best to pixel level quality. In addition to ambiguity at different levels of granularity, ambiguity is endemic within levels. Pixel-level quality terms vary widely, as do recommendations for use of these flags. At the dataset/product level, quality for low-resolution gridded products is often extrapolated from validation campaigns using high spatial resolution swath data, a suspect practice at best. Making use of quality at all levels is complicated by the dependence on application needs. We will present examples of the various meanings of quality in remote sensing data and possible ways forward toward a more unified and usable quality framework.

Lynnes, Christopher↗

NASA NTRS2011

SansEC Sensing Technology - A New Tool for Designing Space Systems and Components

This paper presents concepts for using the NASA developed SansEC sensing technology for reconfiguring/modifying many space subsystems to add to their original function the ability to be sensors/sensor arrays without the addition of the electrical circuitry typically used for sensors. Each sensor is a self-resonating planar pattern of electrically conductive material that is an open-circuit single component without electrical connections. The sensors are wirelessly powered using external oscillating magnetic fields and when electrically excited respond with their own magnetic fields whose frequency, amplitude and bandwidth can be correlated with the magnitude of multiple unrelated physical quantities. These sensors have been demonstrated for numerous measurements required for spacecraft and inflatable/expandable structures. SansEC sensors are damage resilient and simple to fabricate. Thin films of conductive material can be used to create sensor arrays that function as sensing skins. Each sensor on the skin can be tailored for a science or engineering measurement. Additionally, each sensor has an inherent damage detection capability. These sensing skins can be used to redesign inflatable habitat multi-layer insulation to provide additional functions of environmental measurement and micrometeorite/orbital debris damage detections. The sensing skins can be deposited on planetary exploratory vehicles to increase the number of measurements with negligible weight increase.

Woodard, Stanley E.↗

NASA NTRS2011

Virtual Sensor Test Instrumentation

Virtual Sensor Test Instrumentation is based on the concept of smart sensor technology for testing with intelligence needed to perform sell-diagnosis of health, and to participate in a hierarchy of health determination at sensor, process, and system levels. A virtual sensor test instrumentation consists of five elements: (1) a common sensor interface, (2) microprocessor, (3) wireless interface, (4) signal conditioning and ADC/DAC (analog-to-digital conversion/ digital-to-analog conversion), and (5) onboard EEPROM (electrically erasable programmable read-only memory) for metadata storage and executable software to create powerful, scalable, reconfigurable, and reliable embedded and distributed test instruments. In order to maximize the efficient data conversion through the smart sensor node, plug-and-play functionality is required to interface with traditional sensors to enhance their identity and capabilities for data processing and communications. Virtual sensor test instrumentation can be accessible wirelessly via a Network Capable Application Processor (NCAP) or a Smart Transducer Interlace Module (STIM) that may be managed under real-time rule engines for mission-critical applications. The transducer senses the physical quantity being measured and converts it into an electrical signal. The signal is fed to an A/D converter, and is ready for use by the processor to execute functional transformation based on the sensor characteristics stored in a Transducer Electronic Data Sheet (TEDS). Virtual sensor test instrumentation is built upon an open-system architecture with standardized protocol modules/stacks to interface with industry standards and commonly used software. One major benefit for deploying the virtual sensor test instrumentation is the ability, through a plug-and-play common interface, to convert raw sensor data in either analog or digital form, to an IEEE 1451 standard-based smart sensor, which has instructions to program sensors for a wide variety of functions. The sensor data is processed in a distributed fashion across the network, providing a large pool of resources in real time to meet stringent latency requirements.

Wang, Roy↗

NASA NTRS2011

Preliminary Computational Analysis of the (HIRENASD) Configuration in Preparation for the Aeroelastic Prediction Workshop

This paper presents preliminary computational aeroelastic analysis results generated in preparation for the first Aeroelastic Prediction Workshop (AePW). These results were produced using FUN3D software developed at NASA Langley and are compared against the experimental data generated during the HIgh REynolds Number Aero- Structural Dynamics (HIRENASD) Project. The HIRENASD wind-tunnel model was tested in the European Transonic Windtunnel in 2006 by Aachen University0s Department of Mechanics with funding from the German Research Foundation. The computational effort discussed here was performed (1) to obtain a preliminary assessment of the ability of the FUN3D code to accurately compute physical quantities experimentally measured on the HIRENASD model and (2) to translate the lessons learned from the FUN3D analysis of HIRENASD into a set of initial guidelines for the first AePW, which includes test cases for the HIRENASD model and its experimental data set. This paper compares the computational and experimental results obtained at Mach 0.8 for a Reynolds number of 7 million based on chord, corresponding to the HIRENASD test conditions No. 132 and No. 159. Aerodynamic loads and static aeroelastic displacements are compared at two levels of the grid resolution. Harmonic perturbation numerical results are compared with the experimental data using the magnitude and phase relationship between pressure coefficients and displacement. A dynamic aeroelastic numerical calculation is presented at one wind-tunnel condition in the form of the time history of the generalized displacements. Additional FUN3D validation results are also presented for the AGARD 445.6 wing data set. This wing was tested in the Transonic Dynamics Tunnel and is commonly used in the preliminary benchmarking of computational aeroelastic software.

Chwalowski, Pawel↗

NASA NTRS2005

Conservative Patch Algorithm and Mesh Sequencing for PAB3D

A mesh-sequencing algorithm and a conservative patched-grid-interface algorithm (hereafter Patch Algorithm ) have been incorporated into the PAB3D code, which is a computer program that solves the Navier-Stokes equations for the simulation of subsonic, transonic, or supersonic flows surrounding an aircraft or other complex aerodynamic shapes. These algorithms are efficient, flexible, and have added tremendously to the capabilities of PAB3D. The mesh-sequencing algorithm makes it possible to perform preliminary computations using only a fraction of the grid cells (provided the original cell count is divisible by an integer) along any grid coordinate axis, independently of the other axes. The patch algorithm addresses another critical need in multi-block grid situation where the cell faces of adjacent grid blocks may not coincide, leading to errors in calculating fluxes of conserved physical quantities across interfaces between the blocks. The patch algorithm, based on the Stokes integral formulation of the applicable conservation laws, effectively matches each of the interfacial cells on one side of the block interface to the corresponding fractional cell area pieces on the other side. This approach is comprehensive and unified such that all interface topology is automatically processed without user intervention. This algorithm is implemented in a preprocessing code that creates a cell-by-cell database that will maintain flux conservation at any level of full or reduced grid density as the user may choose by way of the mesh-sequencing algorithm. These two algorithms have enhanced the numerical accuracy of the code, reduced the time and effort for grid preprocessing, and provided users with the flexibility of performing computations at any desired full or reduced grid resolution to suit their specific computational requirements.

Pao, S. P.↗

NASA NTRS2003

Wireless Temperature-Monitoring System

A relatively inexpensive instrumentation system that includes units that are connected to thermocouples and that are parts of a radio-communication network has been developed to enable monitoring of temperatures at multiple locations. Because there is no need to string wires or cables for communication, the system is well suited for monitoring temperatures at remote locations and for applications in which frequent changes of monitored or monitoring locations are needed. The system can also be adapted to monitoring of slowly varying physical quantities, other than temperature, that can be transduced by solid-state electronic sensors. The system comprises any number of transmitting units and a single receiving unit (see figure). Each transmitting unit includes connections for as many as four external thermocouples, a signal-conditioning module, a control module, and a radio-communication module. The signal- conditioning module acts as an interface between the thermocouples and the rest of the transmitting unit and includes a built-in solid ambient-temperature sensor that is in addition to the external thermocouples. The control module is a "system-on-chip" embedded processor that includes analog-to-digital converters, serial and parallel data ports, and an interface for local connection to an analog meter that is used during installation to verify correct operation. The radio-communication module contains a commercial spread-spectrum transceiver that operates in the 900-MHz industrial, scientific, and medical (ISM) frequency band. This transceiver transmits data to the receiving unit at a rate of 19,200 baud. The receiving unit includes a transceiver like that of a transmitting unit, plus a control module that contains a system-on-chip processor that includes serial data port for output to a computer that runs monitoring and/or control software, a parallel data port for output to a printer, and a seven-segment light-emitting-diode display.

Solano, Wanda↗

NASA NTRS2003

Analytic Method for Computing Instrument Pointing Jitter

A new method of calculating the root-mean-square (rms) pointing jitter of a scientific instrument (e.g., a camera, radar antenna, or telescope) is introduced based on a state-space concept. In comparison with the prior method of calculating the rms pointing jitter, the present method involves significantly less computation. The rms pointing jitter of an instrument (the square root of the jitter variance shown in the figure) is an important physical quantity which impacts the design of the instrument, its actuators, controls, sensory components, and sensor- output-sampling circuitry. Using the Sirlin, San Martin, and Lucke definition of pointing jitter, the prior method of computing the rms pointing jitter involves a frequency-domain integral of a rational polynomial multiplied by a transcendental weighting function, necessitating the use of numerical-integration techniques. In practice, numerical integration complicates the problem of calculating the rms pointing error. In contrast, the state-space method provides exact analytic expressions that can be evaluated without numerical integration.

Bayard, David↗

NASA NTRS2011

Fast Plasma Investigation for MMS: Simulation of the Burst Triggering System

The Magnetospheric Multiscale (MMS) mission will study small-scale reconnection structures and their rapid motions from closely spaced platforms using instruments capable of high angular, energy, and time resolution measurements. To meet these requirements, the Fast Plasma Instrument (FPI) consists of eight (8) identical half top-hat electron sensors and eight (8) identical ion sensors and an Instrument Data Processing Unit (IDPU). The sensors (electron or ion) are grouped into pairs whose 6 degree x 180 degree fields-of-view (FOV) are set 90 degrees apart. Each sensor is equipped with electrostatic aperture steering to allow the sensor to scan a 45 degree x 180 degree fan about the its nominal viewing (0 deflection) direction. Each pair of sensors, known as the Dual Electron Spectrometer (DES) and the Dual Ion Spectrometer (DIS), occupies a quadrant on the MMS spacecraft and the combination of the eight electron/ion sensors, employing aperture steering, image the full-sky every 30-ms (electrons) and 150-ms (ions), respectively. To probe the diffusion regions of reconnection, the highest temporal/spatial resolution mode of FPI results in the DES complement of a given spacecraft generating 6.5-Mb (raised dot) per second of electron data while the DIS generates 1.1-Mb (raised dot) per second of ion data yielding an FPI total data rate of 6.6-Mb (raised dot) per second. The FPI electron/ion data is collected by the IDPU then transmitted to the Central Data Instrument Processor (CIDP) on the spacecraft for science interest ranking. Only data sequences that contain the greatest amount of temporal/spatial structure will be intelligently down-linked by the spacecraft. This requires a data ranking process known as the burst trigger system. The burst trigger system uses pseudo physical quantities to approximate the local plasma environments. As each pseudo quantity will have a different value, a set of two scaling factors is employed for each pseudo term. These pseudo quantities are then combined at the instrument, spacecraft, and observatory level leading to a final ranking of data based on expected scientific interest. Here, we present simulations of the fixed point burst trigger system for the FPI. A variety of data sets based on previous mission data as well as analytical formulations are tested. Comparisons of floating point calculations versus the fixed point hardware simulation are shown. Analysis of the potential sources of error from overflows, quantization, etc. are examined and mitigation methods are presented. Finally a series of calibration curves are presented, showing the expected error in pseudo quantities based solely on the scale parameters chosen and the expected data range. We conclude with a presentation of the current base-lined FPI burst trigger approach.

Barrie, A. C.↗

NASA NTRS2010

On the Phase-Averaged Spectrum of Pulsars and Shape of Their Cutoffs

All gamma ray pulsars exhibit an exponential cutoff in their spectra and for bright pulsars the statistics are sufficiently high to study the detailed shape of the cutoff. The phase averaged spectra of some pulsars exhibit a sub-exponential cutoff, not predicted by any single physical mechanism. Further studies clarified that (his gentler average cutoff is a consequence of having significant variations of the cutoff energy in the phase-resolved spectrum. In conclusion, the phase-averaged spectrum of a pulsar is not a physical quantity to test high-energy emission models.

Celik, O.↗

NASA NTRS2015

Smart Optical Material Characterization System and Method

Disclosed is a system and method for characterizing optical materials, using steps and equipment for generating a coherent laser light, filtering the light to remove high order spatial components, collecting the filtered light and forming a parallel light beam, splitting the parallel beam into a first direction and a second direction wherein the parallel beam travelling in the second direction travels toward the material sample so that the parallel beam passes through the sample, applying various physical quantities to the sample, reflecting the beam travelling in the first direction to produce a first reflected beam, reflecting the beam that passes through the sample to produce a second reflected beam that travels back through the sample, combining the second reflected beam after it travels back though the sample with the first reflected beam, sensing the light beam produced by combining the first and second reflected beams, and processing the sensed beam to determine sample characteristics and properties.

Choi, Sang Hyouk↗

NASA NTRS2014

A Vortical Dawn Flank Boundary Layer for Near-Radial IMF: Wind Observations on 24 October 2001

We present an example of a boundary layer tailward of the dawn terminator which is entirely populated by rolled-up flow vortices. Observations were made by Wind on 24 October 2001 as the spacecraft moved across the region at the X plane approximately equal to −13 Earth radii. Interplanetary conditions were steady with a near-radial interplanetary magnetic field (IMF). Approximately 15 vortices were observed over the 1.5 hours duration of Wind's crossing, each lasting approximately 5 min. The rolling up is inferred from the presence of a hot tenuous plasma being accelerated to speeds higher than in the adjoining magnetosheath, a circumstance which has been shown to be a reliable signature of this in single-spacecraft observations. A blob of cold dense plasma was entrained in each vortex, at whose leading edge abrupt polarity changes of field and velocity components at current sheets were regularly observed. In the frame of the average boundary layer velocity, the dense blobs were moving predominantly sunward and their scale size along the X plane was approximately 7.4 Earth radii. Inquiring into the generation mechanism of the vortices, we analyze the stability of the boundary layer to sheared flows using compressible magnetohydrodynamic Kelvin-Helmholtz theory with continuous profiles for the physical quantities. We input parameters from (i) the exact theory of magnetosheath flow under aligned solar wind field and flow vectors near the terminator and (ii) the Wind data. It is shown that the configuration is indeed Kelvin-Helmholtz (KH) unstable. This is the first reported example of KH-unstable waves at the magnetopause under a radial IMF.

Magnetosheath↗

NASA NTRS2016

NuSTAR Observations of Water Megamaser AGN

Aims. We study the connection between the masing disk and obscuring torus in Seyfert 2 galaxies. Methods. We present a uniform X-ray spectral analysis of the high energy properties of 14 nearby megamaser active galactic nuclei observed by NuSTAR. We use a simple analytical model to localize the maser disk and understand its connection with the torus by combining NuSTAR spectral parameters with the available physical quantities from VLBI mapping.Results. Most of the sources that we analyzed are heavily obscured, showing a column density in excess of approx.10(exp 23) cm(exp -2); in particular, 79% are Compton-thick [NH is greater than 1.5 x 10(exp 24) cm(exp -2)]. When using column densities measured by NuSTAR with the assumption that the torus is the extension of the maser disk, and further assuming a reasonable density profile, we can predict the torus dimensions. They are found to be consistent with mid-IR interferometry parsec-scale observations of Circinus and NGC 1068. In this picture, the maser disk is intimately connected to the inner part of the torus. It is probably made of a large number of molecular clouds that connect the torus and the outer part of the accretion disk, giving rise to a thin disk rotating in most cases in Keplerian or sub-Keplerian motion. This toy model explains the established close connection between water megamaser emission and nuclear obscuration as a geometric effect.

masers / galaxies: active / galaxies: Seyfert↗

NASA NTRS2017

Optimal A-Train Data Utilization: A Use Case of Aura OMI L2G and MERRA-2 Aerosol Products

Ozone Monitoring Instrument (OMI) aboard NASA's Aura mission measures ozone column and profile, aerosols, clouds, surface UV irradiance, and the trace gases including NO2, SO2, HCHO, BrO, and OClO using UltraViolet electromagnetic spectrum (280 - 400 nm) with a daily global coverage and a pixel spatial resolution of 13 km × 24 km at nadir, and it's been one of the key instruments to study the Earth's atmospheric composition and chemistry. The second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) is NASA's atmospheric reanalysis using an upgraded version of Goddard Earth Observing System Model, version 5 (GEOS-5) data assimilation system. Compared to its predecessor MERRA, MERRA-2 is enhanced with more aspects of the Earth system among which is aerosol assimilation. When comparing between satellite pixel measurements and modeled grid data, how to properly handle counterpart pairing is critical considering their spatial and temporal variations. The comparison between satellite and model data by simply using Level 3 (L3) products may result biases due to lack of detailed temporal information. It has been preferred to inter-compare or implement satellite derived physical quantity (i.e., Level 2 (L2) Swath type) directly with/to model measurements with higher temporal and spatial resolution as possible. However, this has posed a challenge in the community to handle. Rather than directly handling the L2 or L3 data, there is a Level 2G (L2G) product conserving L2 pixel scientific data quality but in Grid type with the global coverage. In this presentation, we would like to demonstrate the optimal utilization of OMI L2G daily aerosol products by comparing with MERRA-2 hourly aerosol simulations matched well in both space and time.

MERRA-2 reanalysis↗

NASA NTRS2018

Application of Aura OMI L2G Products Compared with NASA MERRA-2 Assimilation

The Ozone Monitoring Instrument (OMI) is one of the instruments aboard NASA's Aura satellite. It measures ozone total column and vertical profile, aerosols, clouds, and trace gases including NO2, SO2, HCHO, BrO, and OClO using absorption in the ultraviolet electromagnetic spectrum (280 - 400 nm). OMI Level-2G (L2G) products are based on the pixel-level OMI granule satellite measurements stored within global 0.25 deg. X 0.25 deg. grids, therefore they conserve all the Level 2 (L2) spatial and temporal details for 24 hours of scientific data in one file. The second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) is NASA's atmospheric reanalysis, using an upgraded version of Goddard Earth Observing System Model, version 5 (GEOS-5) data assimilation system. MERRA-2 includes aerosol data reanalysis and improved representations of stratospheric ozone, compared with its predecessor MERRA, in both instantaneous and time-averaged collections. It is found that simply comparing satellite Level-3 products might cause biases, due to lack of detailed temporal and original retrieval information. It is therefore preferable to inter-compare or implement satellite derived physical quantities directly with/to model assimilation with as high temporal and spatial resolutions as possible. This study will demonstrate utilization of OMI L2G daily aerosol and ozone products by comparing them with MERRA-2 hourly aerosol/ozone simulations, matched in both space and time aspects. Both OMI and MERRA-2 products are accessible online through NASA Goddard Earth Sciences Data Information Services Center (GES DISC, https://disc.gsfc.nasa.gov/).

OMI L2G products↗

NASA NTRS2018

Life Support Baseline Values and Assumptions Document

The Baseline Values and Assumptions Document (BVAD) provides analysts, modelers, and other life support researchers with a common set of values and assumptions which can be used as a baseline in their studies. This baseline, in turn, provides a common point of origin from which many studies in the community may depart, making research results easier to compare and providing researchers with reasonable values to assume for areas outside their experience. This document identifies many specific physical quantities that define life support systems, serving as a general reference for spacecraft life support system technology developers.

Anderson, Molly S.↗

NASA NTRS2018

Elliptic-Cylindrical Analytical Flux Rope Model for Magnetic Clouds

In this paper, we present the elliptic-cylindrical analytical flux rope model, which constitutes the first level of complexity above that of a circular-cylindrical geometry. The framework of this series of models was established by Nieves-Chinchilla et al. with the circular-cylindrical analytical flux rope model. The model describes the magnetic flux rope topology with distorted cross section as a possible consequence of the flux rope interaction with the solar wind. In this model, for the first time, a flux rope is completely described by a nonorthogonal geometry. The Maxwell equations can be consistently solved using tensorial analysis, and relevant physical quantities can be derived, such as magnetic fluxes, number of turns, or Lorentz force distribution. The model is generalized in termsof the radial dependence of the poloidal and axial current density components. The circular-cylindrical reconstruction technique has been adapted to the new geometry for a specific case of the model and tested againstan interplanetary coronal mass ejection observed by the Wind spacecraft on 2005 June 12. In this specific case,from the comparative analysis between the circular-cylindrical and elliptic-cylindrical models, the inclusion ofthe cross-section distortion in the 3D reconstruction results in significant changes in the derived axis orientation,size, central magnetic field, magnetic fluxes, and force-freeness. The case studied in this paper exemplifies the useof the model and reconstruction technique developed. Furthermore, the novel mathematical formulation to modelflux ropes in heliophysics paves the way to the inclusion of more complex magnetic field configurations.

CMEs↗

NASA NTRS2018

Artificial Neural Networks for Determining Magnetospheric Conditions

This chapter presents a neural-network-based technique that allows for the reconstruction of the global, time-varying distribution of some physical quantity Q, that has been sparsely sampled at various locations within the magnetosphere, and at different times. We begin with a general introduction to the problem of prediction and specification, and why it is important and difficult to achieve with existing methods. We then provide a basic introduction to neural networks, and describe our technique using the specific example of reconstructing the electron plasma density in the Earth's inner magnetosphere on the equatorial plane. We then show more advanced uses of the technique, including 3D reconstruction of the plasma density, specification of chorus and hiss waves, and energetic particle fluxes. We summarize and conclude with a general discussion of how machine learning techniques might be used to advance the state-of-the-art in space weather prediction, and insight discovery.

Bortnik, Jacob↗