Ground based and satellite observations of the January 28, 1967 solar flare event
Solar flare event of 28 January 1967, observing parent flare location, particle fluxes and diffusion and spectral exponent
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Solar flare event of 28 January 1967, observing parent flare location, particle fluxes and diffusion and spectral exponent
A position-sensitive, low-energy proportional counter system is described which will be used on the High-Energy Astronomical Observatory, Mission A, spacecraft. The associated system incorporates the capability to employ pulse-shape discrimination for background rejection and interpolation circuitry to locate the centroid of an X-ray event with an accuracy of approximately one eighth the cathode-wire spacing.
The method for combining geometrical data with satellite dynamical and gravimetry data for the solution of geopotential and station location parameters is discussed. Geometrical tracking data (simultaneous events) from the global network of BC-4 stations are currently being processed in a solution that will greatly enhance of geodetic world system of stations. Previously the stations in Goddard earth models have been derived only from dynamical tracking data. A linear regression model is formulated from combining the data, based upon the statistical technique of weighted least squares. Reduced normal equations, independent of satellite and instrumental parameters, are derived for the solution of the geodetic parameters. Exterior standards for the evaluation of the solution and for the scale of the earth's figure are discussed.
The measured effects of a circumferential distortion in inlet total pressure on the fan, low, and high compressor of an afterburning turbofan engine are presented and discussed. Extensive inner-stage instrumentation, combined with a unique test technique offered an accurate means of measuring the shifts in flow, performance, and stall mechanisms within the compressor. These effects are compared at one speed to the corresponding effects measured with undistorted inlet flow. The results show the rate at which the distorted flow areas were attenuated and rotated as well as the change in flow velocities that occurred at various points in the compressor. High response pressure traces indicated the location of stalls including the sequence of dynamic events from the onset and propagation of various stall-recovery events, to compressor surge, to the resulting hammershock.
The measured effects of a circumferential distortion in inlet total pressure on the fan, low, and high compressor of an afterburning turbofan engine are presented and discussed. Extensive inner-stage instrumentation, combined with a unique test technique offered an accurate means of measuring the shifts in flow, performance, and stall mechanisms within the compressor. These effects are compared at one speed to the corresponding effects measured with undistorted inlet flow. The results show the rate at which the distorted flow areas were attenuated and rotated, as well as the change in flow velocities that occurred at various points in the compressor. High response pressure traces indicated the location of stalls including the sequence of dynamic events from the onset and propagation of various stall-recovery events, to compressor surge, to the resulting hammershock.
Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated with the monitoring architecture to reduce the volume of event traffic flow in the system, and thereby reduce the intrusiveness of the monitoring process. We are developing an event filtering architecture to efficiently process the large volume of event traffic generated by LSD systems (such as distributed interactive applications). This filtering architecture is used to monitor collaborative distance learning application for obtaining debugging and feedback information. Our architecture supports the dynamic (re)configuration and optimization of event filters in large-scale distributed systems. Our work represents a major contribution by (1) survey and evaluating existing event filtering mechanisms In supporting monitoring LSD systems and (2) devising an integrated scalable high- performance architecture of event filtering that spans several kev application domains, presenting techniques to improve the functionality, performance and scalability. This paper describes the primary characteristics and challenges of developing high-performance event filtering for monitoring LSD systems. We survey existing event filtering mechanisms and explain key characteristics for each technique. In addition, we discuss limitations with existing event filtering mechanisms and outline how our architecture will improve key aspects of event filtering.
The research carried out for this protocol was focused on the study of mesoscales structures at the magnetospheric boundary. We investigated three areas: (1) the structure of the magnetospheric boundary for steady solar wind conditions; (2) the dynamics of the dayside magnetospheric boundary and (3) the dynamics of the distant tail magnetospheric boundary. Our approach was to use high resolution three-dimensional global magnetohydrodynamic (MHD) simulations of the interaction of the solar wind with the Earth's magnetosphere. We first considered simple variations of the interplanetary conditions to obtain generic cases that helped us in establishing the basic cause and effect relationships for steady solar wind conditions. Subsequently, we used actual solar wind plasma and magnetic field parameters measured by an upstream spacecraft as input to the simulations and compared the simulation results with sequences of events observed by another or several other spacecraft located downstream the bow shock. In particular we compared results with observations made when spacecraft crossed the magnetospheric boundary.
NOAA's three-axis stabilized series of GOES satellites have a place reserved on the Earth-facing side for an Instrument of Opportunity (IoO). The IoO slot is a location for new technologies that provide space-time-spectral resolution of the environment not possible with the preconceived Imager and Sounder. For example, candidate IoO's have usually proposed to use large-format staring arrays of detectors. The size, weight, power, data rate, and interface allocations for the IoO are modest in comparison to the Imager and Sounder, but the resources are large enough to allow for the collection of useful real time data. Because, the geosynchronous location is ideal for monitoring rapidly changing unpredictable events, IoO's have been suggested to detect lightning, volcanism, ozone and sulfur dioxide, ocean color, vegetation, special weather events, and even broadcast color TV. To become an IoO on GOES, the proposed instrument must: 1) have potential benefit to NOAA, 2) fit within the allocation constraints, 3) be independently funded, including pre-launch test equipment and the spacecraft accommodation costs, 4) be delivered two years before launch for integration and testing, and 5) not interfere with the existing launch schedule or the operational instruments.
The GENETI-SCANNER, newest product of Perceptive Scientific Instruments, Inc. (PSI), rapidly scans slides, locates, digitizes, measures and classifies specific objects and events in research and diagnostic applications. Founded by former NASA employees, PSI's primary product line is based on NASA image processing technology. The instruments karyotype - a process employed in analysis and classification of chromosomes - using a video camera mounted on a microscope. Images are digitized, enabling chromosome image enhancement. The system enables karyotyping to be done significantly faster, increasing productivity and lowering costs. Product is no longer being manufactured.
To improve aircraft noise impact modeling capabilities and to provide a tool to aid in the development of low noise terminal area operations for rotorcraft and tiltrotors, the Rotorcraft Noise Model (RNM) was developed by the NASA Langley Research Center and Wyle Laboratories. RNM is a simulation program that predicts how sound will propagate through the atmosphere and accumulate at receiver locations located on flat ground or varying terrain, for single and multiple vehicle flight operations. At the core of RNM are the vehicle noise sources, input as sound hemispheres. As the vehicle "flies" along its prescribed flight trajectory, the source sound propagation is simulated and accumulated at the receiver locations (single points of interest or multiple grid points) in a systematic time-based manner. These sound signals at the receiver locations may then be analyzed to obtain single event footprints, integrated noise contours, time histories, or numerous other features. RNM may also be used to generate spectral time history data over a ground mesh for the creation of single event sound animation videos. Acoustic properties of the noise source(s) are defined in terms of sound hemispheres that may be obtained from theoretical predictions, wind tunnel experimental results, flight test measurements, or a combination of the three. The sound hemispheres may contain broadband data (source levels as a function of one-third octave band) and pure-tone data (in the form of specific frequency sound pressure levels and phase). A PC executable version of RNM is publicly available and has been adopted by a number of organizations for Environmental Impact Assessment studies of rotorcraft noise. This paper provides a review of the required input data, the theoretical framework of RNM's propagation model and the output results. Code validation results are provided from a NATO helicopter noise flight test as well as a tiltrotor flight test program that used the RNM as a tool to aid in the development of low noise approach profiles.
Simultaneous wall-pressure and PIV measurements are used to study the conditional flow field associated with surface-pressure generation in a separating/reattaching flow established over a fence-with-splitter-plate geometry. The conditional flow field is captured using linear and quadratic stochastic estimation based on the occurrence of positive and negative pressure events in the vicinity of the mean reattachment location. The results shed light on the dominant flow structures associated with significant wall-pressure generation. Furthermore, analysis based on the individual terms in the stochastic estimation expansion shows that both the linear and non-linear flow sources of the coherent (conditional) velocity field are equally important contributors to the generation of the conditional surface pressure.
We provide an overview of the Vector Electric Field Investigation (VEFI) on the Air Force Communication/Navigation Outage Forecasting System (C/NOFS) satellite, a mission designed to understand, model, and forecast the presence of equatorial ionospheric irregularities. VEFI is a NASA/GSFC instrument funded by the Air Force Research Laboratory whose main objectives are to: 1) investigate the role of the ambient electric fields in initiating nighttime ionospheric density depletions and turbulence; 2) determine the quasi-DC electric fields associated with abrupt, large amplitude, density depletions, and 3) quantify the spectrum of the wave electric fields and plasma densities (irregularities) associated with density depletions typically referred to as equatorial spread-F. The VEFI instrument includes a vector electric field double probe detector, a fixed-bias Langmuir probe operating in the ion saturation regime, a flux-gate magnetometer, an optical lightning detector, and associated electronics. The heart of the instrument is the set of detectors designed to measure DC and AC electric fields using 6 identical booms that provide 3 axis, 20-m tip-to-tip orthogonal double probes. Each probe extends a 10 cm diameter sphere containing an embedded preamplifier. VEFI also includes a burst memory that enables snapshots of data from 1-8 channels of selected instruments to be sampled at rates of up to 32 kHz each. The bursts may be triggered by the detection of density depletions, intense electric field wave activity in a given band, lightning detector pulses, or an event at a pre-determined time or location. All VEFI instrument components are working exceptionally well. A description of the instrument, its sensors, and their sampling frequencies and sensitivities will be presented. Representative measurements will be shown.
A document describes a radio communication system being developed for exchanging data and sharing data-processing capabilities among spacecraft flying in formation. The system would establish a high-speed, low-latency, deterministic loop communication path connecting all the spacecraft in a cluster. The system would be a wireless version of a ring bus that complies with the Institute of Electrical and Electronics Engineers (IEEE) standard 1393 (which pertains to a spaceborne fiber-optic data bus enhancement to the IEEE standard developed at NASA's Jet Propulsion Laboratory). Every spacecraft in the cluster would be equipped with a ring-bus radio transceiver. The identity of a spacecraft would be established upon connection into the ring bus, and the spacecraft could be at any location in the ring communication sequence. In the event of failure of a spacecraft, the ring bus would reconfigure itself, bypassing a failed spacecraft. Similarly, the ring bus would reconfigure itself to accommodate a spacecraft newly added to the cluster or newly enabled or re-enabled. Thus, the ring bus would be scalable and robust. Reliability could be increased by launching, into the cluster, spare spacecraft to be activated in the event of failure of other spacecraft.
The Cryogenic Underground Observatory for Rare Events (CUORE) is a tonne-scale cryogenic experiment located at the Laboratori Nazionali del Gran Sasso that exploits bolometric technique to search for neutrinoless double beta decay [0$vββ$] of 130 Te. The detector consists of a segmented array of 988 natural TeO 2 cubic crystals arranged in a cylindrical compact structure of 19 towers. The detector construction was completed in August 2016 and data taking started in Spring 2017. Here, we present a brief description of the bolometric technique for rare events search and the CUORE detector, then we concentrate on the data analysis results. In this respect, we focus on the procedure for data processing and on the first 0$vββ$ results we obtained from a total TeO 2 exposure of 86.3 kg · yr. Next, we illustrate the main background sources and the CUORE background model, from which we obtain the most precise measurement of 130 Te 2$vββ$ half-life to date. Finally, we discuss the improvements achieved with 2018 and 2019 detector optimization campaigns and the current perspectives of our experiment.
Aims. Our main aim is to study the relationship between low-energy solar particles (energies below 1 MeV) and very narrow coronal mass ejections (“jets” with angular width ≤ 20°). Methods. For this purpose, we considered 125 very narrow coronal mass ejections (CMEs) from 1999 to 2003 that are potentially associated with low-energy solar particles (LESPs). These events were chosen on the basis of their source location. We studied only very narrow CMEs at the western limb, which are expected to have good magnetic connectivity with Earth. Results. We found 24 very narrow CMEs associated with energetic particles such as ions (protons and 3He), electrons, or both. We show that arrival times at Earth of energetic particles are consistent with onset times of the respective CMEs, and that in the same time intervals, there are no other potential sources of energetic particles. We also demonstrate statistical differences for the angular width distributions using the Kolmogorov–Smirnov test for angular widths for these 24 events. We consider a coherent sample of jets (mostly originating from boundaries of coronal holes) to identify properties of events that produce solar energetic particles (velocities, widths, and position angles). Our study presents a new approach and result: very narrow CMEs can generate low-energy particles in the vicinity of Earth without other activity on the Sun. The results could be very useful for space weather forecasting.
One of the most intriguing discoveries of Juno is the quasi-systematic detection of upgoing electrons above the auroral regions. Here we discuss a by-product of the most energetic component of this population: a contamination resembling bar codes in the Juno-UVS images. This pattern is likely caused by bursts of ∼10 MeV electrons penetrating the instrument. These events are mostly detected when Juno’s magnetic footprint is located poleward of the main emission relative to the magnetic pole. The signal is not periodic, but the bursts are typically 0.1–1 s apart. They are essentially detected when Juno-UVS is oriented toward Jupiter, indicating that the signal is due to upgoing electrons. The event detections occur between 1 and 7 Jovian radii above the 1-bar level, suggesting that the electron acceleration takes place close to Jupiter and is thus both strong and brief.
Traffic queues, especially queues caused by non-recurrent events such as incidents, are unexpected to high-speed drivers approaching the end of queue (EOQ) and become safety concerns. Though the topic has been extensively studied, the identification of EOQ has been limited by the spatial-temporal resolution of traditional data sources. This study explores the potential of location-based crowdsourced data, specifically Waze user reports. It presents a dynamic clustering algorithm that can group the location-based reports in real time and identify the spatial-temporal extent of congestion as well as the EOQ. The algorithm is a spatial-temporal extension of the density-based spatial clustering of applications with noise (DBSCAN) algorithm for real-time streaming data with an adaptive threshold selection procedure. Here, the proposed method was tested with 34 traffic congestion cases in the Knoxville, Tennessee area of the United States. It is demonstrated that the algorithm can effectively detect spatial-temporal extent of congestion based on Waze report clusters and identify EOQ in real-time. The Waze report-based detection are compared to the detection based on roadside sensor data. The results are promising: The EOQ identification time of Waze is similar to the EOQ detection time of traffic sensor data, with only 1.1 min difference on average. In addition, Waze generates 1.9 EOQ detection points every mile, compared to 1.8 detection points generated by traffic sensor data, suggesting the two data sources are comparable in respect of reporting frequency. The results indicate that Waze is a valuable complementary source for EOQ detection where no traffic sensors are installed.
Abstract-Two types of single event effects - bit errors and single event functional interrupts - were observed during heavy-ion testing of the AD8151 crosspoint switch. Bit errors occurred in bursts with the average number of bits in a burst being dependent on both the ion LET and on the data rate. A pulsed laser was used to identify the locations on the chip where the bit errors and single event functional interrupts occurred. Bit errors originated in the switches, drivers, and output buffers. Single event functional interrupts occurred when the laser was focused on the second rank latch containing the data specifying the state of each switch in the 33x17 matrix.