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This technical paper presents a brief decription of the major activities for this grant during the last three years. Technologyical areas discussed include: model development, ExB convection heating study, study of energetic electron precipitation, polar cap data-model comparison, study of wave heating of O(+), study of photoelectron effects, and study of molecular ion outflow.
Westinghouse Electric Corporation Division under NASA contract NAS3-25865 developed a proof-of-concept (POC) multichannel demultiplexer implemented as an acousto-optic radiofrequency (RF) with a spectrum analyzer. A detailed analysis of the experimental results indicate that the expected degradation caused by the acousto-optical channelizer is approximately 2.0 dB degradation at 10(exp -5) bit-error rate (BER) and 3.0 dB degradation at 10(exp -8) BER. This degradation may be quite acceptable when considering the excellent volume, mass, and power characteristics of acousto-optical channelizing relative to other technologies. In addition, system performance can be greatly improved by using digital pulse shaping in the modem and increasing the channel spacing from 40 to 45 kHz for 64 kbps quadrature phase-shift keying (QPSK) modulation.
Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.
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Wind taken from the National Aeronautics and Space Administration (NASA) scatterometer (NSCAT) is compared with the operational analysis from European Center for Medium-Rnage Forecast (ECMWF) for the entire duration (about 9 months) of the NSCAT mission.
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The MOST IDS team was tasked with focusing on two general areas: The first was to participate with the Fast Plasma Investigation (FPI) team in the development of virtual detectors that model the instrument responses of the MMS FPI sensors. The virtual instruments can be 'flown through' both simulation data (from magnetohydrodynamic, hybrid, and kinetic simulations) and Cluster and THEMIS spacecraft data. The goal is to determine signatures of magnetic reconnection expected during the MMS mission. Such signatures can serve as triggers for selection of burst mode downloads. The chapter contributed by the FPI team covers that effort in detail and, therefore, most of that work has not been included here. The second area of emphasis, and the one detailed in this chapter, was to build on past and present knowledge of magnetic reconnection and its physical signatures. Below we describe intensive analyses of Cluster and THEMIS data together with theoretical models and simulations that delineate the plasma signatures that surround sites of reconnection, including the effects of turbulence as well as the detailed kinetic signatures that indicate proximity to reconnection sites. In particular, we point out that particles are energized in several regions, not only at the actual site of reconnection.
This paper presents a multi-point jig twist optimization study of the Mach 0.745 Transonic Truss-Braced Wing (TTBW) aircraft using an in-house developed aero-structural analysis solver VSPAERO coupled to BEAM3D. A vortex-lattice model of the TTBW model is developed, and a transonic small disturbance /integral boundary layer correction method is implemented in the VSPAERO model to account for transonic and viscous flow effects. A correction method for the wing-strut interference aerodynamics is developed and applied to the VSPAERO solver. Also, a structural dynamic finite-element model of the TTBW aircraft is developed. This finite-element model includes the geometric nonlinear effect due to the tension in the struts which causes a deflection-dependent nonlinear stiffness. The VSPAERO model is coupled to the corresponding finite-element model to provide a rapid aero-structural analysis. The VSPAERO model has been validated against wind tunnel test data and FUN3D CFD simulation data. Three different flight conditions corresponding to Mach 0.745 at 40,000 ft are selected for the TTBW aircraft jig twist optimization to reduce the drag coefficients at the design and off-design cruise lift coefficients. The preliminary optimization results show that the TTBW aircraft with the optimized jig twist achieves a drag reduction of about 9 counts, 7 counts, and8 counts corresponding to the lift coefficients 0.68, 0.73, and 0.78, respectively. A high-fidelity CFD solver FUN3D is used to validate the jig twist optimization.
The Plankton, Aerosol, Cloud ocean Ecosystem (PACE) mission Ocean Color Instrument (OCI) is the next generation ocean color sensor following on from the SeaWiFS and VIIRS designs, to be launched into low Earth orbit in 2022. Like those heritage sensors, OCI has cross track scanning fore-optics, the reflectivity of which (referred to here as the response versus scan angle or RVS) must be characterized prior to launch. The expected test setup, component reflectivity measurements, instrument model, and heritage sensor testing were used to generate simulated RVS data. This simulated data set was then used to verify the functionality of the analysis software in preparation for the upcoming ground test campaign. The analysis software is designed to characterize the RVS for all OCI bands over the full range of scan angles to be measured on orbit as well as verify compliance with the sensor design requirements in near real-time.
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The novel data analysis challenges posed by the Laser Interferometer Space Antenna (LISA) arise from the overwhelmingly large number of astrophysical sources in the measurement band and the density with which they are found in the data. Robust detection and characterization of the numerous gravitational wave sources in LISA data can not be done sequentially, but rather through a simultaneous global fit of a data model containing the full suite of astrophysical and instrumental features present in the data. While previous analyses have focused on individual source types in isolation, here we present the first demonstration of a LISA global fit analysis containing combined astrophysical populations. The prototype pipeline uses a blocked Metropolis Hastings algorithm to alternatingly fit to a population of ultra compact galactic binaries, known “verification binaries” already identified by electromagnetic observations, a population of massive black hole mergers, and an instrument noise model. The Global LISA Analysis Software Suite (GLASS) is assembled from independently developed samplers for the different model components. The modular design enables flexibility to future development by defining standard interfaces for adding new, or updating additional, components to the global fit without being overly prescriptive for how those modules must be internally designed. The GLASS pipeline is demonstrated on data simulated for the LISA Data Challenge 2b. Results of the analysis and a road-map for continued development are described in detail.
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The Artemis I mission successfully demonstrated the Orion Multi-Purpose Crew Module ability to perform a skip re-entry with predictive guidance to reach the target splashdown location. Skip re-entry improves the down-range capability for precision landing, allowing Orion to return to the continental United States at any time during the lunar month, and improves the survivability from a wide range of return trajectories. This paper presents analysis of Orion skip re-entry Guidance and Control performance for the Artemis I mission utilizing recorded flight data and high fidelity simulation data. Descriptions of the related Guidance and Control designs are provided for understanding.
The Artemis I mission successfully demonstrated the Orion Multi-Purpose Crew Module ability to perform a skip re-entry with predictive guidance to reach the target splashdown location. Skip re-entry improves the down-range capability for precision landing, allowing Orion to return to the continental United States at any time during the lunar month, and improves the survivability from a wide range of return trajectories. This paper presents analysis of Orion skip re-entry Guidance and Control performance for the Artemis I mission utilizing recorded flight data and high fidelity simulation data. Descriptions of the related Guidance and Control designs are provided for understanding.
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MISR is scheduled for launch in 1998 on the EOS AM1 platform. The algorithms needed to analyze data from this instrument are currently being tested, using both simulated data and data currently available from the airborne ASAS multi-angle instrument...Results of the retrieval algorithms are presented using simulated MISR data.