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Fifty Years of Exploring Pluto: from Telescopes to the New Horizons Mission
Get PDFPluto was discovered in 1930 at Lowell Observatory in the belated resumption of a wide-field photographic search originally be-gun at Percival Lowells direction prior to his death in 1916. Photometry in the 1950s established the rotation period of 6.4 hours and a color redder than the Sun, but the mass, density, size and albedo were unknown. Near-infrared photometry in 1976 indicated the presence of CH4 frost, suggestive of a relatively high surface albedo and a diameter comparable to the Moon. The large satellite Charon was discovered in 1978, followed by an epoch of mutual transits and occultations of Pluto and Charon from 1985 to 1990, as viewed from Earth. These events resulted in reliable sizes and masses of the two bodies, as well as the orbit of Charon. The mutual events also demonstrated that Pluto and Charon are in locked synchronous rotation and revolution, a configuration unique among the planets. The atmosphere of Pluto was discovered in 1988 from a stellar occultation observed from the Kuiper Airborne Observatory and ground stations, with indications of a haze layer (or a temperature inversion) in the lower atmosphere. Sub-sequent stellar occultations showed that the extent of the atmosphere is variable on a timescale of a few years. The spectroscopic detection of N2 and CO ice in 1993 demonstrated that the atmosphere must be primarily composed of N2, with CH4 and CO as minor components; the spectroscopic detection of gaseous CH4 was reported in 1994
NASA Exploration Mission 2 Mission Design
Get PDFExploration Mission 2 (EM-2) will be NASAs first manned flight on the Space Launch System (SLS) and Orion Spacecraft. The mission has been changed from an SLS Block 1B configuration to Block 1. This change has necessitated a reexamination of the flight profile to determine what changes must be made in order to accommodate the reduced launch vehicle performance on the Block 1. Launch availability and orbital debris risk will be traded to find the best flight profile for both SLS and Orion
NASA Platform for Autonomous Systems (NPAS)
Get PDFNASA Platform for Autonomous Systems (NPAS) is a disruptive software platform and processes being developed by the NASA Stennis Space Center (SSC) Autonomous Systems Laboratory (ASL). Autonomous operations are critical for the success, safety and crew survival of NASA deep space missions beyond low Earth orbit, including the Gateway, and for the future of cost-effective ground mission operations. NPAS represents the embodiment of an innovative paradigm for thinking autonomy in contrast to brute-force autonomy. NPAS uniquely addresses the requirements and integrates the primary functionalities for autonomous operations, in one platform that includes: (1) Integrated System Health Management (ISHM); (2) autonomy strategies, guided by system health and concepts of operations; (3) domain objects (system elements) and infrastructure to create complete application domain knowledge models (4) infrastructure to create, schedule, and execute mission plans; (5) infrastructure to develop user interfaces for comprehensive awareness; and (6) infrastructure to integrate distributed autonomous applications across networks. NPAS is a single platform that can be used to make any system operate with any desirable degree of autonomy, as well as provide comprehensive system awareness to operators and users
Overflow Analysis of Unmanned Aircraft Systems
Get PDFWith the increasing presence of unmanned aircraft systems (UAS), or drones, in the national airspace, the management for access and operation of these vehicles is required. NASAs management approach is being developed under the unmanned aircraft system traffic management (UTM) program. To determine the aerodynamic characteristics of drones, wind tunnel experiments and computation fluid dynamic (CFD) analysis have been conducted. These experiments and analyses are undertaken to understand the flight capabilities of these vehicles in variable head and cross wind conditions. The results of these investigations will provide metrics for the safe operation of these vehicles in and around civil populations and in urban settings. The focus of this paper is to model a drone installed in a wind tunnel for varying pitch attitudes and rotor rpm settings. Specifically, the IRIS drone is modeled in the NASA-Ames 7x10 ft wind tunnel. The tunnel mounting hardware and the tunnel enclosure are modeled along with the IRIS drone geometry. The rotors of the drone are modeled using two methodologies: a rotor disk model and full rotating rotors with moving grids. The results of the analysis are compared with available experimental data to validate the computational approach
Application of a Temperature-Dependent Load Prediction Method to a RUAG Six-Component Block-Type Balance
Get PDFTemperature-dependent data of a RUAG six-component block-type balance was analyzed to assess the accuracy of two load prediction methods for temperature-dependent balance data. The supplied data was prepared for the analysis by splitting it into calibration and check load data subsets. The first calibration data subset was obtained at a temperature of 294 Kelvin. The second calibration data subset was obtained at a temperature of 315 Kelvin. A subset of 38 points was extracted from the second data set and used as check loads so that the accuracy of the two load prediction methods could be tested. First, the Iterative Method in combination with an extended independent and dependent variable set was used for the balance load prediction. This approach fits electrical outputs as a function of loads and the temperature and, afterwards, constructs a load iteration scheme from the regression coefficients so that loads can be predicted from outputs and the temperature during a wind tunnel test. The Non-Iterative Method was also used for the load prediction. This alternate method can more easily be implemented in a data system as loads are directly fitted as a function of electrical outputs and the temperature. Analysis results for the axial force are only discussed in the paper as similar results were obtained for the other five load components. Results for both methods clearly show that the cross-product term constructed from either a primary gage load or a primary gage output and the temperature explains the majority of the temperature-dependent part of the predicted balance load. This term models the temperature dependent nature of the gage sensitivity. Therefore, it is recommended to apply primary gage loadings at different temperatures during a balance calibration whenever temperature effects need to be described. These loadings will contain information about the temperature-dependent nature of the gage sensitivities that can be quantified by related cross-product terms in regression models of the data
Ensemble Lightning Forecasts and Validation over the Hindu Kush Himalayan Region
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