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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2020

Future Missions to the Giant Planets that Can Advance Atmospheric Science Objectives

Other papers in this special issue have discussed the diversity of planetary atmospheres and some of the key science questions for giant planet atmospheres to be addressed in the future. There are crucial measurements that can only be made by orbiters of giant planets and probes dropped into their atmospheres. To help the community be more effective developers of missions and users of data products, we summarize how NASA and ESA categorize their planetary space missions, and the restrictions and requirements placed on each category. We then discuss the atmospheric goals to be addressed by currently approved giant-planet missions as well as missions likely to be considered in the next few years, such as a joint NASA/ESA Ice Giant orbiter with atmospheric probe. Our focus is on interplanetary spacecraft, but we acknowledge the crucial role to be played by ground-based and near-Earth telescopes, as well as theoretical and laboratory work.

Mark D Hofstadter↗
NASA NTRS1993

Impasse-Driven Tutoring for Reactive Skill Acquisition

We are interested in developing effective performance-oriented training for the operation of systems that are used for monitor and control purposes. We have focused on one such system, the communications Link Monitor and Control (LMC) system used in NASA's Deep Space Network (DSN), which is a worldwide system for navigating, tracking and communicating with unmanned interplanetary spacecraft. The tasks in this domain are procedural in nature and require reactive, goal-oriented skills; we have previously described a cognitive model for problem solving that accounts for both novice and expert levels of behavior as well as how skill is acquired [Hill and Johnson, 1993]. Our cognitive modeling work in this task domain led us to make a number of predictions about tutoring that have influenced the design of the system described in this paper.

Johnson, W. Lewis↗
NASA NTRS2001

An overview of results from the ion diagnostics sensors flown on DS1

The Deep Space 1 (DS1) mission has successfully validated the use of ion propulsion technology for interplanetary spacecraft. The NASA Solar Electric Propulsion (SEP) Technology Applications Readiness (NSTAR) Project developed the Ion Propulsion Subsystem (IPS) for DS1. As part of the NSTAR validation effort, the NSTAR Project included a diagnostics element to characterize the local environment produced during IPS operations and its effects on spacecraft subsystems and science instruments. An integrated, comprehensive set of diagnostics, the NSTAR Diagnostics Package (NPD) was developed and operated on DS1 to characterize the IPS environment. The DS1 Spacecraft Team officially assigned the name “IPS Diagnostics Subsystems (IDS)” to the NDP for the DS1 mission. During the technology validation phase of the DS1 mission, a large amount of data was collected from the IDS under a variety of IPS operating conditions. IDS was able to characterize the contamination environment, charge-exchange xenon ion and electron population and energies, plasma noise and electromagnetic noise, and magnetic fields associated with IPS. The results presented here describe the charge-exchange plasma, contamination, plasma wave/EMI, and DC magnetic environments critical to designers of future space missions using ion propulsion

Henty, M. D.↗
NASA NTRS1996

Autonomous Optical Navigation for Interplanetary Missions

The automation of interplanetary spacecraft is becoming increasingly desirable to meet various mission requirements. A prototype of an autonomous spacecraft which will fly by an asteroid and comet is slated for flight in mid-1998 as part of NASA's New Millenium Program.

optical↗
NASA NTRS0202

Rest architecture for link analysis tools portal

A web portal is under development to improve overall services provided by NASA networks that support near-­‐Earth missions. These networks are managed by Space Communication and Navigation (SCaN) Program of NASA and include the following: Deep Space Network (DSN), Space Network (SN), and Near-­‐Earth Network (NEN). DSN is a network of antennas located in three longitudinally separated sites and supports interplanetary spacecraft missions, radio science, and radar astronomy observations. SN consists of a number of geostationary Tracking and Data Relay Satellites (TDRS) and associated ground stations. NEN consists of both NASA-­‐owned ground stations and those owned by international, commercial, and academic partners. This study investigates different web access techniques for mission users to use link analysis tools that aid in operating NASA networks. We developed a web portal prototype following principles of Representational state transfer (REST) architecture to leverage scalability, independent deployment of tools, and generic interfaces. In REST architectures, requests and responses between clients and servers are built around transferring representations of resources that can be addressed in memory. We demonstrate the feasibility of using REST architecture to facilitate web-­‐service transactions via web-­‐portal.

Lee, Carlyn-­‐Ann↗
NASA NTRSDate not supplied

Venus Global Reference Atmospheric Model (Venus-GRAM) Upgrades

Introduction: The Venus Global Reference Atmospheric Model (Venus-GRAM) is one of the most widely used engineering models of Venus’ atmosphere. The Venus-GRAM upgrades are being developed by NASA Marshall Space Flight Center (MSFC) and NASA Langley Research Center (LaRC). This presentation will provide details regarding the upgrades that have been made to Venus-GRAM and the ongoing objectives, tasks, and milestones related to the GRAM upgrades funded by the NASA Science Mission Directorate (SMD). Venus-GRAM: Venus-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of the atmospheric properties of Venus. Venus-GRAM provides mean values and variability for any point in the atmosphere as well as seasonal, geographic, and altitude variations. Venus-GRAM outputs include atmospheric density, temperature, pressure, winds, and chemical composition along a user-defined path. It is extensively used by the engineering community because of its ability to create realistic dispersions. GRAMs have been integrated into high fidelity flight dynamic simulations of launch, entry, descent and landing (EDL), aerobraking and aerocapture. GRAMs are currently available for Earth, Mars, Venus, Neptune, Titan, and Uranus. The lower atmosphere model in Venus-GRAM (up to 250 km) is based on the Venus International Reference Atmosphere (VIRA) [1]. The Venus-GRAM thermosphere (250 to 1000 km) is based on a MSFC-developed model [2] which assumes an isothermal temperature profile initialized using VIRA conditions at 250 km [3]. The VIRA version included in Venus-GRAM includes Pioneer Venus Orbiter and Probe data as well as Venera probe data, but it does not include a solid planet model or a high-resolution gravity model [4]. Venus-GRAM Upgrade Status: Code Modernization. Venus-GRAM has been rearchitected from Fortran to a common object-oriented C++ framework called the GRAM Suite. This new architecture creates a common GRAM library of data models and utilities. The first C++ release of the rearchitected Venus-GRAM is a straight conversion from the latest Fortran version. Model Upgrades. The focus of the model upgrade task is to improve the atmosphere models in the existing GRAMs and to establish a foundation for developing GRAMs for additional destinations. The GRAM ephemeris has been upgraded to the NASA Navigation and Ancillary Information Facility (NAIF) SPICE toolkit (version N0066). The calculation of the speed of sound has also been improved in the GRAMs. In FY20, the GRAM project established contracts to improve the model data within Venus-GRAM. Hampton University is developing an empirical global model for Venus. The University of Wisconsin is reanalyzing the Venus Express radio occultation observations and analyzing the Akatsuki thermal imaging data. Upgraded Venus-GRAM Release. GRAM Suite Version 1.3 will be released in September 2021 and will contain the rearchitected Venus-GRAM, including the common GRAM framework and planet–specific code. A User Guide and Programmer’s Manual are released with all GRAMs. Conclusions: GRAMs are frequently used toolsets and vital in assessing effects of atmospheres on interplanetary spacecraft during the program life cycle process. Releases of the GRAM Suite, upgrades of the existing planetary GRAMs, and development of new planetary GRAMs are ongoing. Venus-GRAM atmosphere model upgrades will be included in the next phase of GRAM tasks. References: [1] Kliore, A. J. et al. (1985) ASR, 5, 11, 1-304. [2] Justh, H. L. et al. (2006) AIAA/AAS Astrodynamics Specialist Conference & Exhibit, Abstract AIAA-2006-6394. [3] Guide to Reference and Standard Atmosphere Models, BSR/AIAA G-003-2010. [4] Limaye, S. S. (2012), LPSC VEXAG Townhall Meeting. Acknowledgments: The authors gratefully acknowledge support from the NASA SMD.

atmospheric models↗
NASA NTRSDate not supplied

Prediction and Enhancement of Thermal Protection Systems from Meteoroid Damage using a Smooth Particle Hydrodynamic Code

Interplanetary spacecraft are exposed to meteoroid fluxes that range in speeds from 10 to 72 km/sec, far above the capability of today’s test facilities to provide predictions for the likelihood of spacecraft critical penetration. Of special interest are sample return missions, which (though protected by shielding) must often survive years of exposure to the meteoroid environment in order to re-enter Earth’s atmosphere with their scientific cargo. This paper describes the simulation of meteoric material damage to thermal protection systems (TPS) housed beneath protective “garage” (shielding) enclosures using the Smooth Particle Hydrodynamics Code (SPHC) operated by the Institute for Defense Analyses and Stellingwerf Consulting in support of ongoing NASA tasks. The study outlined in this paper considered the impact effect of both meteoric materials such as iron, ice, and chondrites (dunnite), and non-meteoric materials such as aluminum and nylon against both external shielding materials (single and dual aluminum bumpers) and Heat shield for Extreme Entry Environments Technology (HEEET) TPS materials, used alone and in conjunction with shielding. A general predictive damage equation to HEEET TPS is developed from these SPHC simulations for velocities up to 70 km/sec.

Hypervelocity Impact, hydrocode, meteoroid and orb↗
NASA NTRS2021

Time series comparisons in Deep Space Network

The Deep Space Network (DSN) is NASA’s international array of antennas that support interplanetary spacecraft missions. DSN provides radar and radio astronomy observations that enhance our understanding of the solar system and the larger universe. A track is a block of continuous multi-dimensional time series from the beginning to end of DSN communication with the target spacecraft, containing 129 monitor data items lasting several hours at a frequency of 0.2-1Hz. Monitor data on each track reports on the performance of specific spacecraft operations and the DSN itself. DSN is receiving signals from 32 spacecraft across the solar system. DSN has pressure to reduce costs while maintaining the quality of support for DSN mission users. DSN operators need to simultaneously monitor multiple tracks and identify anomalies in real time. DSN has seen that as the number of missions increases, the data that needs to be processed increases over time. In this project, we look at the last 8 years of data for analysis. Any anomaly in the track indicates a problem with either the spacecraft, DSN equipment, or weather conditions. DSN operators typically write “discrepancy reports” for further analysis. It is recognized that it would be quite helpful to identify 10 similar historical tracks out of the huge database to quickly find/match anomalies. This tool has three functions: (1) identification of the top 10 similar historical tracks, (2) detection of anomalies compared to the reference normal track, and (3) comparison of statistical differences between two given tracks. The requirements for these features were confirmed by survey responses from 21 DSN operators and engineers. The preliminary machine learning model has shown promising performance (AUC=0.92). We plan to increase the number of data sets and perform additional testing to improve performance further before its planned integration into the Track Visualizer to assist DSN field operators and engineers.

Rebbapragada, Umaa↗
NASA NTRS2006

Multi-Spacecraft Observations of Interplanetary Shock Accelerated Particle Events

We use simultaneous measurements from the Wind and ACE spacecraft to determine the spatial properties of both interplanetary (IP) shocks and the shock-associated energetic particle events. We combine plasma, magnetic field and energetic particle data from ACE and Wind for 124 energetic storm particle (ESP) events from 1998 to 2003 and examine the spatial and temporal variations of these events in the Earth's vicinity. We find that even though the two spacecraft were occasionally separated by more than 400 RE, the plasma, field, and energetic particle time-intensity profiles during the events were very similar. In addition, we find that the ion composition and energy spectra in individual IP shock events are identical at the two spacecraft locations. We also use the fitted shock velocity along the normal from ACE and estimate the shock transit time to Wind location. In general, there is poor agreement between the estimated transit time and the actual measured transit time. Hence, our assumptions that a) the IP shock at 1 AU propagates radially, and/or b) the IP shock is spherically symmetric at 1 AU are not valid. In this paper, we will also study, for the first time, the anisotropy measurements of low-energy IP shock-associated ions at both ACE and Wind. We will then compare these new anisotropy analyses with locally measured shock parameters and identify possible signatures of different shock acceleration processes as predicted by the first-order Fermi and shock-drift models.

Ho, G. C.↗
NASA NTRS1986

On the use of a sunward libration-point-orbiting spacecraft as an interplanetary magnetic field monitor for magnetospheric studies

In order to test the accuracy of using magnetometer data from a spacecraft orbiting the sunward libration point to determine the orientation of the interplanetary magnetic field (IMF), the angle between the IMF at ISEE 3, when it was positioned around the libration point, and at ISEE 1, orbiting the earth, has been calculated for a data set of 1-hour periods covering four months. For each period, a 10-minute average of ISEE 1 data is compared with 10-minute averages of ISEE 3 data at successively lagged intervals. It is concluded that the IMF orientation at a libration-point-orbiting spacecraft, lagged by the time required for the solar wind to convect to the earth, is a convenient predictor of IMF orientation near the earth, to within about 20-degree accuracy.

Kelly, T. J.↗
NASA NTRS1995

JPL's Galileo Spacecraft Will Shoot an Interplanetary 'Bulls's Eye'

JPL's Galileo spacecraft, with a December 1995 rendezvous with Jupiter, shot an interplanetary 'bull's eye' when it released its probe to conduct history's first sampling of Jupiter's atmosphere. The probe will slam into Jupiter's hydrogen-helium atmosphere at 100,000 mph as the spacecraft flies overhead and receives and records the probe's data on the structure and composition of the atmosphere.

Galileo Jupiter Interplanetary Spacecraft↗