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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 NTRS2010

Systems Maintenance Automated Repair Tasks (SMART)

SMART is a uniform automated discrepancy analysis and repair-authoring platform that improves technical accuracy and timely delivery of repair procedures for a given discrepancy (see figure a). SMART will minimize data errors, create uniform repair processes, and enhance the existing knowledge base of engineering repair processes. This innovation is the first tool developed that links the hardware specification requirements with the actual repair methods, sequences, and required equipment. SMART is flexibly designed to be useable by multiple engineering groups requiring decision analysis, and by any work authorization and disposition platform (see figure b). The organizational logic creates the link between specification requirements of the hardware, and specific procedures required to repair discrepancies. The first segment in the SMART process uses a decision analysis tree to define all the permutations between component/ subcomponent/discrepancy/repair on the hardware. The second segment uses a repair matrix to define what the steps and sequences are for any repair defined in the decision tree. This segment also allows for the selection of specific steps from multivariable steps. SMART will also be able to interface with outside databases and to store information from them to be inserted into the repair-procedure document. Some of the steps will be identified as optional, and would only be used based on the location and the current configuration of the hardware. The output from this analysis would be sent to a work authoring system in the form of a predefined sequence of steps containing required actions, tools, parts, materials, certifications, and specific requirements controlling quality, functional requirements, and limitations.

Schuh, Joseph↗

NASA NTRS1980

An interplanetary targeting and orbit insertion maneuver design technique

The paper describes a tradeoff in selecting a planetary encounter aimpoint and a spacecraft propulsive maneuver strategy in the Pioneer Venus Orbiter Mission. The method uses parametric data spanning a region of acceptable targeting aimpoints in the delivery space and the geometric considerations. Real-time maneuver adjustments accounted for known attitude control errors, orbit determination updates, and late changes in a targeting specification.

Hintz, G. R.↗

NASA NTRS2017

Coupled Data Assimilation for Integrated Earth System Analysis and Prediction: Goals, Challenges, and Recommendations

The purpose of this report is to identify fundamental issues for coupled data assimilation (CDA), such as gaps in science and limitations in forecasting systems, in order to provide guidance to the World Meteorological Organization (WMO) on how to facilitate more rapid progress internationally. Coupled Earth system modeling provides the opportunity to extend skillful atmospheric forecasts beyond the traditional two-week barrier by extracting skill from low-frequency state components such as the land, ocean, and sea ice. More generally, coupled models are needed to support seamless prediction systems that span timescales from weather, subseasonal to seasonal (S2S), multiyear, and decadal. Therefore, initialization methods are needed for coupled Earth system models, either applied to each individual component (called Weakly Coupled Data Assimilation - WCDA) or applied the coupled Earth system model as a whole (called Strongly Coupled Data Assimilation - SCDA). Using CDA, in which model forecasts and potentially the state estimation are performed jointly, each model domain benefits from observations in other domains either directly using error covariance information known at the time of the analysis (SCDA), or indirectly through flux interactions at the model boundaries (WCDA). Because the non-atmospheric domains are generally under-observed compared to the atmosphere, CDA provides a significant advantage over single-domain analyses. Next, we provide a synopsis of goals, challenges, and recommendations to advance CDA: Goals: (a) Extend predictive skill beyond the current capability of NWP (e.g. as demonstrated by improving forecast skill scores), (b) produce physically consistent initial conditions for coupled numerical prediction systems and reanalyses (including consistent fluxes at the domain interfaces), (c) make best use of existing observations by allowing observations from each domain to influence and improve the full earth system analysis, (d) develop a robust observation-based identification and understanding of mechanisms that determine the variability of weather and climate, (e) identify critical weaknesses in coupled models and the earth observing system, (f) generate full-field estimates of unobserved or sparsely observed variables, (g) improve the estimation of the external forcings causing changes to climate, (h) transition successes from idealized CDA experiments to real-world applications. Challenges: (a) Modeling at the interfaces between interacting components of coupled Earth system models may be inadequate for estimating uncertainty or error covariances between domains, (b) current data assimilation methods may be insufficient to simultaneously analyze domains containing multiple spatiotemporal scales of interest, (c) there is no standardization of observation data or their delivery systems across domains, (d) the size and complexity of many large-scale coupled Earth system models makes it is difficult to accurately represent uncertainty due to model parameters and coupling parameters, (e) model errors lead to local biases that can transfer between the different Earth system components and lead to coupled model biases and long-term model drift, (e) information propagation across model components with different spatiotemporal scales is extremely complicated, and must be improved in current coupled modeling frameworks, (h) there is insufficient knowledge on how to represent evolving errors in non-atmospheric model components (e.g. as sea ice, land and ocean) on the timescales of NWP.

CDA↗

NASA NTRS2017

Resolution of Orbit Determination Prediction Instabilities at Titan During Cassini's Solstice Mission

The Cassini spacecraft has been in orbit about Saturn since 2004. Exploration of the Saturn system is driven by gravitational flybys of the moon Titan which alter the spacecraft trajectory. The Cassini Navigation Team receives regular updates to the Saturn satellites ephemeris from JPL's Solar System Dynamics group. The difference between subsequent ephemeris deliveries can be hundreds of meters in the position of Titan at the time of a flyby. Errors in Titan's position propagate downstream to the next flyby through the estimated spacecraft trajectory. Prior to 2013, the Cassini Orbit Determination Team estimated the Saturn satellite ephemeris parameters and used the a posteriori states and covariance of an operations arc as a priori inputs to subsequent estimation arcs. Since 2013, the OD Team has only been considering errors in the ephemeris and not estimating a correction to the satellite positions. The T119 Titan flyby exhibited a 3D miss distance of 2.44 km and the following T120 flyby yielded a smaller miss of 1.06 km at the 2.9s error level. These discrepancies between pre-flyby prediction and post-flyby trajectory reconstruction were due to errors in the Titan ephemeris. In order to improve the targeting of Titan in future flybys, the team restarted the satellite ephemeris estimation process for orbit determination solutions. Subsequent flybys had target misses of less than 1 km at the sub-3 error level. This paper describes the method of scaling the a priori satellite ephemeris covariance in the orbit determination process to allow larger corrections to the satellite system and improve the prediction of the spacecraft’s Titan-relative position at the time of encounters.

Boone, Dylan↗

NASA NTRS1994

Software interface verifier

A Telos study of 40 recent subsystem deliveries into the DSN at JPL found software interface testing to be the single most expensive and error-prone activity, and the study team suggested creating an automated software interface test tool. The resulting Software Interface Verifier (SIV), which was funded by NASA/JPL and created by Telos, employed 92 percent software reuse to quickly create an initial version which incorporated early user feedback. SIV is now successfully used by developers for interface prototyping and unit testing, by test engineers for formal testing, and by end users for non-intrusive data flow tests in the operational environment. Metrics, including cost, are included. Lessons learned include the need for early user training. SIV is ported to many platforms and can be successfully used or tailored by other NASA groups.

Soderstrom, Tomas J.↗

NASA NTRS1993

Design decisions from the history of the EUVE science payload

Some of the design issues that arose during the development of the EUVE science payload and solutions to the problems involved are examined. In particular, attention is given to the use of parallel and serial busses, the selection of the the ROM approach for software storage and execution, implementation of memory error detection and correction, and the selection of command structures. The early design decisions paid off in the timely delivery of the scientific payload and in the successful completion of the survey phase of the EUVE science mission.

Marchant, W.↗

NASA NTRS2006

CFDP Performance over Weather-Dependent Ka-Band Channel

This study presents an analysis of the delay performance of the CCSDS File Delivery Protocol (CFDP) over weather-dependent Ka-band channel. The Ka-band channel condition is determined by the strength of the atmospheric noise temperature, which is weather dependent. Noise temperature data collected from the Deep Space Network (DSN) Madrid site is used to characterize the correlations between good and bad channel states in a two-state Markov model. Specifically, the probability distribution of file delivery latency using the CFDP deferred Negative Acknowledgement (NAK) mode is derived and quantified. Deep space communication scenarios with different file sizes and bit error rates (BERs) are studied and compared. Furthermore, we also examine the sensitivity of our analysis with respect to different data sampling methods. Our analysis shows that while the weather-dependent channel only results in fairly small increases in the average number of CFDP retransmissions required, the maximum number of transmissions required to complete 99 percentile, on the other hand, is significantly larger for the weather-dependent channel due to the significant correlation of poor weather states.

weather↗

NASA NTRS1980

Test Bed Concentrator (TBC)

A point focussing concentrator design adapted from an existing communications antenna for use in a solar test bed application is described. The structure design, configured for use with JPL's spherical radius mirror panels, made no attempt toward optimization. The key objectives of stiffness, pointing accuracy, and timely delivery were exceeded. The system weight is approximately 16,000 Kg (36,000 lbs) and has a calculated 1 sigma system error of 0.03 degrees.

Goldberg, V. R.↗

NASA NTRS2017

A First Look at the Navigation Design and Analysis for the Orion Exploration Mission 2

This paper will detail the navigation and dispersion design and analysis of the first Orion crewed mission. The optical navigation measurement model will be described. The vehicle noise includes the residual acceleration from attitude deadbanding, attitude maneuvers, CO2 venting, wastewater venting, ammonia sublimator venting and solar radiation pressure. The maneuver execution errors account for the contribution of accelerometer scale-factor on the accuracy of the maneuver execution. Linear covariance techniques are used to obtain the navigation errors and the trajectory dispersions as well as the DV performance. Particular attention will be paid to the accuracy of the delivery at Earth Entry Interface and at the Lunar Flyby.

D'Souza, Chris D.↗

NASA NTRSDate not supplied

NASA's Deep Space Network (DSN) Lunar Exploration Upgrades (DLEU)

In the near future, the National Aeronautics and Space Administration (NASA) will return to the moon beginning the next era of human exploration. NASA’s Space Communications and Navigation (SCaN) program will play a vital role in establishing communications and navigation support to realize the ambitious goals of the Artemis program. SCaN’s overall lunar communications support plan will be covered in a separate 2023 SpaceOps paper: “NASA’s Communications and Navigation Architecture Plans to Support the Return to the Moon and a Sustainable Lunar Presence”. The plan as it currently stands, includes a three-fold approach of lunar relay services, a dedicated set of new ground stations and support through the Deep Space Network (DSN). This paper will have a more granular focus on the DSN and NASA’s plans to upgrade and expand the network to be better suited for human spaceflight on and around the lunar surface. NASA’s Deep Space Network (DSN) will be a critical communications component for the upcoming lunar activities. There will be multiple spacecraft, using different bands, and some of those spacecraft will be transmitting and receiving using multiple bands, requiring DSN support of S-band (2 GHz), X-band (7 GHz up, 8 GHz down), and K-band (22.5 GHz up, 26 GHz down). Since there may be more than one spacecraft in the beamwidth of the DSN antennas, the DSN support will require an extension of the DSN’s capability to support multiple spacecraft using one antenna, expanding it to provide two simultaneous uplinks in the different bands at each antenna. Achieving this requires using new techniques for manufacturing the frequency selective surfaces, called dichroics, which steer the different frequency beams from and to the appropriate transmitting and receiving equipment, along with the addition of a new K-band uplink system. Additionally, due to the relative closeness of the moon from Earth (as opposed to the planetary missions the DSN supports daily), significantly higher data rates on both uplink and downlink are required, specifically up to 20 Mbps on the uplink and 150 Mbps on the downlink, both using Low Density Parity Check (LDPC) error correcting codes. And, again due to the relative closeness of the moon, there is a need for low latency data delivery of the high rate downlink telemetry which requires a change in the current DSN paradigm of delivering higher rate data with higher latency.

deep space network↗

NASA NTRSDate not supplied

NASA’s Deep Space Network (DSN) Lunar Exploration Upgrades (DLEU)

In the near future, the National Aeronautics and Space Administration (NASA) will returnhumansto the moon beginning the next era of human exploration. NASA’s Space Communications and Navigation (SCaN) program will play a vital role in establishing communications and navigation support to realize the ambitious goals of the Artemis program. SCaN’s overall lunar communications support plan will be covered in a separate 2023 SpaceOps paper: “NASA’s Communications and Navigation Architecture Plans to Support the Return to the Moon and a Sustainable Lunar Presence.” The four-point plan,as it currently stands, includes lunar relay services, a dedicated set of new ground stations, international partner contributions,and supportthrough the Deep Space Network (DSN)and associated upgrades. This paper will have a more granular focus on the DSN and NASA’s plans to upgrade and expand the network to be better suited for human spaceflight on and around the lunar surface. NASA’s Deep Space Network (DSN) will be a critical communications component for the upcoming lunar activities. There will be multiple spacecraft, using different bands, and some of those spacecraft will be transmitting and receiving using multiple bands, requiring DSN support of S-band (2 GHz), X-band (7 GHz up, 8 GHz down), and K-band (22.5 GHz up, 26 GHz down). Since there may be more than one spacecraft in the beamwidth of the DSN antennas, the DSN support will require an extension of the DSN’s capability to support multiple spacecraft using one antenna, expanding it to provide two simultaneous uplinks in the different bands at each antenna. Achieving this requires using new techniques for manufacturing the frequency selective surfaces, called dichroics, which steer the different frequency beams from and to the appropriate transmitting and receiving equipment, along with the addition of a new K-band uplink system. Additionally, due to the relative closeness of the moon from Earth (as opposed to the planetary missionsthe DSN supports daily), significantly higher data rates on both uplink and downlinkare requiredare possible and desirable by the lunar missions, specifically up to 20 Mbps on the uplink and 150 Mbps on the downlink, both using Low Density Parity Check (LDPC) error correcting codes. And, again due to the relative closeness of the moon, there is a need for low latency data delivery of the high rate downlink telemetry which requires a change in the current DSN paradigm of delivering higher rate data with higher latency.

Moon↗

NASA NTRS2004

Mars Exploration Rovers navigation results

The twin Mars Exploration Rovers, Spirit and Opportunity, were launched on June 10, 2003(dagger), and July 8, 2003, from Cape Canaveral, Florida. Spirit and Opportunity were targeted for landings at Gusev Crater (arrival on January 4, 2004) and Meridiani Planum (arrival on January 25, 2004). The primary navigation challenge was to deliver each spacecraft to the desired atmospheric entry interface point with sufficient accuracy such that each lander would touch down within a specified landing ellipse (about 70 km x 5 km) determined to be safe for landing and also judged to be scientifically interesting. In order to achieve landing within the target ellipse, precise control of the inertial entry flight path angle (FPA) at atmospheric entry was required. The maximum allowable errors in FPA following TCM-5 (trajectory correction maneuver #5) at Entry (E) - 2 days were +/-0.12(deg) (3(sigma)) for Spirit and +/-0.14(deg) (3(sigma)) for Opportunity. Achieving these entry delivery accuracies necessitated significant improvements to the interplanetary avigation system used for MER. These improvements included new processes and software for orbit determination, propulsive maneuver design, and entry, descent, and landing (EDL) trajectory simulation. The actual achieved atmospheric entry accuracies for Spirit and Opportunity significantly exceeded the requirements. At the navigation data cutoff for the TCM-5 final design, the orbit determination FPA knowledge error was +/-0.028(deg) (3(sigma) ) for Spirit and +/-0.035(deg) (3(sigma)) for Opportunity. Because of exceptionally accurate navigation performance, TCM-5 (E - 2 days) and TCM-6 (E - 4 hours) were canceled for both Spirit and Opportunity. The actual landing locations (determined from in-situ Doppler tracking between the MER rovers and the Mars Odyssey orbiter) differed from the target landing points by 10.1 km (downtrack) for Spirit and 24.6 km (downtrack) for Opportunity. The majority of the landing position offsets for both landers was primarily caused by variations in atmosphere and spacecraft aerodynamic modeling from what was predicted. The amount of the landing position offset caused by navigation-only errors was only 3.3 km (uptrack) for Spirit and 9.7 km (downtrack) for Opportunity.

Mars Exploration Rover (MER)↗

NASA NTRS2004

Mars Exploration Rovers navigation results

The twin Mars Exploration Rovers, Spirit and Opportunity, were launched on June 10, 2003, and July 8, 2003, from Cape Canaveral, Florida. Spirit and Opportunity were targeted for landings at Gusev Crater (arrival on January 4, 2004) and Meridiani Planum (arrival on January 25, 2004). The primary navigation challenge was to deliver each spacecraft to the desired atmospheric entry interface point with sufficient accuracy such that each lander would touch down within a specified landing ellipse (about 70 km x 5 km) determined to be safe for landing and also judged to be scientifically interesting. In order to achieve landing within the target ellipse, precise control of the inertial entry flight path angle (FPA) at atmospheric entry was required. The maximum allowable errors in FPA following TCM-5 (trajectory correction maneuver #5) at Entry (E) -2 days were +/-0.12 deg(3 sigma) for Spirit and +/-0.14 deg(3 sigma) for Opportunity. Achieving these entry delivery accuracies necessitated significant improvements to the interplanetary navigation system used for MER. These improvements included new processes and software for orbit determination, propulsive maneuver design, and entry, descent, and landing (EDL) trajectory simulation. The actual achieved atmospheric entry accuracies for Spirit and Opportunity significantly exceeded the requirements. At the navigation data cutoff for the TCM-5 final design, the orbit determination FPA knowledge error was 0.028 deg(3 sigma) for Spirit and 0.035 deg(3 sigma) for Opportunity. Because of exceptionally accurate navigation performance, TCM-5 (E - 2 days) and TCM-6 (E - 4 hours) were canceled for both Spirit and Opportunity. The actual landing locations (determined from in-situ Doppler tracking between the MER rovers and the Mars Odyssey orbiter) differed from the target landing points by 10.1 km (downtrack) for Spirit and 24.6 km (downtrack) for Opportunity. The majority of the landing position offsets for both landers was primarily caused by variations in atmosphere and spacecraft aerodynamic modeling from what was predicted. The amount of the landing position offset caused by navigation-only errors was only 3.3 km (uptrack) for Spirit and 9.7 km (downtrack) for Opportunity.

Mars Exploration Rover (MER)↗

NASA NTRS1998

MODIS Science Team Member Semi-annual Report

This paper presents a semi-annual report of the MODerate resolution imaging Spectroradiometer (MODIS) Science Team Members. The most important activities undertaken during this reporting period are the following: 1) Versions 2.1 and 2.2 surface reflectance L2/L3 DAAC/SDST delivery; 2) Version 2.0 1km and 250m VI product delivery (assist Arizona); 3) Version 2.1 surface reflectance L2 testing; 4) Land Synthetic data set generator improvements; 5) QA; 6) Surface reflectance error budget generation (SWAMP request); 7) SCF Hardware; 8) Aerosol transport modeling; 9) Aerosol optical depth retrieval from AVHRR data; 10) Aerosol characteristics retrieval from SeaWIFS/AVHRR fusioned data; 11) Validation activities; 12) Aerosol climatology; and 13) 6S code. The report includes summaries of the topics above.

Vermote, Eric↗

NASA NTRSDate not supplied

Preliminary Statistical Maneuver Analysis for A Low-Thrust NRHO to DRO Transfer

To understand practical implications of implementing transfers that leverage multibody dynamics, a statistical analysis is performed on an Earth-Moon Near Rectilinear Halo Orbit (NRHO) to distant retrograde orbit (DRO) transfer using solar electric propulsion. The statistical analysis includes perturbations due to maneu- ver execution and orbit determination error to understand operational character- istics of the transfer such as statistical ∆V and statistical state targeting errors at the final DRO. We explore the need for low-thrust trajectory correction maneuver (TCM) opportunities as well as the delivery accuracy to the final target. Finally, we explore options for long-term-stable target DROs.

low thrust↗

NASA NTRS2003

Navigation for the Mars PREMIER netlander delivery

This paper presents covariance and propulsive maneuver analyses performed to determine the impact on navigation performance of parameters such as: the addition of deltaDOR measurements, tracking data schedule, and maneuver execution errors.

approach↗

NASA NTRS1992

Deep Space Network information system architecture study

The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control.

Beswick, C. A.↗

NASA NTRS2006

CFDP Performance over Weather-dependent Ka-band Channel

deep space communications↗