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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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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A Generalized Guidance Approach to In-Space Solid-Propellant Vehicle Maneuvers

Exploration-class vehicles that require fully autonomous ascent and descent must employ robust, explicit path-adaptive guidance algorithms that can operate in a wide range of physical environments. Vehicle designs that employ solid-propellant rocket motors (SRMs) for maneuvers are attractive from a systems engineering perspective because of their simplicity and reliability, but may cause complications for both mission designers and GNC engineers when dealing with total impulse uncertainty, as well as proper energy management of a motor with an uncontrolled cutoff time. This paper presents a simplified guidance algorithm, named Simple Cross-Product Steering (SxS), that was derived during early studies of NASA’s Mars Sample Return mission’s Mars Ascent Vehicle. The algorithm takes roots in a flight-proven guidance algorithm commonly referred to as Cross-Product Steering. SxS has been shown to provide sufficient guidance accuracy for in-space SRM burns in a simulated Martian environment, and preliminary studies have been conducted to test the algorithm in a solid-propellant lunar braking scenario. A method for predicting proper motor ignition time during execution of the Cross-Product Steering algorithm is the primary contribution of this paper. Mechanization notes are also provided that were realized in early phases of MAV. Results are shown for an example ascent vehicle in a simulated Mars environment.

GNC↗
NASA NTRS2020

A Generalized Guidance Approach to In-Space Solid-Propellant Vehicle Maneuvers

Exploration-class vehicles that require fully autonomous ascent and descent must employ robust, explicit path-adaptive guidance algorithms that can operate in a wide range of physical environments. Vehicle designs that employ solid-propellant rocket motors (SRMs) for maneuvers are attractive from a system engineering perspective because of their simplicity and reliability but may cause complications for both mission designers and GNC engineers when dealing with total impulse uncertainty, as well as proper energy management of a motor with an uncontrolled cutoff time. This paper presents a simplified guidance algorithm, named Simple Cross-Product Steering (SxS), that was derived during early studies of NASA’s Mars Sample Return mission’s Mars Ascent Vehicle. The algorithm takes roots in a flight-proven guidance algorithm commonly referred to as Cross-Product Steering. This algorithm has been shown to provide sufficient guidance accuracy for in-space SRM burns in a simulated Martian environment, and preliminary studies have been conducted to test the algorithm in a solid-propellant lunar braking scenario. A method for predicting proper motor ignition time during execution of the Cross-Product Steering algorithm is the primary contribution of this paper. Mechanization notes are also provided that were realized in early phases of MAV. Results are shown for an example ascent vehicle a simulated Mars environment.

Jason M Everett↗
NASA NTRSDate not supplied

NASA Space Communications and Navigation Approach to Cloud Capability Implementation

The integration of cloud services and capabilities across government and commercial sectors has continued to increase over the last several years. Cloud architectures provide on-demand process, storage, and transfer of data as a service without the need to purchase expensive hardware, infrastructure, and their associated maintenance costs. Most cloud environments charge the user for only the resources they use, making cloud implementations highly scalable and easily adjustable to the user’s changing demands.

cloud computing↗
NASA NTRS1991

Three dimensional vision - Requirements and applications in a space environment

Various approaches to three-dimensional vision in space are reviewed with emphasis on the redundant 3D vision system designed for the Center for Intelligent Robotic Systems for Space Exploration. The system uses a controllable subset of five cameras, programmable structured light patterns, and sophisticated calibration routines. The design emphasizes real-time operation, human supervisory intervention, and the use of 3D vision to enhance the performance of cooperating robotic arms. Two methods of estimating the location of a point using 3D vision are discussed.

Noseworthy, J. R.↗
NASA NTRS1979

Design of reduced-order controllers for large flexible space structures

Several approaches to the design of reduced-order controllers for large space structures are discussed. The approaches are based on linear-quadratic-Gaussian (LQG) control theory and include truncation, singular perturbation regulator and estimator, direct sensor feedback, higher-order estimator, and selective suppression of some of the uncontrolled or 'residual' modes. Numerical results are given for a long free-free beam. Sufficient conditions for stability in the presence of control and observation spillovers are outlined. It is shown that the system considered can be satisfactorily controlled using a single torque generator and one attitude and one rate sensor.

Joshi, S. M.↗
NASA NTRS1989

Ground-based simulation of telepresence for materials science experiments

A series of ground-based telepresence experiments have been performed to determine the minimum video frame rate and resolution required for the successive performance of materials science experiments in space. The approach used is to simulate transmission between earth and space station with transmission between laboratories on earth. The experiments include isothermal dendrite growth, physical vapor transport, and glass melting. Modifications of existing apparatus, software developed, and the establishment of an inhouse network are reviewed.

Johnston, James C.↗
NASA NTRS1990

The kinematics and dynamics of space manipulators - The virtual manipulator approach

Future robotic manipulator systems will be required to perform complex tasks in space such as satellite repair. These robotic manipulators will encounter a number of kinematic, dynamic, and control problems caused by the dynamic coupling between the manipulators and its spacecraft. This dynamic coupling also makes it difficult to analyze these systems. This paper introduces a new analytical modeling method for space manipulators called the Virtual Manipulator (VM), which has a fixed based in inertial space at a point called a Virtual Ground. The kinematics and dynamics of the manipulator, spacecraft, and payload can be described relatively easily in terms of the VM. With its fixed base, the Virtual Manipulator is shown to have the potential to be an effective aid for the analysis, design, and development of future space manipulator systems.

Vafa, Z.↗
NASA NTRS1991

Space Photovoltaic Research and Technology, 1989

Remarkable progress on a wide variety of approaches in space photovoltaics, for both near and far term applications is reported. Papers were presented in a variety of technical areas, including multi-junction cell technology, GaAs and InP cells, system studies, cell and array development, and non-solar direct conversion. Five workshops were held to discuss the following topics: mechanical versus monolithic multi-junction cells; strategy in space flight experiments; non-solar direct conversion; indium phosphide cells; and space cell theory and modeling.

Source record↗
NASA NTRS1991

A systems approach to the commercialization of space communications technology - The NASA/JPL Mobile Satellite Program

This paper discusss the systems approach taken by NASA and the Jet Propulsion Laboratory in the commercialization of land-mobile satellite services (LMSS) in the United States. As the lead center for NASA's Mobile Satellite Program, JPL was involved in identifying and addressing many of the key barriers to commercialization of mobile satellite communications, including technical, economic, regulatory and institutional risks, or uncertainties. The systems engineering approach described here was used to mitigate these risks. The result was the development and implementation of the JPL Mobile Satellite Experiment Project. This Project included not only technology development, but also studies to support NASA in the definition of the regulatory, market, and investment environments within which LMSS would evolve and eventually operate, as well as initiatives to mitigate their associated commercialization risks. The end result of these government-led endeavors was the acceleration of the introduction of commercial mobile satellite services, both nationally and internationally.

Weber, William J., III↗
NASA NTRSDate not supplied

Increasing accessibility to deep learning-based analytics for space biology: pretrained models, transfer learning, and analytics platform development

Biological systems react in complex ways to the stressors of spaceflight, and the data capturing these relationships is concomitantly high-dimensional and complex. Deep learning and machine learning approaches are increasingly popular as an analytical approach for space biosciences, due to their ability to model complex relationships in complex data. However, such approaches often require large datasets and extensive computational resources. New approaches that minimize data sizes and computational power needed to leverage machine learning, and resources that make these approaches accessible, are needed to increase accessibility and adoption of machine learning in the space biosciences. Transfer learning, in which a pretrained model of broad utility is trained on a large dataset, and subsequently reused on downstream applications for which data is more limited, is one approach to minimizing data and computational intensity of deep learning applications. This transfer learning approach results in more performant models in high-dimensional, low-sample-size settings such as space biology, as compared to training models on limited data from scratch. This presentation will outline efforts to generate pretrained models for the space biology community, and highlight transfer learning applications modeling microbial antibiotic resistance during spaceflight. Finally, in order to increase accessibility of these models and tools, as well as others, for the broader space biology community, we present a modeling and analysis platform facilitating machine learning applications in space biology. This platform streamlines machine learning training and analysis in a notebook format, facilitates download and use of space biology data from the NASA GeneLab database, and can be utilized on NASA-hosted servers or downloaded and hosted locally. This effort, as part of the AI4LS (Artificial Intelligence for Life in Space) working group, will increase accessibility, feasibility, and performance of machine learning approaches for the space biology community.

Adrienne Hoarfrost↗
NASA NTRS2017

NASA's Space Launch System: Systems Engineering Approach for Affordability and Mission Success

NASA is working toward the first launch of the Space Launch System, a new, unmatched capability for deep space exploration with launch readiness planned for 2019. Since program start in 2011, SLS has passed several major formal design milestones, and every major element of the vehicle has produced test and flight hardware. The SLS approach to systems engineering has been key to the program's success. Key aspects of the SLS SE&I approach include: 1) minimizing the number of requirements, 2) elimination of explicit verification requirements, 3) use of certified models of subsystem capability in lieu of requirements when appropriate and 4) certification of capability beyond minimum required capability.

Hutt, John J.↗
NASA NTRS2005

Visions for Space Exploration: ILS Issues and Approaches

This viewgraph presentation reviews some of the logistic issues that the Vision for Space Exploration will entail. There is a review of the vision and the timeline for the return to the moon that will lead to the first human exploration of Mars. The lessons learned from the International Space Station (ISS) and other such missions are also reviewed.

Watson, Kevin↗
NASA NTRS2015

Predicting Space Weather Effects on Close Approach Events

The NASA Robotic Conjunction Assessment Risk Analysis (CARA) team sends ephemeris data to the Joint Space Operations Center (JSpOC) for conjunction assessment screening against the JSpOC high accuracy catalog and then assesses risk posed to protected assets from predicted close approaches. Since most spacecraft supported by the CARA team are located in LEO orbits, atmospheric drag is the primary source of state estimate uncertainty. Drag magnitude and uncertainty is directly governed by atmospheric density and thus space weather. At present the actual effect of space weather on atmospheric density cannot be accurately predicted because most atmospheric density models are empirical in nature, which do not perform well in prediction. The Jacchia-Bowman-HASDM 2009 (JBH09) atmospheric density model used at the JSpOC employs a solar storm active compensation feature that predicts storm sizes and arrival times and thus the resulting neutral density alterations. With this feature, estimation errors can occur in either direction (i.e., over- or under-estimation of density and thus drag). Although the exact effect of a solar storm on atmospheric drag cannot be determined, one can explore the effects of JBH09 model error on conjuncting objects' trajectories to determine if a conjunction is likely to become riskier, less risky, or pass unaffected. The CARA team has constructed a Space Weather Trade-Space tool that systematically alters the drag situation for the conjuncting objects and recalculates the probability of collision for each case to determine the range of possible effects on the collision risk. In addition to a review of the theory and the particulars of the tool, the different types of observed output will be explained, along with statistics of their frequency.

Space Weather↗