Search NASA⌕ Search

SEARCH · Search NASA

Results for “Learning and Development”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Lessons learned in the development of the Hubble Space Telescope software

An effort is made to document what was successful in the HST software development, and to present a retrospective analysis indicating what could have been done more efficiently. Consideration is given to systems engineering and design definition, standards and tools, system architecture and design, operational considerations, and reuse and adaptation of existing resources.

Harrington, Michael↗
NASA NTRS1992

Linear decentralized learning control

The new field of learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this task. The simplest forms of learning control are based on the same concept as integral control, but operating in the domain of the repetitions of the task. This paper studies the use of such controllers in a decentralized system, such as a robot with the controller for each link acting independently. The basic result of the paper is to show that stability of the learning controllers for all subsystems when the coupling between subsystems is turned off, assures stability of the decentralized learning in the coupled system, provided that the sample time in the digital learning controller is sufficiently short.

Lee, Soo C.↗
NASA NTRS2005

REIMR: A Process for Utilizing Propulsion-Oriented 'Lessons-Learned' to Mitigate Development Risk

This paper is a summary overview of a study conducted a t the NASA Marshall Space Flight Center (MSFC) during the initial phases of the Space Launch Initiative (SLI) program to evaluate a large number of technical problems associated with the design, development, test, evaluation and operation of several major liquid propellant rocket engine systems (i.e., SSME, Fastrac, J-2, F-1). The results of this study was the identification of the "Fundamental Root Causes" that enabled the technical problems to manifest, and practices that can be implemented to prevent them from recurring in future engine development efforts. This paper will discus the Fundamental Root Causes, cite some examples of how the technical problems arose from them, and provide a discussion of how they can be mitigated or avoided.

Ballard, Richard O.↗
NASA NTRS2006

REIMR - A Process for Utilizing Liquid Rocket Propulsion-Oriented 'Lessons Learned' to Mitigate Development Risk in Nuclear Thermal Propulsion

This paper is a summary overview of a study conducted at the NASA Marshall Space Flight Center (NASA MSFC) during the initial phases of the Space Launch Initiative (SLI) program to evaluate a large number of technical problems associated with the design, development, test, evaluation and operation of several major liquid propellant rocket engine systems (i.e., SSME, Fastrac, J-2, F-1). One of the primary results of this study was the identification of the Fundamental Root Causes that enabled the technical problems to manifest, and practices that can be implemented to prevent them from recurring in future propulsion system development efforts, such as that which is currently envisioned in the field of nuclear thermal propulsion (NTF). This paper will discuss the Fundamental Root Causes, cite some examples of how the technical problems arose from them, and provide a discussion of how they can be mitigated or avoided in the development of an NTP system

Ballard, RIchard O.↗
NASA NTRS2004

Development of a State Machine Sequencer for the Keck Interferometer: Evolution, Development and Lessons Learned using a CASE Tool Approach

This paper presents a discussion of the evolution of a sequencer from a simple EPICS (Experimental Physics and Industrial Control System) based sequencer into a complex implementation designed utilizing UML (Unified Modeling Language) methodologies and a CASE (Computer Aided Software Engineering) tool approach. The main purpose of the sequencer (called the IF Sequencer) is to provide overall control of the Keck Interferometer to enable science operations be carried out by a single operator (and/or observer). The interferometer links the two 10m telescopes of the W. M. Keck Observatory at Mauna Kea, Hawaii. The IF Sequencer is a high-level, multi-threaded, Hare1 finite state machine, software program designed to orchestrate several lower-level hardware and software hard real time subsystems that must perform their work in a specific and sequential order. The sequencing need not be done in hard real-time. Each state machine thread commands either a high-speed real-time multiple mode embedded controller via CORB A, or slower controllers via EPICS Channel Access interfaces. The overall operation of the system is simplified by the automation. The UML is discussed and our use of it to implement the sequencer is presented. The decision to use the Rhapsody product as our CASE tool is explained and reflected upon. Most importantly, a section on lessons learned is presented and the difficulty of integrating CASE tool automatically generated C++ code into a large control system consisting of multiple infrastructures is presented.

interferometer↗
NASA NTRS2014

Design and Lessons Learned on the Development of a Cryogenic Pupil Select Mechanism (PSM)

Calibration and testing of the instruments on the Integrated Science Instrument Module (ISIM) of the James Webb Space Telescope (JWST) is being performed by the use of a cryogenic, full-field, optical simulator that was constructed for this purpose. The Pupil Select Mechanism (PSM) assembly is one of several mechanisms and optical elements that compose the Optical Telescope Element SIMulator, or OSIM. The PSM allows for several optical elements to be inserted into the optical plane of OSIM, introducing a variety of aberrations, distortions, obscurations, and other calibration states into the pupil plane. The following discussion focuses on the details of the design evolution, analysis, build, and test of this mechanism along with the challenges associated with creating a sub arc-minute positioning mechanism operating in an extreme cryogenic environment. In addition, difficult challenges in the control system design will be discussed including the incorporation of closed-loop feedback control into a system that was designed to operate in an open-loop fashion.

PSM Design↗
NASA NTRS2014

Using a Support Vector Machine and a Land Surface Model to Estimate Large-Scale Passive Microwave Temperatures over Snow-Covered Land in North America

A support vector machine (SVM), a machine learning technique developed from statistical learning theory, is employed for the purpose of estimating passive microwave (PMW) brightness temperatures over snow-covered land in North America as observed by the Advanced Microwave Scanning Radiometer (AMSR-E) satellite sensor. The capability of the trained SVM is compared relative to the artificial neural network (ANN) estimates originally presented in [14]. The results suggest the SVM outperforms the ANN at 10.65 GHz, 18.7 GHz, and 36.5 GHz for both vertically and horizontally-polarized PMW radiation. When compared against daily AMSR-E measurements not used during the training procedure and subsequently averaged across the North American domain over the 9-year study period, the root mean squared error in the SVM output is 8 K or less while the anomaly correlation coefficient is 0.7 or greater. When compared relative to the results from the ANN at any of the six frequency and polarization combinations tested, the root mean squared error was reduced by more than 18 percent while the anomaly correlation coefficient was increased by more than 52 percent. Further, the temporal and spatial variability in the modeled brightness temperatures via the SVM more closely agrees with that found in the original AMSR-E measurements. These findings suggest the SVM is a superior alternative to the ANN for eventual use as a measurement operator within a data assimilation framework.

Modeling↗
NASA NTRS2014

Design and Lessons Learned on the Development of a Cryogenic Pupil Select Mechanism used in the Testing and Calibration of the Integrated Science Instrument Module (ISIM) on the James Webb Space Telescope (JWST)

Calibration and testing of the instruments on the Integrated Science Instrument Module (ISIM) of the James Webb Space Telescope (JWST) is being performed by the use of a cryogenic, full-field, optical simulator that was constructed for this purpose. The Pupil Select Mechanism (PSM) assembly is one of several mechanisms and optical elements that compose the Optical Telescope Element SIMulator, or OSIM. The PSM allows for several optical elements to be inserted into the optical plane of OSIM, introducing a variety of aberrations, distortions, obscurations, and other calibration states into the pupil plane. The following discussion focuses on the details of the design evolution, analysis, build, and test of this mechanism along with the challenges associated with creating a sub arc-minute positioning mechanism operating in an extreme cryogenic environment. In addition, difficult challenges in the control system design will be discussed including the incorporation of closed-loop feedback control into a system that was designed to operate in an open-loop fashion.

Mitchell, Alissa↗
NASA NTRS2025

Evolving the SpaceFOM: Lessons Learned and Future Development

For over fifty years, simulation has been a cornerstone technology for space missions. In many cases, one single simulator, developed by one team, is not enough to meet the simulation objectives. Astronaut crew training, docking, vehicle testing and complex mission planning all require several simulations to be connected and to interoperate, in order to achieve the goal of the simulation. To facilitate the development of interoperable simulations, an open standard, the SISO SpaceFOM was developed in collaboration between government, industry and academia. The standard was released in 2020. The initial release of SpaceFOM focuses on the core interoperability topics for space simulation: (i) specifying spatial data using several, well defined reference frames, (ii) managing time (including real-time, hard real-time, and as-fast-as-possible execution), (iii) composition of systems with subsystems such as space vehicles, and (iv) execution control, such as initializing, running, pausing, and terminating simulations. The initial release of SpaceFOM focuses on the core interoperability topics for space simulation: (i) specifying spatial data using several, well defined reference frames, (ii) managing time (including real-time, hard real-time, and as-fast-as-possible execution), (iii) composition of systems with subsystems such as space vehicles, and (iv) execution control, such as initializing, running, pausing, and terminating simulations. A number of requirements for the next version of SpaceFOM have been identified and proposed solutions are already under development. One key area is the object classes used for data exchange, where a richer set of classes have been proposed, based on practical use cases. For time management, the use of variable time resolutions and variable time steps is also proposed. For execution control, save and restore of simulations is considered as well as improved robustness, to handle failing components. A number of clarifications are also under consideration. This paper provides both a forward-looking view of the technical developments underway and a retrospective on the standard's evolution. The authors emphasize that prioritizing core challenges and delivering a practical first version were crucial steps. While not every idea was implemented in the initial release, the timely delivery of a functional standard enabled real-world applications, the growth of a user community, and the collection of valuable insights to shape future versions. The authors look forward to working with the next version of SpaceFOM together with the growing user community.

Simulation Interoperability↗
NASA NTRSDate not supplied

Evolving the SpaceFOM: Lessons Learned and Future Development

For over fifty years, simulation has been a cornerstone technology for space missions. In many cases, one single simulator, developed by one team, is not enough to meet the simulation objectives. Astronaut crew training, docking, vehicle testing and complex mission planning all require several simulations to be connected and to interoperate, in order to achieve the goal of the simulation. To facilitate the development of interoperable simulations, an open standard, the SISO SpaceFOM was developed in collaboration between government, industry and academia. The standard was released in 2020. The initial release of SpaceFOM focuses on the core interoperability topics for space simulation: (i) specifying spatial data using several, well defined reference frames, (ii) managing time (including real-time, hard real-time, and as-fast-as-possible execution), (iii) composition of systems with subsystems such as space vehicles, and (iv) execution control, such as initializing, running, pausing, and terminating simulations. A number of requirements for the next version of SpaceFOM have been identified and proposed solutions are already under development. One key area is the object classes used for data exchange, where a richer set of classes have been proposed, based on practical use cases. For time management, the use of variable time resolutions and variable time steps is also proposed. For execution control, save and restore of simulations is considered as well as improved robustness, to handle failing components. A number of clarifications are also under consideration. This paper provides both a forward-looking view of the technical developments underway and a retrospective on the standard's evolution. The authors emphasize that prioritizing core challenges and delivering a practical first version were crucial steps. While not every idea was implemented in the initial release, the timely delivery of a functional standard enabled real-world applications, the growth of a user community, and the collection of valuable insights to shape future versions. The authors look forward to working with the next version of SpaceFOM together with the growing user community.

FOMs↗