Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Continual Learning”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Effect of continuous gamma-ray exposure on performance of learned tasks and effect of subsequent fractionated exposures on blood-forming tissue

Sixteen monkeys trained to perform continuous and discrete-avoidance and fixed-ratio tasks with visual and auditory cues were performance-tested before, during, and after 10-day gamma-ray exposures totaling 0, 500, 750, and 1000 rads. Approximately 14 months after the performance-test exposures, surviving animals were exposed to 100-rad gamma-ray fractions at 56-day intervals to observe injury and recovery patterns of blood-forming tissues. The fixed-ratio, food-reward task performance showed a transient decline in all dose groups within 24 hours of the start of gamma-ray exposure, followed by recovery to normal food-consumption levels within 48 to 72 hours. Avoidance tasks were performed successfully by all groups during the 10-day exposure, but reaction times of the two higher dose-rate groups in which animals received 3 and 4 rads per hour or total doses of 750 and 1000 rads, respectively, were somewhat slower.

Spalding, J. F.↗
NASA NTRS2010

LDCM Ground System. Network Lesson Learned

This slide presentation reviews the Landsat Data Continuity Mission (LDCM) and the lessons learned in implementing the network that was assembled to allow for the acquisition, archiving and distribution of the data from the Landsat mission. The objective of the LDCM is to continue the acquisition, archiving, and distribution of moderate-resolution multispectral imagery affording global, synoptic, and repetitive coverage of the earth's land surface at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. It includes a review of the ground network, including a block diagram of the ground network elements (GNE) and a review of the RF design and testing. Also included is a listing of the lessons learned.

Gal-Edd, Jonathan↗
NASA NTRS1991

Analog VLSI neural network integrated circuits

Two analog very large scale integration (VLSI) vector matrix multiplier integrated circuit chips were designed, fabricated, and partially tested. They can perform both vector-matrix and matrix-matrix multiplication operations at high speeds. The 32 by 32 vector-matrix multiplier chip and the 128 by 64 vector-matrix multiplier chip were designed to perform 300 million and 3 billion multiplications per second, respectively. An additional circuit that has been developed is a continuous-time adaptive learning circuit. The performance achieved thus far for this circuit is an adaptivity of 28 dB at 300 KHz and 11 dB at 15 MHz. This circuit has demonstrated greater than two orders of magnitude higher frequency of operation than any previous adaptive learning circuit.

Kub, F. J.↗
NASA NTRS2012

NASA's Space Launch System: A Flagship for Exploration Beyond Earth's Orbit

The National Aeronautics and Space Administration s (NASA) Space Launch System (SLS) Program, managed at the Marshall Space Flight Center, is making progress toward delivering a new capability for exploration beyond Earth orbit in an austere economic climate. This fact drives the SLS team to find innovative solutions to the challenges of designing, developing, fielding, and operating the largest rocket in history. To arrive at the current SLS plan, government and industry experts carefully analyzed hundreds of architecture options and arrived at the one clear solution to stringent requirements for safety, affordability, and sustainability over the decades that the rocket will be in operation. This paper will explore ways to fit this major development within the funding guidelines by using existing engine assets and hardware now in testing to meet a first launch by 2017. It will explain the SLS Program s long-range plan to keep the budget within bounds, yet evolve the 70 metric ton (t) initial lift capability to 130-t lift capability after the first two flights. To achieve the evolved configuration, advanced technologies must offer appropriate return on investment to be selected through a competitive process. For context, the SLS will be larger than the Saturn V that took 12 men on 6 trips for a total of 11 days on the lunar surface over 4 decades ago. Astronauts train for long-duration voyages on the International Space Station, but have not had transportation to go beyond Earth orbit in modern times, until now. NASA is refining its mission manifest, guided by U.S. Space Policy and the Global Exploration Roadmap. Launching the Orion Multi-Purpose Cargo Vehicle s first autonomous certification flight in 2017, followed by a crewed flight in 2021, the SLS will offer a robust way to transport international crews and the air, water, food, and equipment they need for extended trips to asteroids, Lagrange Points, and Mars. In addition, the SLS will accommodate high-priority science experiments. SLS affordability initiatives include streamlining interfaces, applying risk-based insight into contracted work, centralizing systems engineering and integration, and nurturing a learning culture that continually benchmarks its performance against successful ventures. As this paper will explain, the SLS is making measurable progress toward becoming a global infrastructure asset for robotic and human scouts of all nations by harnessing business and technological innovations to deliver sustainable solutions for space exploration.

May, Todd↗
NASA NTRS2012

NASA's Space Launch System: A Flagship for Exploration Beyond Earth's Orbit

The National Aeronautics and Space Administration's (NASA) Space Launch System (SLS) Program, managed at the Marshall Space Flight Center, is making progress toward delivering a new capability for exploration beyond Earth orbit in an austere economic climate. This fact drives the SLS team to find innovative solutions to the challenges of designing, developing, fielding, and operating the largest rocket in history. To arrive at the current SLS plan, government and industry experts carefully analyzed hundreds of architecture options and arrived at the one clear solution to stringent requirements for safety, affordability, and sustainability over the decades that the rocket will be in operation. This paper will explore ways to fit this major development within the funding guidelines by using existing engine assets and hardware now in testing to meet a first launch by 2017. It will explain the SLS Program s long-range plan to keep the budget within bounds, yet evolve the 70 metric ton (t) initial lift capability to 130-t lift capability after the first two flights. To achieve the evolved configuration, advanced technologies must offer appropriate return on investment to be selected through a competitive process. For context, the SLS will be larger than the Saturn V that took 12 men on 6 trips for a total of 11 days on the lunar surface over 4 decades ago. Astronauts train for long-duration voyages on the International Space Station, but have not had transportation to go beyond Earth orbit in modern times, until now. NASA is refining its mission manifest, guided by U.S. Space Policy and the Global Exploration Roadmap. Launching the Orion Multi-Purpose Crew Vehicle s (MPCV s) first autonomous certification flight in 2017, followed by a crewed flight in 2021, the SLS will offer a robust way to transport international crews and the air, water, food, and equipment they need for extended trips to asteroids, Lagrange Points, and Mars. In addition, the SLS will accommodate high-priority science experiments. SLS affordability initiatives include streamlining interfaces, applying risk-based insight into contracted work, centralizing systems engineering and integration, and nurturing a learning culture that continually benchmarks its performance against successful ventures. As this paper will explain, the SLS is making measurable progress toward becoming a global infrastructure asset for robotic and human scouts of all nations by harnessing business and technological innovations to deliver sustainable solutions for space exploration.

May, Todd A.↗
NASA NTRSDate not supplied

Autonomous Spacecraft Attitude Control Using Deep Reinforcement Learning

While machine learning and spacecraft autonomy continue to gain research interest, significant work remains to be done in efficiently applying modern machine learning techniques to problems in space ight. This study presents a framework for deriving a discrete neural spacecraft attitude controller using reinforcement learning, a paradigm of machine learning, without the need for high-performance computing. The developed attitude controller is an approximately time-optimal solution to a highly constrained control problem, able to achieve well above industry-standard pointing accuracies. Control examples are also presented of the agent performing large-angle spacecraft slews in the developed simulation environment and future extensions of this work are discussed.

ATAP↗
NASA NTRS1995

Workshop on Discovery Lessons-Learned

As part of the Discovery Program's continuous improvement effort, a Discovery Program Lessons-Learned workshop was designed to review how well the Discovery Program is moving toward its goal of providing low-cost research opportunities to the planetary science community while ensuring continued U.S. leadership in solar system exploration. The principal focus of the workshop was on the recently completed Announcement of Opportunity (AO) cycle, but the program direction and program management were also open to comment. The objective of the workshop was to identify both the strengths and weaknesses of the process up to this point, with the goal of improving the process for the next AO cycle. The process for initializing the workshop was to solicit comments from the communities involved in the program and to use the feedback as the basis for establishing the workshop agenda. The following four sessions were developed after reviewing and synthesizing both the formal feedback received and informal feedback obtained during discussions with various participants: (1) Science and Return on Investment; (2) Technology vs. Risk; Mission Success and Other Factors; (3) Cost; and (4) AO.AO Process Changes and Program Management.

Saunders, M.↗
NASA NTRS1989

The least constraint principle for learning in neurodynamics

An adaptive neural network for auto-associative memories operating in continuous time is considered. A new learning algorithm for the weight matrix defined by explicit locations of desirable equilibrium points is introduced. The approach is based upon the minimum 'strength energy' of the weight matrix for each prescribed performance of the neural network.

Zak, Michail↗
NASA NTRS2017

Evaluation of Strain Measurement Devices for Inflatable Structures

Inflatable structures provide a significant volume savings for future NASA deep space missions. The complexity of these structures, however, provides difficulty for engineers in designing, analyzing, and testing. Common strain measurement systems for metallic parts cannot be used directly on fabrics. New technologies must be developed and tested to accuractly measure the strain of inflatable structures. This paper documents the testing of six candidate strain measurement devices for use on fabrics. The resistance devices tested showed significant hysteresis during creep and cyclic testing. The capacitive device, however, showed excellent results and little-to-no hysteresis. Because of this issue, only two out of the six proposed devices will continue in development. The resulting data and lessons learned from this effort provides direction for continued work to produce a structural health monitoring system for inflatable habitats.

Litteken, Douglas A.↗
NASA NTRS2017

Evaluation of Strain Measurement Devices for Inflatable Structures

Inflatable structures provide a significant volume savings for future NASA deep space missions. The complexity of these structures, however, provides difficulty for engineers in designing, analyzing, and testing. Common strain measurement systems for metallic parts cannot be used directly on fabrics. New technologies must be developed and tested to accurately measure the strain of inflatable structures. This paper documents the testing of six candidate strain measurement devices for use on fabrics. The resistance devices tested showed significant hysteresis during creep and cyclic testing. The capacitive device, however, showed excellent results and little-to-no hysteresis. Because of this issue, only two out of the six proposed devices will continue in development. The resulting data and lessons learned from this effort provides direction for continued work to produce a structural health monitoring system for inflatable habitats.

Litteken, Doug↗
NASA NTRS2014

Loss of Signal, Aeromedical Lessons Learned from the STS-107 Columbia Space Shuttle Mishap

Loss of Signal, a NASA publication to be available in May 2014 presents the aeromedical lessons learned from the Columbia accident that will enhance crew safety and survival on human space flight missions. These lessons were presented to limited audiences at three separate Aerospace Medical Association (AsMA) conferences: in 2004 in Anchorage, Alaska, on the causes of the accident; in 2005 in Kansas City, Missouri, on the response, recovery, and identification aspects of the investigation; and in 2011, again in Anchorage, Alaska, on future implications for human space flight. As we embark on the development of new spacefaring vehicles through both government and commercial efforts, the NASA Johnson Space Center Human Health and Performance Directorate is continuing to make this information available to a wider audience engaged in the design and development of future space vehicles. Loss of Signal summarizes and consolidates the aeromedical impacts of the Columbia mishap process-the response, recovery, identification, investigative studies, medical and legal forensic analysis, and future preparation that are needed to respond to spacecraft mishaps. The goal of this book is to provide an account of the aeromedical aspects of the Columbia accident and the investigation that followed, and to encourage aerospace medical specialists to continue to capture information, learn from it, and improve procedures and spacecraft designs for the safety of future crews. This poster presents an outline of Loss of Signal contents and highlights from each of five sections - the mission and mishap, the response, the investigation, the analysis and the future.

Stepaniak, Phillip C.↗
NASA NTRS2014

Loss of Signal, Aeromedical Lessons Learned for the STS-I07 Columbia Space Shuttle Mishap

Loss of Signal, a NASA publication to be available in May 2014, presents the aeromedical lessons learned from the Columbia accident that will enhance crew safety and survival on human space flight missions. These lessons were presented to limited audiences at three separate Aerospace Medical Association (AsMA) conferences: in 2004 in Anchorage, Alaska, on the causes of the accident; in 2005 in Kansas City, Missouri, on the response, recovery, and identification aspects of the investigation; and in 2011, again in Anchorage, Alaska, on future implications for human space flight. As we embark on the development of new spacefaring vehicles through both government and commercial efforts, the NASA Johnson Space Center Human Health and Performance Directorate is continuing to make this information available to a wider audience engaged in the design and development of future space vehicles. Loss of Signal summarizes and consolidates the aeromedical impacts of the Columbia mishap process-the response, recovery, identification, investigative studies, medical and legal forensic analysis, and future preparation that are needed to respond to spacecraft mishaps. The goals of this book are to provide an account of the aeromedical aspects of the Columbia accident and the investigation that followed, and to encourage aerospace medical specialists to continue to capture information, learn from it, and improve procedures and spacecraft designs for the safety of future crews.

Patlach, Robert↗
NASA NTRS1986

Learned pattern recognition using synthetic-discriminant-functions

A method of using synthetic-discriminant-functions to facilitate learning in a pattern recognition system is discussed. Learning is accomplished by continually adding images to the training set used for synthetic discriminant functions (SDF) construction. Object identification is performed by efficiently searching a library of SDF filters for the maximum optical correlation. Two library structures are discussed - binary tree and multilinked graph - along with maximum ascent, back-tracking, perturbation, and simulated annealing searching techniques. By incorporating the distortion invariant properties of SDFs within a library structure, a robust pattern recognition system can be produced.

Jared, David A.↗
NASA NTRS1987

Information transfer in pilots' use of a collision avoidance system

A flight simulator study of pilots' use of the Traffic-alert and Collision Avoidance System is described. Three levels of information on the location of other air traffic were presented to different groups of airline pilots. The amount of informtion on the location of other traffic had little effect on pilots' performance of the maneuvers commanded by the collision avoidance system. Measured crew responses were similar with no presentation of traffic location, with limited information, and with continuous traffic information. No learning effects were observed, and differences in flight experience did not contribute to the performance difference found.

Chappell, Sheryl L.↗
NASA NTRS2005

Distributed Adaptive Control: Beyond Single-Instant, Discrete Variables

In extensive form noncooperative game theory, at each instant t, each agent i sets its state x, independently of the other agents, by sampling an associated distribution, q(sub i)(x(sub i)). The coupling between the agents arises in the joint evolution of those distributions. Distributed control problems can be cast the same way. In those problems the system designer sets aspects of the joint evolution of the distributions to try to optimize the goal for the overall system. Now information theory tells us what the separate q(sub i) of the agents are most likely to be if the system were to have a particular expected value of the objective function G(x(sub 1),x(sub 2), ...). So one can view the job of the system designer as speeding an iterative process. Each step of that process starts with a specified value of E(G), and the convergence of the q(sub i) to the most likely set of distributions consistent with that value. After this the target value for E(sub q)(G) is lowered, and then the process repeats. Previous work has elaborated many schemes for implementing this process when the underlying variables x(sub i) all have a finite number of possible values and G does not extend to multiple instants in time. That work also is based on a fixed mapping from agents to control devices, so that the the statistical independence of the agents' moves means independence of the device states. This paper also extends that work to relax all of these restrictions. This extends the applicability of that work to include continuous spaces and Reinforcement Learning. This paper also elaborates how some of that earlier work can be viewed as a first-principles justification of evolution-based search algorithms.

Wolpert, David H.↗
NASA NTRS2008

Building on the Past - Looking to the Future: A Focus on Payload Safety

The history of the space industry stretches far and above lunar landings to the construction of the International Space Station. For years, humans have sought to understand the nature of the universe. As society grows in knowledge and curiosity of space, the focus of maintaining the safety of the crew and vehicle habitability is of utmost importance to the National Aeronautics and Space Administration (NASA) community. Through the years, Payload Safety has developed not only as a Panel, but also as part of the NASA community, striving to enhance the efficiency and understanding of how business should be conducted as more International Partners become involved. This is the first in a series of papers and presentations in what is hoped to be an annual update that provides continuous challenges and lessons learned in the areas of communication, safety requirements and processes and other areas which have been vital to the Payload Safety Review Panel (PSRP).

Nash, Sally K.↗
NASA NTRS2013

Improved CPAS Photogrammetric Capabilities for Engineering Development Unit (EDU) Testing

This paper focuses on two key improvements to the photogrammetric analysis capabilities of the Capsule Parachute Assembly System (CPAS) for the Orion vehicle. The Engineering Development Unit (EDU) system deploys Drogue and Pilot parachutes via mortar, where an important metric is the muzzle velocity. This can be estimated using a high speed camera pointed along the mortar trajectory. The distance to the camera is computed from the apparent size of features of known dimension. This method was validated with a ground test and compares favorably with simulations. The second major photogrammetric product is measuring the geometry of the Main parachute cluster during steady-state descent using onboard cameras. This is challenging as the current test vehicles are suspended by a single-point attachment unlike earlier stable platforms suspended under a confluence fitting. The mathematical modeling of fly-out angles and projected areas has undergone significant revision. As the test program continues, several lessons were learned about optimizing the camera usage, installation, and settings to obtain the highest quality imagery possible.

Ray, Eric S.↗
NASA NTRS2018

Preparing to Assure Mission Success

Space flight missions are inherently risky. The mission operations assurance discipline grew out of strategies to control error and evolved into what today is an independent technical authority dedicated to achieving mission success. After the Mars Climate Orbiter loss, NASA made a set of recommendations for missions. Two of those recommendations led to the creation of today’s Mission Operations Assurance Manager role: (1) require an independent Mission Assurance representative during the operational phase of every flight project, and (2) require all flight projects to report and track post-launch anomalies. Since then, the MOAM role has been continually refined by lessons learned from its practice on more than 20 concurrent missions. The MOAM role requires significant operations experience as well as an additional set of skills. In the interests of developing a cadre of potential MOAMs, the MOAM training program was developed. It is a 14-unit set of presentations/discussions covering the 11 categories of MOAM tasks. It is offered to new MOAMs and interested systems engineers with an eye to preparing both types of personnel for present and future assignments, as well as building relationships among personnel of different organizations. MOAM training sessions include presentations on the various tools and processes employed by MOAMs, interspersed with mindset lessons illustrated via “war story” discussions of previous missions.

Bryant, Larry↗