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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Integrated energy management study. Energy efficient transport program

The Integrated Energy Management (IEM) Study investigated the practicality and feasibility of a closed-loop energy management system for transport aircraft. The study involved: (1) instrumentation and collection of in-flight data for a United Airlines 727-200 flying 80 revenue flights throughout the United Airlines network,(2) analysis of the in-flight data to select representative city pairs and establish operational procedures employed in flying a reference flight profile, (3) simulation of the reference profile in a fast-time model to verify the model and establish performance values against which to measure IEM benefits, (4) development of IEM algorithms, and (5) assessment of the IEM concept.

Source record↗
NASA NTRS1992

Some thoughts on the management of large, complex international space ventures

Management issues relevant to the development and deployment of large international space ventures are discussed with particular attention given to previous experience. Management approaches utilized in the past are labeled as either simple or complex, and signs of efficient management are examined. Simple approaches include those in which experiments and subsystems are developed for integration into spacecraft, and the Apollo-Soyuz Test Project is given as an example of a simple multinational approach. Complex approaches include those for ESA's Spacelab Project and the Space Station Freedom in which functional interfaces cross agency and political boundaries. It is concluded that individual elements of space programs should be managed by individual participating agencies, and overall configuration control is coordinated by level with a program director acting to manage overall objectives and project interfaces.

Lee, T. J.↗
NASA NTRS1991

Parallel processing for scientific computations

The main contribution of the effort in the last two years is the introduction of the MOPPS system. After doing extensive literature search, we introduced the system which is described next. MOPPS employs a new solution to the problem of managing programs which solve scientific and engineering applications on a distributed processing environment. Autonomous computers cooperate efficiently in solving large scientific problems with this solution. MOPPS has the advantage of not assuming the presence of any particular network topology or configuration, computer architecture, or operating system. It imposes little overhead on network and processor resources while efficiently managing programs concurrently. The core of MOPPS is an intelligent program manager that builds a knowledge base of the execution performance of the parallel programs it is managing under various conditions. The manager applies this knowledge to improve the performance of future runs. The program manager learns from experience.

Alkhatib, Hasan S.↗
NASA NTRS1992

Creating a foundation for a synergistic approach to program management

In order to accelerate the movement of humans into space within reasonable budgetary constraints, NASA must develop an organizational structure that will allow the agency to efficiently use all the resources it has available for the development of any program the nation decides to undertake. This work considers the entire set of tasks involved in the successful development of any program. Areas that hold the greatest promise of accelerating programmatic development and/or increasing the efficiency of the use of available resources by being dealt with in a centralized manner rather than being handled by each program individually are identified. Using this information, an agency organizational structure is developed that will allow NASA to promote interprogram synergisms. In order for NASA to efficiently manage its programs in a manner that will allow programs to benefit from one another and thereby accelerate the movement of humans into space, several steps must be taken. First, NASA must develop an organizational structure that will allow potential interprogram synergisms to be identified and promoted. Key features of the organizational structure are recommended in this paper. Second, NASA must begin to develop the requirements for a program in a manner that will promote overall space program goals rather than achieving only the goals that apply to the program for which the requirements are being developed. Finally, NASA must consider organizing the agency around the functions required to support NASA's goals and objectives rather than around geographic locations.

Knoll, Karyn T.↗
NASA NTRS1987

Cryogenic Fluid Management Flight Experiment (CFMFE)

Since its foundation, NASA has excelled in the study and development of microgravity fluid management technology. With the advent of space-based vehicles and systems, the use of and the ability to efficiently manage subcritical cryogens in the space environment has become necessary to our growing space program. The NASA Lewis Research Center is responsible for the planning and execution of a program which will provide advanced in-space cryogenic fluid management technology. A number of future space missions have been identified that will require or could benefit from this technology. These technology needs have been prioritized and the Cryogenic Fluid Management Flight Experiment (CFMFE) is being designed to provide the experimental data necessary for the technological development effort.

Defelice, David M.↗
NASA NTRS2017

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗
NASA NTRS2017

Multi-Objective Reinforcement Learning-based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗
NASA NTRS2013

Flight-Deck Strategies and Outcomes When Flying Schedule-Matching Descents

Recent studies at NASA Ames Research Center have investigated the development and use of ground-based (air traffic controller) tools to manage and schedule air traffic in future terminal airspace. An exploratory study was undertaken to investigate the impacts that such tools (and concepts) could have on the flight-deck. Ten Boeing 747-400 crews flew eight optimized profile descents in the Los Angeles terminal airspace, while receiving scripted current day and futuristic speed clearances, to ascertain their ability to fly schedulematching descents without prior training. Although the study was exploratory in nature, four variables were manipulated: route constraints, winds, speed changes, and clearance phraseology. Despite flying the same scenarios with the same events and timing, there were significant differences in the time it took crews to fly the approaches. This variation is the product of a number of factors but highlights potential difficulties for scheduling tools that would have to accommodate this amount of natural variation in descent times. The focus of this paper is the examination of the crews' aircraft management strategies and outcomes. This includes potentially problematic human-automation interaction issues that may negatively impact arrival times, speed and altitude constraint compliance, and energy management efficiency.

Flight Management System↗
NASA NTRS1995

Descent advisor preliminary field test

A field test of the Descent Advisor (DA) automation tool was conducted at the Denver Air Route Traffic Control Center in September 1994. DA is being developed to assist Center controllers in the efficient management and control of arrival traffic. DA generates advisories, based on trajectory predictions, to achieve accurate meter-fix arrival times in a fuel efficient manner while assisting the controller with the prediction and resolution of potential conflicts. The test objectives were to evaluate the accuracy of DA trajectory predictions for conventional- and flight-management-system-equipped jet transports, to identify significant sources of trajectory prediction error, and to investigate procedural and training issues (both air and ground) associated with DA operations. Various commercial aircraft (97 flights total) and a Boeing 737-100 research aircraft participated in the test. Preliminary results from the primary test set of 24 commercial flights indicate a mean DA arrival time prediction error of 2.4 sec late with a standard deviation of 13.1 sec. This paper describes the field test and presents preliminary results for the commercial flights.

Green, Steven M.↗
NASA NTRS1995

Descent Advisor Preliminary Field Test

A field test of the Descent Advisor (DA) automation tool was conducted at the Denver Air Route Traffic Control Center in September 1994. DA is being developed to assist Center controllers in the efficient management and control of arrival traffic. DA generates advisories, based on trajectory predictions, to achieve accurate meter-fix arrival times in a fuel efficient manner while assisting the controller with the prediction and resolution of potential conflicts. The test objectives were: (1) to evaluate the accuracy of DA trajectory predictions for conventional and flight-management system equipped jet transports, (2) to identify significant sources of trajectory prediction error, and (3) to investigate procedural and training issues (both air and ground) associated with DA operations. Various commercial aircraft (97 flights total) and a Boeing 737-100 research aircraft participated in the test. Preliminary results from the primary test set of 24 commercial flights indicate a mean DA arrival time prediction error of 2.4 seconds late with a standard deviation of 13.1 seconds. This paper describes the field test and presents preliminary results for the commercial flights.

Green, Steven M.↗
NASA NTRS2004

Information Technology Support in the 8000 Directorate

My summer internship was spent supporting various projects within the Environmental Management Office and Glenn Safety Office. Mentored by Eli Abumeri, I was trained in areas of Information Technology such as: Servers, printers, scanners, CAD systems, Web, Programming, and Database Management, ODIN (networking, computers, and phones). I worked closely with the Chemical Sampling and Analysis Team (CSAT) to redesign a database to more efficiently manage and maintain data collected for the Drinking Water Program. This Program has been established for over fifteen years here at the Glenn Research Center. It involves the continued testing and retesting of all drinking water dispensers. The quality of the drinking water is of great importance and is determined by comparing the concentration of contaminants in the water with specifications set forth by the Environmental Protection Agency (EPA) in the Safe Drinking Water Act (SDWA) and its 1986 and 1991 amendments. The Drinking Water Program consists of periodic testing of all drinking water fountains and sinks. Each is tested at least once every 2 years for contaminants and naturally occurring species. The EPA's protocol is to collect an initial and a 5 minute draw from each dispenser. The 5 minute draw is what is used for the maximum contaminant level. However, the CS&AT has added a 30 second draw since most individuals do not run the water 5 minutes prior to drinking. This data is then entered into a relational Microsoft Access database. The database allows for the quick retrieval of any test@) done on any dispenser. The data can be queried by building number, date or test type, and test results are documented in an analytical report for employees to read. To aid with the tracking of recycled materials within the lab, my help was enlisted to create a database that could make this process less cumbersome and more efficient. The date of pickup, type of material, weight received, and unit cost per recyclable. This information could then calculate the dollar amount generated by the recycling of certain materials. This database will ultimately prove useful in determining the amounts of materials consumed by the lab and will help serve as an indicator potential overuse.

FROM↗
NASA NTRS1988

Space station as a vital focus for advancing the technologies of automation and robotics

A major guideline for the design of the U.S. Space Station is that the Space Station address a wide variety of functions. These functions include the servicing of unmanned assets in space, the support of commercial labs in space and the efficient management of the Space Station itself; the largest space asset. The technologies of Automation and Robotics have the promise to help in reducing Space Station operating costs and to achieve a highly efficient use of the human in space. The use of advanced automation and artificial intelligence techniques, such as expert systems, in Space Station subsystems for activity planning and failure mode management will enable us to reduce dependency on a mission control center and could ultimately result in breaking the umbilical link from Earth to the Space Station. The application of robotic technologies with advanced perception capability and hierarchical intelligent control to servicing system will enable the servicing of assets either in space or in situ with a high degree of human efficiency. The results of studies leading toward the formulation of an automation and robotics plan for Space Station development are presented.

Varsi, Giulio↗
NASA NTRS2001

Batching System for Superior Service

Veridian's Portable Batch System (PBS) was the recipient of the 1997 NASA Space Act Award for outstanding software. A batch system is a set of processes for managing queues and jobs. Without a batch system, it is difficult to manage the workload of a computer system. By bundling the enterprise's computing resources, the PBS technology offers users a single coherent interface, resulting in efficient management of the batch services. Users choose which information to package into "containers" for system-wide use. PBS also provides detailed system usage data, a procedure not easily executed without this software. PBS operates on networked, multi-platform UNIX environments. Veridian's new version, PBS Pro,TM has additional features and enhancements, including support for additional operating systems. Veridian distributes the original version of PBS as Open Source software via the PBS website. Customers can register and download the software at no cost. PBS Pro is also available via the web and offers additional features such as increased stability, reliability, and fault tolerance.A company using PBS can expect a significant increase in the effective management of its computing resources. Tangible benefits include increased utilization of costly resources and enhanced understanding of computational requirements and user needs.

Source record↗
NASA NTRS2008

Using Hyperspectral Imagery to Identify Turfgrass Stresses

The use of a form of remote sensing to aid in the management of large turfgrass fields (e.g. golf courses) has been proposed. A turfgrass field of interest would be surveyed in sunlight by use of an airborne hyperspectral imaging system, then the raw observational data would be preprocessed into hyperspectral reflectance image data. These data would be further processed to identify turfgrass stresses, to determine the spatial distributions of those stresses, and to generate maps showing the spatial distributions. Until now, chemicals and water have often been applied, variously, (1) indiscriminately to an entire turfgrass field without regard to localization of specific stresses or (2) to visible and possibly localized signs of stress for example, browning, damage from traffic, or conspicuous growth of weeds. Indiscriminate application is uneconomical and environmentally unsound; the amounts of water and chemicals consumed could be insufficient in some areas and excessive in most areas, and excess chemicals can leak into the environment. In cases in which developing stresses do not show visible signs at first, it could be more economical and effective to take corrective action before visible signs appear. By enabling early identification of specific stresses and their locations, the proposed method would provide guidance for planning more effective, more economical, and more environmentally sound turfgrass-management practices, including application of chemicals and water, aeration, and mowing. The underlying concept of using hyperspectral imagery to generate stress maps as guides to efficient management of vegetation in large fields is not new; it has been applied in the growth of crops to be harvested. What is new here is the effort to develop an algorithm that processes hyperspectral reflectance data into spectral indices specific to stresses in turfgrass. The development effort has included a study in which small turfgrass plots that were, variously, healthy or subjected to a variety of controlled stresses were observed by use of a hand-held spectroradiometer. The spectroradiometer readings in the wavelength range from 350 to 1,000 nm were processed to extract hyperspectral reflectance data, which, in turn, were analyzed to find correlations with the controlled stresses. Several indices were found to be correlated with drought stress and to be potentially useful for identifying drought stress before visible symptoms appear.

Hutto, Kendall↗
NASA NTRS1991

Method for providing real-time control of a gaseous propellant rocket propulsion system

The new and improved methods and apparatus disclosed provide effective real-time management of a spacecraft rocket engine powered by gaseous propellants. Real-time measurements representative of the engine performance are compared with predetermined standards to selectively control the supply of propellants to the engine for optimizing its performance as well as efficiently managing the consumption of propellants. A priority system is provided for achieving effective real-time management of the propulsion system by first regulating the propellants to keep the engine operating at an efficient level and thereafter regulating the consumption ratio of the propellants. A lower priority level is provided to balance the consumption of the propellants so significant quantities of unexpended propellants will not be left over at the end of the scheduled mission of the engine.

Morris, Brian G.↗
NASA NTRS2019

Health Management and Prognostics for Electric Aircraft Powertrain

W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.

Kulkarni, Chetan↗
NASA NTRS1995

A visiting scientist program for the burst and transient source experiment

During this project, Universities Space Research Association provided program management and the administration for overseeing the performance of the total contractual effort. The program director and administrative staff provided the expertise and experience needed to efficiently manage the program.USRA provided a program coordinator and v visiting scientists to perform scientific research with Burst and Transient Source Experiment (BATSE) data. This research was associated with the primary scientific objectives of BATSE and with the various BATSE collaborations which were formed in response to the Compton Gamma Ray Observatory Guest Investigator Program. USRA provided administration for workshops, colloquia, the preparation of scientific documentation, etc. and also provided flexible program support in order to meet the on-going needs of MSFC's BATSE program. USRA performed tasks associated with the recovery, archiving, and processing of scientific data from BATSE. A bibliography of research in the astrophysics discipline is attached as Appendix 1. Visiting Scientists and Research Associates performed activities on this project, and their technical reports are attached as Appendix 2.

Kerr, Frank J.↗
NASA NTRS1985

Cryogenic Fluid Management Facility

The Cryogenic Fluid Management Facility is a reusable test bed which is designed to be carried within the Shuttle cargo bay to investigate the systems and technologies associated with the efficient management of cryogens in space. Cryogenic fluid management consists of the systems and technologies for: (1) liquid storage and supply, including capillary acquisition/expulsion systems which provide single-phase liquid to the user system, (2) both passive and active thermal control systems, and (3) fluid transfer/resupply systems, including transfer lines and receiver tanks. The facility contains a storage and supply tank, a transfer line and a receiver tank, configured to provide low-g verification of fluid and thermal models of cryogenic storage and transfer processes. The facility will provide design data and criteria for future subcritical cryogenic storage and transfer system applications, such as Space Station life support, attitude control, power and fuel depot supply, resupply tankers, external tank (ET) propellant scavenging, and ground-based and space-based orbit transfer vehicles (OTV).

Eberhardt, R. N.↗