Search NASA⌕ Search

SEARCH · Search NASA

Results for “resource guide”

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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Evolution and Impact of Saturn V on Space Launch System from a Guidance, Navigation, and Mission Analysis Perspective

The Saturn V launch vehicle represented a jump in capability for heavy lift launch vehicles, enabling the Lunar Orbit Rendezvous approach to planetary exploration employed by the Apollo program 50 years ago. Following Apollo, and the development of the Space Transportation System, the NASA space exploration program shifted focus from lunar exploration to long-term, sustained, re-usable access to Low Earth Orbit. With the recent focus of NASA on the Artemis program and continued exploration of cislunar space as a precursor to Martian exploration, the shift has swung back to heavy lift capability. To meet this need, NASA has developed the Space Launch System. While the vehicle is a new design, it is heavily influenced by the engineering solutions and approach used on the Saturn V while taking advantage of the state of the art of launch vehicle design. The approach to abort, for example, shares many familiarities with the triggers and concept of operations used on Saturn V. Analysis approaches to dispersed trajectory performance are also very similar, but advances in computing technology have enabled a much more expanded set of inputs that can be modelled and assessed in a rapid manner. Additionally, guided flight algorithms share similar first principles but have expanded to include day of launch wind information. Trajectory optimization has also advanced significantly due to the availability of computing resources, but similar maneuvers and profiles are flown across both vehicles. Also, while the approach of onboard inertial navigation has been maintained between the two programs, the shift from platform to strapdown systems enables reduced complexity in the system design while maintaining required performance. As described, the Space Launch System is the evolution of NASA launch vehicle designs, owing a large heritage to the Saturn vehicle program and incorporating advances in propulsion systems, avionics, computing, and sensor technology over the past 50 years.

Ahmad, Naeem↗
NASA NTRS1999

Globus Quick Start Guide. Globus Software Version 1.1

The Globus Project is a community effort, led by Argonne National Laboratory and the University of Southern California's Information Sciences Institute. Globus is developing the basic software infrastructure for computations that integrate geographically distributed computational and information resources.

Source record↗
NASA NTRS2014

RECOVER: An Automated Cloud-Based Decision Support System for Post-fire Rehabilitation Planning

RECOVER is a site-specific decision support system that automatically brings together in a single analysis environment the information necessary for post-fire rehabilitation decision-making. After a major wildfire, law requires that the federal land management agencies certify a comprehensive plan for public safety, burned area stabilization, resource protection, and site recovery. These burned area emergency response (BAER) plans are a crucial part of our national response to wildfire disasters and depend heavily on data acquired from a variety of sources. Final plans are due within 21 days of control of a major wildfire and become the guiding document for managing the activities and budgets for all subsequent remediation efforts. There are few instances in the federal government where plans of such wide-ranging scope and importance are assembled on such short notice and translated into action more quickly. RECOVER has been designed in close collaboration with our agency partners and directly addresses their high-priority decision-making requirements. In response to a fire detection event, RECOVER uses the rapid resource allocation capabilities of cloud computing to automatically collect Earth observational data, derived decision products, and historic biophysical data so that when the fire is contained, BAER teams will have a complete and ready-to-use RECOVER dataset and GIS analysis environment customized for the target wildfire. Initial studies suggest that RECOVER can transform this information-intensive process by reducing from days to a matter of minutes the time required to assemble and deliver crucial wildfire-related data.

cloud computing↗
NASA NTRS1987

The 1987 RIACS annual report

The Research Institute for Advanced Computer Science (RIACS) was established at the NASA Ames Research Center in June of 1983. RIACS is privately operated by the Universities Space Research Association (USRA), a consortium of 64 universities with graduate programs in the aerospace sciences, under several Cooperative Agreements with NASA. RIACS's goal is to provide preeminent leadership in basic and applied computer science research as partners in support of NASA's goals and missions. In pursuit of this goal, RIACS contributes to several of the grand challenges in science and engineering facing NASA: flying an airplane inside a computer; determining the chemical properties of materials under hostile conditions in the atmospheres of earth and the planets; sending intelligent machines on unmanned space missions; creating a one-world network that makes all scientific resources, including those in space, accessible to all the world's scientists; providing intelligent computational support to all stages of the process of scientific investigation from problem formulation to results dissemination; and developing accurate global models for climatic behavior throughout the world. In working with these challenges, we seek novel architectures, and novel ways to use them, that exploit the potential of parallel and distributed computation and make possible new functions that are beyond the current reach of computing machines. The investigation includes pattern computers as well as the more familiar numeric and symbolic computers, and it includes networked systems of resources distributed around the world. We believe that successful computer science research is interdisciplinary: it is driven by (and drives) important problems in other disciplines. We believe that research should be guided by a clear long-term vision with planned milestones. And we believe that our environment must foster and exploit innovation. Our activities and accomplishments for the calendar year 1987 and our plans for 1988 are reported.

Source record↗
NASA NTRS1991

Priority scheme planning for the robust SSM/PMAD testbed

Whenever mixing priorities of manually controlled resources with those of autonomously controlled resources, the space station module power management and distribution (SSM/PMAD) environment requires cooperating expert system interaction between the planning function and the priority manager. The elements and interactions of the SSM/PMAD planning and priority management functions are presented. Their adherence to cooperating for common achievement are described. In the SSM/PMAD testbed these actions are guided by having a system planning function, KANT, which has insight to the executing system and its automated database. First, the user must be given access to all information which may have an effect on the desired outcome. Second, the fault manager element, FRAMES, must be informed as to the change so that correct diagnoses and operations take place if and when faults occur. Third, some element must engage as mediator for selection of resources and actions to be added or removed at the user's request. This is performed by the priority manager, LPLMS. Lastly, the scheduling mechanism, MAESTRO, must provide future schedules adhering to the user modified resource base.

Elges, Michael R.↗
NASA NTRS2004

Learning to Control Advanced Life Support Systems

Advanced life support systems have many interacting processes and limited resources. Controlling and optimizing advanced life support systems presents unique challenges. In particular, advanced life support systems are nonlinear coupled dynamical systems and it is difficult for humans to take all interactions into account to design an effective control strategy. In this project. we developed several reinforcement learning controllers that actively explore the space of possible control strategies, guided by rewards from a user specified long term objective function. We evaluated these controllers using a discrete event simulation of an advanced life support system. This simulation, called BioSim, designed by Nasa scientists David Kortenkamp and Scott Bell has multiple, interacting life support modules including crew, food production, air revitalization, water recovery, solid waste incineration and power. They are implemented in a consumer/producer relationship in which certain modules produce resources that are consumed by other modules. Stores hold resources between modules. Control of this simulation is via adjusting flows of resources between modules and into/out of stores. We developed adaptive algorithms that control the flow of resources in BioSim. Our learning algorithms discovered several ingenious strategies for maximizing mission length by controlling the air and water recycling systems as well as crop planting schedules. By exploiting non-linearities in the overall system dynamics, the learned controllers easily out- performed controllers written by human experts. In sum, we accomplished three goals. We (1) developed foundations for learning models of coupled dynamical systems by active exploration of the state space, (2) developed and tested algorithms that learn to efficiently control air and water recycling processes as well as crop scheduling in Biosim, and (3) developed an understanding of the role machine learning in designing control systems for advanced life support.

Subramanian, Devika↗
NASA NTRS2003

Educator Resource Center for NASA Langley Research Center

The goal of the ERCN is to provide expertise and facilities to help educators access and utilize science, mathematics, and technology instructional products aligned with national standards and appropriate state frameworks and based on NASA s unique mission and results. The NASA Langley s Office of Education has established the service area for this ERC to be the five states of Kentucky, North Carolina, South Carolina, Virginia and West Virginia. This educational grant activity is associated with NASA s Mission to inspire the next generation of explorers.. .as only NASA can. The communication of NASA s knowledge is the prime role of this ERC. Functioning as a dissemination system of instructional materials and support for pre-college education programs we have met the NASA Education ERCN Program's goal. The following ERCN objectives have been accomplished: Demonstrate and facilitate the use of NASA educational products and technologies in print, video and web based formats. Examples include but are not limited to NASA approved Educator s Guides with Activities based on national standards for appropriate subjects and grade levels. We have demonstrated the use videotape series in analogue format and the new digital video instructional systems along with the use of NASA TV. The promotion of web page based resources such as the new NASA Portal web and the ability to download print resources is continuously facilitated in workshops. This objective has been completed by educator contacts that include on-site visits, phone requests, postal mail requests, e-mail requests, fax requests and workshops offered.

Bridgford, Todd↗
NASA NTRS1985

Guidebook for analysis of tether applications

This guidebook is intended as a tool to facilitate initial analyses of proposed tether applications in space. The guiding philosophy is that a brief analysis of all the common problem areas is far more useful than a detailed study in any one area. Such analyses can minimize the waste of resources on elegant but fatally flawed concepts, and can identify the areas where more effort is needed on concepts which do survive the initial analyses. The simplified formulas, approximations, and analytical tools included should be used only for preliminary analyses. For detailed analyses, the references with each topic and in the bibliography may be useful.

Carroll, J. A.↗
NASA NTRS2019

Complex Dynamics of Air Traffic Flow

Air traffic in the United States has continued to grow at a steady pace since 1980, except for a dip immediately after the tragic events of September 11, 2001. There are different growth scenarios associated both with the magnitude and the composition of the future air traffic. The Terminal Area Forecast (TAF), prepared every year by the FAA, projects the growth of traffic in the United States. Both Boeing and Airbus publish market outlooks for air travel annually. Although predicting the future growth of traffic is difficult, there are two significant trends: heavily congested major airports continue to see an increase in traffic, and the emergence of regional jets and other smaller aircraft with fewer passengers operating directly between non-major airports. The interaction between air traffic demand and the ability of the system to provide the necessary airport and airspace resources can be modeled as a network. The size of the resulting network varies depending on the choice of its nodes. It would be useful to understand the properties of this network to guide future design and development. Many questions, such as the growth of delay with increasing traffic demand and impact of the en route weather on future air traffic, require a systematic understanding of the properties of the air traffic network. There has been a major advance in the understanding of the behavior of networks with a large number of components. Several theories have been advanced about the evolution of large biological and engineering networks by authors in diversified disciplines like physics, mathematics, biology and computer science. Several networks exhibit a scale-free property in the sense that the probabilistic distribution of their nodes as a function of connections decreases slower than an exponential. These networks are characterized by the fact that a small number of components have a disproportionate influence on the performance of the network. Scale-free networks are tolerant to random failure of components, but are vulnerable to selective attack on components. This paper examines two network representations for the baseline air traffic system. A network defined with the 40 major airports as nodes and with standard flight routes as links has a characteristic scale: all nodes have 60 or more links and no node has more than 460 links. Another network is defined with baseline aircraft routing structure exhibits an exponentially truncated scale-free behavior. Its degree ranges from 2 connections to 2900 connections, and 225 nodes have more than 250 connections. Furthermore, those high-degree nodes are homogeneously distributed in the airspace. A consequence of this scale-free behavior is that the random loss of a single node has little impact, but the loss of multiple high-degree nodes (such as occurs during major storms in busy airspace) can adversely impact the system. Two future scenarios of air traffic growth are used to predict the growth of air traffic in the United States. It is shown that a three-times growth in the overall traffic may result in a ten-times impact on the density of traffic in certain parts of the United States.

Scale-free Networks↗
NASA NTRS2023

Adaptive Mission Assurance (AMA) – A Conceptual Guide for NASA Missions

NASA is well acquainted with and skilled in conducting Risk Class A Safety and Mission Assurance (SMA). Class A missions are characterized as having highly specific performance with an ultra-low risk tolerance for risk and mission failure. But space is rapidly changing, and the space enterprise is challenged to pursue faster more agile mission developments with fewer resources and directed schedules. To meet this demand mission development teams face accepting more risk and trading performance within strict cost and schedule constraints. In responding to this challenge, The Aerospace Corporation has evolved the Adaptive Mission Assurance (AMA) approach. The benefit of an “adaptive” approach is most realized for smaller Research and Development (R&D), or Science and Technology (S&T) demonstration missions constrained by significantly smaller budgets and directed schedules. The challenge for these “risk tolerant, constraints-driven” missions is how to identify the most valuable mission assurance tasks that will fit within strict budgetary and schedule constraints for “gracefully” accepting risk that still achieves an agreeable expectation of mission success. AMA can respond to this challenge with little to no impact to team staffing or existing workload. This conceptual guide introduces AMA as a potential implementation for NASA Risk Class D and Sub-Class D missions.

Douglas A. Harris↗
NASA NTRS1994

Scheduling: A guide for program managers

The following topics are discussed concerning scheduling: (1) milestone scheduling; (2) network scheduling; (3) program evaluation and review technique; (4) critical path method; (5) developing a network; (6) converting an ugly duckling to a swan; (7) network scheduling problem; (8) (9) network scheduling when resources are limited; (10) multi-program considerations; (11) influence on program performance; (12) line-of-balance technique; (13) time management; (14) recapitulization; and (15) analysis.

Source record↗
NASA NTRS2020

A Systematic Review of Local to Regional Yield Forecasting Approaches and Frequently Used Data Resources

Forecasting crop yields, or providing an expectation of ex-ante harvest amounts, is highly relevant to the whole agricultural production chain. Farmers can adapt their management, traders or insurers their pricing schemes, suppliers their stocks, logistic companies their routes, national authorities their food balance sheets to guide import or export and, finally, international aid organizations can mobilize reliefs. Evidence has grown in the literature that such forecasts with a meaningful lead time are possible on various geographic scales and for a broad range of crops. Here, we present a systematic review of the methods applied in end-of-season yield forecasting and three frequently used data sources: weather data, satellite data and crop masks. Our literature database comprises 362 studies (2004–2019) which were evaluated regarding methods, crops, regions, data sources, lead time and performance. Moreover, we present 24 sources of real-time and predictive weather data, 21 sources of remote sensing data and 16 crop masks. Yield forecasting in our literature sample has been performed for 44 crops in 71 countries, also including many non-staple crops, but with an apparent bias in regions and crops. Forecasting performance depends on various factors, including crop, region, method, lead time to harvest and input diversity. Our systematic review supports a broader application of locally successful approaches at larger scales by providing a comprehensive, accessible compendium of necessary information for yield forecasting. We discuss improvement potentials with respect to methodological approaches and available data sources. We additionally suggest standardization procedures for future forecasting studies and encourage studying additional crops and geographic regions. Implications of forecasts for different target groups on different scales and the adaptation towards climate change are also discussed.

Seasonal crop yield forecasting↗
NASA NTRS1988

Integrated resource scheduling in a distributed scheduling environment

The Space Station era presents a highly-complex multi-mission planning and scheduling environment exercised over a highly distributed system. In order to automate the scheduling process, customers require a mechanism for communicating their scheduling requirements to NASA. A request language that a remotely-located customer can use to specify his scheduling requirements to a NASA scheduler, thus automating the customer-scheduler interface, is described. This notation, Flexible Envelope-Request Notation (FERN), allows the user to completely specify his scheduling requirements such as resource usage, temporal constraints, and scheduling preferences and options. The FERN also contains mechanisms for representing schedule and resource availability information, which are used in the inter-scheduler inconsistency resolution process. Additionally, a scheduler is described that can accept these requests, process them, generate schedules, and return schedule and resource availability information to the requester. The Request-Oriented Scheduling Engine (ROSE) was designed to function either as an independent scheduler or as a scheduling element in a network of schedulers. When used in a network of schedulers, each ROSE communicates schedule and resource usage information to other schedulers via the FERN notation, enabling inconsistencies to be resolved between schedulers. Individual ROSE schedules are created by viewing the problem as a constraint satisfaction problem with a heuristically guided search strategy.

Zoch, David↗
NASA NTRS1997

Developing a Graphical User Interface for the ALSS Crop Planning Tool

The goal of my project was to create a graphical user interface for a prototype crop scheduler. The crop scheduler was developed by Dr. Jorge Leon and Laura Whitaker for the ALSS (Advanced Life Support System) program. The addition of a system-independent graphical user interface to the crop planning tool will make the application more accessible to a wider range of users and enhance its value as an analysis, design, and planning tool. My presentation will demonstrate the form and functionality of this interface. This graphical user interface allows users to edit system parameters stored in the file system. Data on the interaction of the crew, crops, and waste processing system with the available system resources is organized and labeled. Program output, which is stored in the file system, is also presented to the user in performance-time plots and organized charts. The menu system is designed to guide the user through analysis and decision making tasks, providing some help if necessary. The Java programming language was used to develop this interface in hopes of providing portability and remote operation.

Koehlert, Erik↗
NASA NTRSDate not supplied

Anisotropic Goal-Based Mesh Adaptation Metric Clarification and Development

Adaptive unstructured mesh techniques have a limited, but growing impact on production analysis workflows to control discretization error for reliable simulation results. Multiple independent implementations of flow solvers, anisotropic metric construction methods, and anisotropic mesh adaptation mechanics have matured. Goal-based metrics target estimated error in output functions, such as lift and drag, through the guidance of an adjoint solution. A unification of goal-based anisotropic metrics is presented for steady viscous flows, which is an active area of research. These goal-based metrics drive robust and efficient anisotropic mesh adaptation for the calculation of output functions. The super-convergent functional output error behavior of stabilized finite-element methods is exploited without a formal proof, and evidence of super-convergence is shown in numerical experiments. Mesh adapted drag and lift outputs for two simple bodies in compressible viscous flow show convergence of error to less than a single drag count. Asymptotic behavior established for relatively coarse meshes shows the efficiency of this goal-based metric when compared to solution interpolation error control and expert-guided meshing. Anisotropic mesh adaptation techniques are applied to a transport aircraft in a high-lift configuration where variation between approaches decreases with mesh refinement, but asymptotic behavior is not observed with available resources.

goal-based↗
NASA NTRS1994

Integration for navigation on the UMASS mobile perception lab

Integration of real-time visual procedures for use on the Mobile Perception Lab (MPL) was presented. The MPL is an autonomous vehicle designed for testing visually guided behavior. Two critical areas of focus in the system design were data storage/exchange and process control. The Intermediate Symbolic Representation (ISR3) supported data storage and exchange, and the MPL script monitor provided process control. Resource allocation, inter-process communication, and real-time control are difficult problems which must be solved in order to construct strong autonomous systems.

Draper, Bruce↗
NASA NTRSDate not supplied

Moon to Mars In Situ Resource Utilization (ISRU) Status Update

In 2017, NASA initiated the Artemis program to send astronauts back to the lunar surface, create a sustainable human lunar exploration program, and lead the first human exploration mission to the Mars surface. While much of NASA’s plans for the Artemis program currently focus on the Human Lunar Return and the ability for astronauts to explore the lunar surface for limited durations each year, the longer-term vision for the Artemis program is to enable sustained human exploration and commercial operations in cis-lunar space and the lunar surface. An important aspect of achieving this long-term vision, is to better understand and characterize the resources on the Moon and Mars and learn how to extract and use these resources. Known as In Situ Resource Utilization (ISRU), the identification, mapping, extraction, and processing of space resources has the potential to greatly reduce the cost and risk of human exploration. These are achieved by reducing what needs to be delivered from Earth and the dependency on these supplies, lowering costs through commercial operations, and expanding infrastructure for safer and more capable exploration and surface operations. To guide development of ISRU technologies and systems on the ground and demonstrate these capabilities on the Moon and Mars, the NASA Space Technology Mission Directorate (STMD) created and released the ISRU Envisioned Future Priorities (EFP) strategic plan in 2022 and updated it in 2023. While lunar ISRU technology development had already started, these publicly released strategic plans have been used to guide and prioritize technology development, and assess the progress in achieving the vision. Since the release of the ISRU EFP, there have been several significant activities/events that have occurred with respect to human lunar exploration, surface infrastructure, and ISRU. This presentation will provide an overview and status of on-going technology and system development activities, an update of ISRU into the Artemis campaign, an update on ISRU-related activities.

NASA↗
NASA NTRS2022

Planting a Flag in the Tropics: The Essential Tropical Geometric Background for Networking Applications

This Technical Memorandum serves to guide future NASA researchers and the public at large in terms of how Tropical Geometry can be applied to optimization problems, namely in networking. We give a basic overview of Tropical Geometry through a collection of resources we have summarized. Lastly, we include a discussion of power diagrams viewed as stratified spaces which may be a useful tool to study tropical varieties.

Tropical Geometry↗