Search NASA⌕ Search

SEARCH · Search NASA

Results for “Computer Science - Operating Systems”

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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

SIM_EXPLORE: Software for Directed Exploration of Complex Systems

Physics-based numerical simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. While such codes may provide the highest- fidelity representation of system behavior, they are often so slow to run that insight into the system is limited. Trying to understand the effects of inputs on outputs by conducting an exhaustive grid-based sweep over the input parameter space is simply too time-consuming. An alternative approach called "directed exploration" has been developed to harvest information from numerical simulators more efficiently. The basic idea is to employ active learning and supervised machine learning to choose cleverly at each step which simulation trials to run next based on the results of previous trials. SIM_EXPLORE is a new computer program that uses directed exploration to explore efficiently complex systems represented by numerical simulations. The software sequentially identifies and runs simulation trials that it believes will be most informative given the results of previous trials. The results of new trials are incorporated into the software's model of the system behavior. The updated model is then used to pick the next round of new trials. This process, implemented as a closed-loop system wrapped around existing simulation code, provides a means to improve the speed and efficiency with which a set of simulations can yield scientifically useful results. The software focuses on the case in which the feedback from the simulation trials is binary-valued, i.e., the learner is only informed of the success or failure of the simulation trial to produce a desired output. The software offers a number of choices for the supervised learning algorithm (the method used to model the system behavior given the results so far) and a number of choices for the active learning strategy (the method used to choose which new simulation trials to run given the current behavior model). The software also makes use of the LEGION distributed computing framework to leverage the power of a set of compute nodes. The approach has been demonstrated on a planetary science application in which numerical simulations are used to study the formation of asteroid families.

Burl, Michael↗
NASA NTRS2006

Aerocapture Technologies

Aeroassist technology development is a vital part of the NASA In-Space Propulsion Technology (ISPT) Program. One of the main focus areas of ISPT is aeroassist technologies through the Aerocapture Technology (AT) Activity. Within the ISPT, the current aeroassist technology development focus is aerocapture. Aerocapture relies on the exchange of momentum with an atmosphere to achieve thrust, in this case a decelerating thrust leading to orbit capture. Without aerocapture, a substantial propulsion system would be needed on the spacecraft to perform the same reduction of velocity. This could cause reductions in the science payload delivered to the destination, increases in the size of the launch vehicle (to carry the additional fuel required for planetary capture) or could simply make the mission impossible due to additional propulsion requirements. The AT is advancing each technology needed for the successful implementation of aerocapture in future missions. The technology development focuses on both rigid aeroshell systems as well as the development of inflatable aerocapture systems, advanced aeroshell performance sensors, lightweight structure and higher temperature adhesives. Inflatable systems such as tethered trailing ballutes ('balloon parachutes'), clamped ballutes, and inflatable aeroshells are also under development. Aerocapture-specific computational tools required to support future aerocapture missions are also an integral part of the ATP. Tools include: engineering reference atmosphere models, guidance and navigation, aerothermodynamic modeling, radiation modeling and flight simulation. Systems analysis plays a key role in the AT development process. The NASA in-house aerocapture systems analysis team has been taken with multiple systems definition and concept studies to complement the technology development tasks. The team derives science requirements, develops guidance and navigation algorithms, as well as engineering reference atmosphere models and aeroheating specifications. The study team also creates designs for the overall mission spacecraft. Presentation slides are provided to further describe the aerocapture project.

Keys, Andrew S.↗
NASA NTRS1985

Research in computer science

Synopses are given for NASA supported work in computer science at the University of Virginia. Some areas of research include: error seeding as a testing method; knowledge representation for engineering design; analysis of faults in a multi-version software experiment; implementation of a parallel programming environment; two computer graphics systems for visualization of pressure distribution and convective density particles; task decomposition for multiple robot arms; vectorized incomplete conjugate gradient; and iterative methods for solving linear equations on the Flex/32.

Ortega, J. M.↗
NASA NTRSDate not supplied

Model Assisted Probability of Detection for NASA Space Missions

Model assisted probability of detection (MAPOD) uses data from simulations to improve a traditional probability of detection (POD) study. This could include extending the parameter space to reduce uncertainty or substituting experimental data with simulated data to reduce the time and cost of a POD study. In the past MAPOD was difficult due to limited computational resources, but recent innovations in simulation tools and high-performance computing have made this type of high-degree-of-freedom modeling possible, and complex structures have made it necessary. This presentation will summarize the work done by the computational nondestructive evaluation (CNDE) specialists within the Nondestructive Evaluation Sciences branch at NASA Langley Research Center (LaRC) to complete a MAPOD study for phased array ultrasound testing (PAUT) of a friction stir welding (FSW) method to be used on Space Launch System (SLS) structures. The three critical needs for a MAPOD study are a validated and verified model of the inspection technique for the structure being inspected, some experimental POD data, and an uncertainty model for both the model and the experimental data. PAUT was simulated using Extende CIVA’s UT module. The model was validated using laboratory inspection data from NASA Marshall Space Flight Center (MSFC) for a Hit/Miss POD for FSW in 2219-T87 aluminum panels representative of those used in the SLS. This model was then used to simulate flaw sizes that were originally omitted from the original POD study. The results of this new MAPOD study will be presented along with a discussion of the methods and processes used to analyze the original data, selected simulation parameters, and development of the uncertainty model used for the statistical analysis. The goal of this effort is not just to improve the POD study but to demonstrate the value of MAPOD and provide a roadmap for application of MAPOD on future projects.

Elizabeth Gregory↗
NASA NTRS1999

Human Exploration Ethnography of the Haughton-Mars Project, 1998-1999

During the past two field seasons, July 1988 and 1999, we have conducted research about the field practices of scientists and engineers at Haughton Crater on Devon Island in the Canadian Arctic, with the objective of determining how people will live and work on Mars. This broad investigation of field life and work practice, part of the Haughton-Mars Project lead by Pascal Lee, spans social and cognitive anthropology, psychology, and computer science. Our approach involves systematic observation and description of activities, places, and concepts, constituting an ethnography of field science at Haughton. Our focus is on human behaviors-what people do, where, when, with whom, and why. By locating behavior in time and place-in contrast with a purely functional or "task oriented" description of work-we find patterns constituting the choreography of interaction between people, their habitat, and their tools. As such, we view the exploration process in terms of a total system comprising a social organization, facilities, terrain/climate, personal identities, artifacts, and computer tools. Because we are computer scientists seeking to develop new kinds of tools for living and working on Mars, we focus on the existing representational tools (such as documents and measuring devices), learning and improvization (such as use of the internet or informal assistance), and prototype computational systems brought to the field. Our research is based on partnership, by which field scientists and engineers actively contribute to our findings, just as we participate in their work and life.

Clancey, William J.↗
NASA NTRS2006

Simulated convective systems using a cloud resolving model: Impact of large-scale temperature and moisture forcing using observations and GEOS-3 reanalysis

The GCE (Goddard Cumulus Ensemble) model, which has been developed and improved at NASA Goddard Space Flight Center over the past two decades, is considered as one of the finer and state-of-the-art CRMs (Cloud Resolving Models) in the research community. As the chosen CRM for a NASA Interdisciplinary Science (IDS) Project, GCE has recently been successfully upgraded into an MPI (Message Passing Interface) version with which great improvement has been achieved in computational efficiency, scalability, and portability. By basically using the large-scale temperature and moisture advective forcing, as well as the temperature, water vapor and wind fields obtained from TRMM (Tropical Rainfall Measuring Mission) field experiments such as SCSMEX (South China Sea Monsoon Experiment) and KWAJEX (Kwajalein Experiment), our recent 2-D and 3-D GCE simulations were able to capture detailed convective systems typical of the targeted (simulated) regions. The GEOS-3 [Goddard EOS (Earth Observing System) Version-3] reanalysis data have also been proposed and successfully implemented for usage in the proposed/performed GCE long-term simulations (i.e., aiming at producing massive simulated cloud data -- Cloud Library) in compensating the scarcity of real field experimental data in both time and space (location). Preliminary 2-D or 3-D pilot results using GEOS-3 data have generally showed good qualitative agreement (yet some quantitative difference) with the respective numerical results using the SCSMEX observations. The first objective of this paper is to ensure the GEOS-3 data quality by comparing the model results obtained from several pairs of simulations using the real observations and GEOS-3 reanalysis data. The different large-scale advective forcing obtained from these two kinds of resources (i.e., sounding observations and GEOS-3 reanalysis) has been considered as a major critical factor in producing various model results. The second objective of this paper is therefore to investigate and present such an impact of large-scale forcing on various modeled quantities (such as hydrometeors, rainfall, and etc.). A third objective is to validate the overall GCE 3-D model performance by comparing the numerical results with sounding observations, as well as available satellite retrievals.

Shie, C.-L.↗
NASA NTRS1994

Intelligent Computational Systems. Opening Remarks: CFD Application Process Workshop

This discussion will include a short review of the challenges that must be overcome if computational physics technology is to have a larger impact on the design cycles of U.S. aerospace companies. Some of the potential solutions to these challenges may come from the information sciences fields. A few examples of potential computational physics/information sciences synergy will be presented, as motivation and inspiration for the Improving The CFD Applications Process Workshop.

VanDalsem, William R.↗
NASA NTRS1996

Implementation of a Very Large Atmospheric Correction Lookup Table for ASTER Using a Relational Database Management System

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)is designed to provide a high resolution map of the Earth in both visible, near-infrared, and thermal spectral regions of the electromagnetic spectrum. The ASTER Science Team has developed several standard data product algorithms, but the most complex aod computing-intensive of these is the estimation of surface radiance and reflectance values, which is done by modeling and correcting for the effects of the atmosphere. The algorithm for atmospheric correction in the visible bands sensed by ASTER calls for use of a very large Atmospheric Correction Look Up Table (ACLUT).

ASTER↗
NASA NTRS2015

Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

The use of cloud computing resources continues to grow within the public and private sector components of the weather enterprise as users become more familiar with cloud‐computing concepts, and competition among service providers continues to reduce costs and other barriers to entry. Cloud resources can also provide capabilities similar to high‐performance computing environments, supporting multi‐node systems required for near real‐time, regional weather predictions. Referred to as "Infrastructure as a Service", or IaaS, the use of cloud-based computing hardware in an on‐demand payment system allows for rapid deployment of a modeling system in environments lacking access to a large, supercomputing infrastructure. Use of IaaS capabilities to support regional weather prediction may be of particular interest to developing countries that have not yet established large supercomputing resources, but would otherwise benefit from a regional weather forecasting capability. Recently, collaborators from NASA Marshall Space Flight Center and Ames Research Center have developed a scripted, on‐demand capability for launching the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS), which includes pre‐compiled binaries of the latest version of the Weather Research and Forecasting (WRF) model. The WRF‐EMS provides scripting for downloading appropriate initial and boundary conditions from global models, along with higher‐resolution vegetation, land surface, and sea surface temperature data sets provided by the NASA Short‐term Prediction Research and Transition (SPoRT) Center. This presentation will provide an overview of the modeling system capabilities and benchmarks performed on the Amazon Elastic Compute Cloud (EC2) environment. In addition, the presentation will discuss future opportunities to deploy the system in support of weather prediction in developing countries supported by NASA's SERVIR Project, which provides capacity building activities in environmental monitoring and prediction across a growing number of regional hubs throughout the world. Capacity‐building applications that extend numerical weather prediction to developing countries are intended to provide near real‐time applications to benefit public health, safety, and economic interests, but may have a greater impact during disaster events by providing a source for local predictions of weather‐related hazards, or impacts that local weather events may have during the recovery phase.

Molthan, Andrew↗
NASA NTRS1990

Resource Allocation Planning Helper (RALPH): Lessons learned

The current task of Resource Allocation Process includes the planning and apportionment of JPL's Ground Data System composed of the Deep Space Network and Mission Control and Computing Center facilities. The addition of the data driven, rule based planning system, RALPH, has expanded the planning horizon from 8 weeks to 10 years and has resulted in large labor savings. Use of the system has also resulted in important improvements in science return through enhanced resource utilization. In addition, RALPH has been instrumental in supporting rapid turn around for an increased volume of special what if studies. The status of RALPH is briefly reviewed and important lessons learned from the creation of an highly functional design team are focused on through an evolutionary design and implementation period in which an AI shell was selected, prototyped, and ultimately abandoned, and through the fundamental changes to the very process that spawned the tool kit. Principal topics include proper integration of software tools within the planning environment, transition from prototype to delivered to delivered software, changes in the planning methodology as a result of evolving software capabilities and creation of the ability to develop and process generic requirements to allow planning flexibility.

Durham, Ralph↗
NASA NTRS2006

Cassini Archive Tracking System

The Cassini Archive Tracking System (CATS) is a computer program that enables tracking of scientific data transfers from originators to the Planetary Data System (PDS) archives. Without CATS, there is no systematic means of locating products in the archive process or ensuring their completeness. By keeping a database of transfer communications and status, CATS enables the Cassini Project and the PDS to efficiently and accurately report on archive status. More importantly, problem areas are easily identified through customized reports that can be generated on the fly from any Web-enabled computer. A Web-browser interface and clearly defined authorization scheme provide safe distributed access to the system, where users can perform functions such as create customized reports, record a transfer, and respond to a transfer. CATS ensures that Cassini provides complete science archives to the PDS on schedule and that those archives are available to the science community by the PDS. The three-tier architecture is loosely coupled and designed for simple adaptation to multimission use. Written in the Java programming language, it is portable and can be run on any Java-enabled Web server.

Conner, Diane↗
NASA NTRS2013

Human and Robotic Space Mission Use Cases for High-Performance Spaceflight Computing

Spaceflight computing is a key resource in NASA space missions and a core determining factor of spacecraft capability, with ripple effects throughout the spacecraft, end-to-end system, and the mission; it can be aptly viewed as a "technology multiplier" in that advances in onboard computing provide dramatic improvements in flight functions and capabilities across the NASA mission classes, and will enable new flight capabilities and mission scenarios, increasing science and exploration return per mission-dollar.

flight computing↗
NASA NTRS2022

A Strategic Lens on Quantum Sensing for Space Applications

As classical technologies approach their theoretical power limits, quantum technologies, including computing, communications, and sensing, are often credited as the next science and engineering revolution. Quantum sensors are the basis of quantum computing and communications technologies, but also have unique uses for security, medical, and space-related applications. Regarding NASA’s agency goals, quantum sensing can improve climate change monitoring, enable navigations systems for deep space, and enhance fundamental astrophysics research. This report outlines the findings from an independent intern project on the ways NASA can strategically invest in quantum sensing technologies. This report also outlines policy barriers to developing the technology, largely related to communication difficulties, unfamiliarity with quantum, and lengthy approval processes. The information on tools and challenges relevant to quantum technology was gathered from literature reviews, online research, and discussions with NASA individuals. This report concludes with strategic recommendations to answer the question: what policies should NASA implement to effectively research and develop quantum sensing technologies?

Holland Frieling↗
NASA NTRS2011

Hyperresolution Global Land Surface Modeling: Meeting a Grand Challenge for Monitoring Earth's Terrestrial Water

Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (approx.10-100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 10(exp 9) unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a grand challenge to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

Wood, Eric F.↗
NASA NTRS1995

Data handling and visualization for NASA's science programs

Advanced information systems capabilities are essential to conducting NASA's scientific research mission. Access to these capabilities is no longer a luxury for a select few within the science community, but rather an absolute necessity for carrying out scientific investigations. The dependence on high performance computing and networking, as well as ready and expedient access to science data, metadata, and analysis tools is the fundamental underpinning for the entire research endeavor. At the same time, advances in the whole range of information technologies continues on an almost explosive growth path, reaching beyond the research community to affect the population as a whole. Capitalizing on and exploiting these advances are critical to the continued success of space science investigations. NASA must remain abreast of developments in the field and strike an appropriate balance between being a smart buyer and a direct investor in the technology which serves its unique requirements. Another key theme deals with the need for the space and computer science communities to collaborate as partners to more fully realize the potential of information technology in the space science research environment.

Bredekamp, Joseph H.↗
NASA NTRS1997

Center of Excellence in Space Data and Information Science, Year 9

This report summarizes the range of computer science related activities undertaken by CESDIS(Center of Excellence in Space Data and Information Sciences) for NASA in the twelve months from July 1, 1996 through June 30, 1997. These activities address issues related to accessing, processing, and analyzing data from space observing systems through collaborative efforts with university, industry, and NASA space and Earth scientists.

DATA MANAGEMENT↗
NASA NTRS2006

Biology Inspired Approach for Communal Behavior in Sensor Networks

Research in wireless sensor network technology has exploded in the last decade. Promises of complex and ubiquitous control of the physical environment by these networks open avenues for new kinds of science and business. Due to the small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors working in concert. Although the reduction in size has been phenomenal it results in severe limitations on the computing, communicating, and power capabilities of these devices. Under these constraints, research efforts have concentrated on developing techniques for performing relatively simple tasks with minimal energy expense assuming some form of centralized control. Unfortunately, centralized control does not scale to massive size networks and execution of simple tasks in sparsely populated networks will not lead to the sophisticated applications predicted. These must be enabled by new techniques dependent on local and autonomous cooperation between sensors to effect global functions. As a step in that direction, in this work we detail a technique whereby a large population of sensors can attain a global goal using only local information and by making only local decisions without any form of centralized control.

Jones, Kennie H.↗
NASA NTRS1999

Research and Educational Opportunities with NASA GSFC

The research carried out in the Earth sciences at NASA's Goddard Space Flight Center will be the focus of the presentation. These research interests span the full breath of disciplines in Earth System Science. Branches and research groups focus on areas as diverse as planetary geomagnetics and atmospheric chemistry. There are 4 major laboratories in the directorate and 2 organizations that focus on scientific information technology. These laboratories focus on atmospheric sciences (atmospheric chemistry, climate and radiation, regional processes, atmospheric modeling), hydrological sciences (snow, ice, oceans, and seasonal-to-interannual prediction), terrestrial physics (geology, terrestrial biology, land-atmosphere interactions, geophysics), climate modeling (global warming, greenhouse gases, climate change). Two of the labs also have branches that focus on sensor development especially using lidar and microwave technologies. In the information technologies, areas of scientific and technical research, and expertise include massively parallel computers, technologies for high speed electronic networks, scientific visualization, information systems, archive and distribution systems, and information processing. Examples will be presented from each of these research disciplines.

Meeson, Blanche W.↗