Research Campaign: The Sciences of Space Manufacturing
Explore the source record for details and available documents.
Decadal Survey↗
SEARCH · Engineering Papers
Results for “computer Science”
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.
Coordinated Science Laboratory Summary progress report, Sep. - Nov. 1965
Progress related to surface physics, computer programs, control systems, information science, superconductivity, and other research projects
PLASMA PHYSICS↗
Design of Mariner 9 Science Sequences using Interactive Graphics Software
This paper discusses the analyst/computer system used to design the daily science sequences required to carry out the desired Mariner 9 science plan. The Mariner 9 computer environment, the development and capabilities of the science sequence design software, and the techniques followed in the daily mission operations are discussed. Included is a discussion of the overall mission operations organization and the individual components which played an essential role in the sequence design process. A summary of actual sequences processed, a discussion of problems encountered, and recommendations for future applications are given.
Freeman, J. E.↗
Human Centered Computing for Mars Exploration
The science objectives are to determine the aqueous, climatic, and geologic history of a site on Mars where conditions may have been favorable to the preservation of evidence of prebiotic or biotic processes. Human Centered Computing is a development process that starts with users and their needs, rather than with technology. The goal is a system design that serves the user, where the technology fits the task and the complexity is that of the task not of the tool.
Trimble, Jay↗
The SGI/CRAY T3E: Experiences and Insights
The focus of the HPCC Earth and Space Sciences (ESS) Project is capability computing - pushing highly scalable computing testbeds to their performance limits. The drivers of this focus are the Grand Challenge problems in Earth and space science: those that could not be addressed in a capacity computing environment where large jobs must continually compete for resources. These Grand Challenge codes require a high degree of communication, large memory, and very large I/O (throughout the duration of the processing, not just in loading initial conditions and saving final results). This set of parameters led to the selection of an SGI/Cray T3E as the current ESS Computing Testbed. The T3E at the Goddard Space Flight Center is a unique computational resource within NASA. As such, it must be managed to effectively support the diverse research efforts across the NASA research community yet still enable the ESS Grand Challenge Investigator teams to achieve their performance milestones, for which the system was intended. To date, all Grand Challenge Investigator teams have achieved the 10 GFLOPS milestone, eight of nine have achieved the 50 GFLOPS milestone, and three have achieved the 100 GFLOPS milestone. In addition, many technical papers have been published highlighting results achieved on the NASA T3E, including some at this Workshop. The successes enabled by the NASA T3E computing environment are best illustrated by the 512 PE upgrade funded by the NASA Earth Science Enterprise earlier this year. Never before has an HPCC computing testbed been so well received by the general NASA science community that it was deemed critical to the success of a core NASA science effort. NASA looks forward to many more success stories before the conclusion of the NASA-SGI/Cray cooperative agreement in June 1999.
Bernard, Lisa Hamet↗
NASA's Information Power Grid: Large Scale Distributed Computing and Data Management
Large-scale science and engineering are done through the interaction of people, heterogeneous computing resources, information systems, and instruments, all of which are geographically and organizationally dispersed. The overall motivation for Grids is to facilitate the routine interactions of these resources in order to support large-scale science and engineering. Multi-disciplinary simulations provide a good example of a class of applications that are very likely to require aggregation of widely distributed computing, data, and intellectual resources. Such simulations - e.g. whole system aircraft simulation and whole system living cell simulation - require integrating applications and data that are developed by different teams of researchers frequently in different locations. The research team's are the only ones that have the expertise to maintain and improve the simulation code and/or the body of experimental data that drives the simulations. This results in an inherently distributed computing and data management environment.
Johnston, William E.↗
Digital optical computers at the optoelectronic computing systems center
The Digital Optical Computing Program within the National Science Foundation Engineering Research Center for Opto-electronic Computing Systems has as its specific goal research on optical computing architectures suitable for use at the highest possible speeds. The program can be targeted toward exploiting the time domain because other programs in the Center are pursuing research on parallel optical systems, exploiting optical interconnection and optical devices and materials. Using a general purpose computing architecture as the focus, we are developing design techniques, tools and architecture for operation at the speed of light limit. Experimental work is being done with the somewhat low speed components currently available but with architectures which will scale up in speed as faster devices are developed. The design algorithms and tools developed for a general purpose, stored program computer are being applied to other systems such as optimally controlled optical communication networks.
Jordan, Harry F.↗
Federated Cloud Challenges in NASA's Earth Science Data Systems (Why So Difficult?)
NASA is presented with a number of opportunities and challenges in federating its Earth Science Data Systems in the burgeoning world of cloud computing. Cloud hosting of Earth Science data provides a new way of bringing data together, at least from a virtual location sense, and is one of the main motives for NASA to host data there. However, NASA is also faced with a Big Data Variety challenge, brought on by the variety of the EO datasets in its archives. This diversity requires many diverse science archives to service the different science communities. As a result, nearly every major function in the Earth Observing System Data and Information System (EOSDIS) must also be federated across its data centers. This pattern is repeated with many of the outside agencies and organizations that EOSDIS federates with, such as the Committee for Earth Observing Satellites, leading to pioneering work on "deep federation" in a joint project with the European Space Agency to develop a Multi-Mission Algorithm and Analysis Platform.
Lynnes, Christopher↗
The Visualization, Exploration, and Data Analysis (VEDA) Platform: A Modular, Open Platform Lowering the Barrier to Entry to Cloud Computing
Explore the source record for details and available documents.
Data Science↗
The impact of supercomputers on experimentation: A view from a national laboratory
The relative roles of large scale scientific computers and physical experiments in several science and engineering disciplines are discussed. Increasing dependence on computers is shown to be motivated both by the rapid growth in computer speed and memory, which permits accurate numerical simulation of complex physical phenomena, and by the rapid reduction in the cost of performing a calculation, which makes computation an increasingly attractive complement to experimentation. Computer speed and memory requirements are presented for selected areas of such disciplines as fluid dynamics, aerodynamics, aerothermodynamics, chemistry, atmospheric sciences, astronomy, and astrophysics, together with some examples of the complementary nature of computation and experiment. Finally, the impact of the emerging role of computers in the technical disciplines is discussed in terms of both the requirements for experimentation and the attainment of previously inaccessible information on physical processes.
Peterson, V. L.↗
The impact of supercomputers on experimentation - A view from a National Laboratory
The relative roles of large-scale scientific computers and physical experiments in several science and engineering disciplines are discussed. Increasing dependence on computers is shown to be motivated both by the rapid growth in computer speed and memory, which permits accurate numerical simulation of complex physical phenomena, and by the rapid reduction in the cost of performing a calculation, which makes computation an increasingly attractive complement to experimentation. Computer speed and memory requirements are presented for selected areas of such disciplines as fluid dynamics, aerodynamics, aerothermodynamics, chemistry, atmospheric sciences, astronomy, and astrophysics, together with some examples of the complementary nature of computation and experiment. Finally, the impact of the emerging role of computers in the technical disciplines is discussed in terms of both the requirements for experimentation and the attainment of previously inaccessible information on physical processes.
Peterson, V. L.↗
The Impact of Supercomputers on Experimentation: A View from a National Laboratory
The relative roles of large-scale scientific computers and physical experiments in several science and engineering disciplines are discussed. Increasing dependence on computers is shown to be motivated both by the rapid growth in computer speed and memory, which permits accurate numerical simulation of complex physical phenomena, and by the rapid reduction in the cost of performing a calculation, which makes computation an increasingly, attractive complement to experimentation. Computer speed and memory requirements are presented for selected areas of such disciplines as fluid dynamics, aerodynamics, aerothermodynamics, chemistry, atmospheric sciences, astronomy, and astrophysics, together with some examples of the complementary nature of computation and experiment. Finally the impact of the emerging role of computers in the technical disciplines is discussed in terms of both the requirements for experimentation and the attainment of previously inaccessible information on physical processes.
Peterson, V.L.↗
The Montage architecture for grid-enabled science processing of large, distributed datasets
Montage is an Earth Science Technology Office (ESTO) Computational Technologies (CT) Round III Grand Challenge investigation to deploy a portable, compute-intensive, custom astronomical image mosaicking service for the National Virtual Observatory (NVO). Although Montage is developing a compute- and data-intensive service for the astronomy community, we are also helping to address a problem that spans both Earth and Space science, namely how to efficiently access and process multi-terabyte, distributed datasets. In both communities, the datasets are massive, and are stored in distributed archives that are, in most cases, remote from the available Computational resources. Therefore, state of the art computational grid technologies are a key element of the Montage portal architecture. This paper describes the aspects of the Montage design that are applicable to both the Earth and Space science communities.
virtual observatory↗
What Machines Need to Learn to Support Human Problem-Solving
In the development of intelligent systems that interact with humans, there is often confusion between how the system functions with respect to the humans it interacts with and how it interfaces with those humans. The former is a much deeper challenge than the latter it requires a system-level understanding of evolving human roles as well as an understanding of what humans need to know (and when) in order to perform their tasks. This talk will focus on some of the challenges in getting this right as well as on the type of research and development that results in successful human-autonomy teaming. Brief Bio: Dr. Alonso Vera is Chief of the Human Systems Integration Division at NASA Ames Research Center. His expertise is in human-computer interaction, information systems, artificial intelligence, and computational human performance modeling. He has led the design, development and deployment of mission software systems across NASA robotic and human space flight missions, including Mars Exploration Rovers, Phoenix Mars Lander, ISS, Constellation, and Exploration Systems. Dr. Vera received a Bachelor of Science with First Class Honors from McGill University in 1985 and a Ph.D. from Cornell University in 1991. He went on to a Post-Doctoral Fellowship in the School of Computer Science at Carnegie Mellon University from 1990-93.
intelligent systems↗
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.↗
High-temperature properties of gases
Computational chemistry is being applied at NASA Ames Research Center to a variety of problems in chemistry, physics, and materials sciences. Supercomputers and modern computational chemistry techniques have provided a powerful new tool to help fill NASA's continuing need for information about the properties of gases and materials as well as their interaction. For example, radiative transition probabilities, spectroscopic constants, bond dissociation energies, transport properties, and chemical reaction rates for molecules can be determined computationally just as reliably as by experiment. Recent results on the radiative transition probabilities of the strongly radiating systems of air species, based on state-of-the-art computational chemistry calculations, are presented and compared with experimental data.
Cooper, David M.↗
Application of advanced computing techniques to the analysis and display of space science measurements
A prototype system has been developed to aid the experimental space scientist in the display and analysis of spaceborne data acquired from direct measurement sensors in orbit. We explored the implementation of a rule-based environment for semi-automatic generation of visualizations that assist the domain scientist in exploring one's data. The goal has been to enable rapid generation of visualizations which enhance the scientist's ability to thoroughly mine his data. Transferring the task of visualization generation from the human programmer to the computer produced a rapid prototyping environment for visualizations. The visualization and analysis environment has been tested against a set of data obtained from the Hot Plasma Composition Experiment on the AMPTE/CCE satellite creating new visualizations which provided new insight into the data.
Klumpar, D. M.↗
A Science Information Infrastructure for Access to Earth and Space Science Data through the Nation's Science Museums
In this project, we worked with the University of California at Berkeley/Center for Extreme Ultraviolet Astrophysics and five science museums (the National Air and Space Museum, the Science Museum of Virginia, the Lawrence Hall of Science, the Exploratorium., and the New York Hall of Science) to formulate plans for computer-based laboratories located at these museums. These Science Learning Laboratories would be networked and provided with real Earth and space science observations, as well as appropriate lesson plans, that would allow the general public to directly access and manipulate the actual remote sensing data, much as a scientist would.
Murray, S.↗