Boost-phase discrimination research

The final report describes the combined work of the Computational Chemistry and Aerothermodynamics branches within the Thermosciences Division at NASA Ames Research Center directed at understanding the signatures of shock-heated air. Considerable progress was made in determining accurate transition probabilities for the important band systems of NO that account for much of the emission in the ultraviolet region. Research carried out under this project showed that in order to reproduce the observed radiation from the bow shock region of missiles in their boost phase it is necessary to include the Burnett terms in the constituent equation, account for the non-Boltzmann energy distribution, correctly model the NO formation and rotational excitation process, and use accurate transition probabilities for the NO band systems. This work resulted in significant improvements in the computer code NEQAIR that models both the radiation and fluid dynamics in the shock region

Progress in computing nozzle/plume flow fields

The long-term goal is to develop the capability to predict chemically-reacting, multi-stream nozzle and plume flow fields. Two basic Navier-Stokes solvers, including the widely used F-3D code, are upgraded to include several upwind difference schemes and portable chemistry packages. Current computational capabilities for solving equilibrium single-stream and multi-stream, frozen gas, and finite rate chemistry problems are described. A variety of complex nozzle and plume flows were computed. Solutions presented include axisymmetric plume flow for ideal and equilibrium air, 3-D NASP nozzle/afterbody flow, and an internal nozzle calculation comparing various finite-rate chemistry packages

AN EXPERIMENTAL INVESTIGATION OF INCOMPRESSIBLE FLOW WITHOUT SWIRL IN R-RADIAL DIFFUSERS

Abstract not availabl

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

The term "Grid" refers to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. The vision for NASN's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks that will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: The scientist / design engineer whose primary interest is problem solving (e.g., determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user if the tool designer: The computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. This paper describes the current state of IPG (the operational testbed), the set of capabilities being put into place for the operational prototype IPG, as well as some of the longer term R&D tasks

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

Creating science-driven computer architecture: A new patch to scientific leadership

We believe that it is critical for the future of high end computing in the United States to bring into existence a new class of computational capability that is optimal for science. In recent years scientific computing has increasingly become dependent on hardware that is designed and optimized for commercial applications. Science in this country has greatly benefited from the improvements in computers that derive from advances in microprocessors following Moore's Law, and a strategy of relying on machines optimized primarily for business applications. However within the last several years, in part because of the challenge presented by the appearance of the Japanese Earth Simulator, the sense has been growing in the scientific community that a new strategy is needed. A more aggressive strategy than reliance only on market forces driven by business applications is necessary in order to achieve a better alignment between the needs of scientific computing and the platforms available. The United States should undertake a program that will result in scientific computing capability that durably returns the advantage to American science, because doing so is crucial to the country's future. Such a strategy must also be sustainable. New classes of computer designs will not only revolutionize the power of supercomputing for science, but will also affect scientific computing at all scales. What is called for is the opening of a new frontier of scientific capability that will ensure that American science is greatly enabled in its pursuit of research in critical areas such as nanoscience, climate prediction, combustion, modeling in the life sciences, and fusion energy, as well as in meeting essential needs for national security. In this white paper we propose a strategy for accomplishing this mission, pursuing different directions of hardware development and deployment, and establishing a highly capable networking and grid infrastructure connecting these platforms to the broad research community