Results for “computational environment” — Page 4

NASA NTRS1989

Computer network environment planning and analysis

The GSFC Computer Network Environment provides a broadband RF cable between campus buildings and ethernet spines in buildings for the interlinking of Local Area Networks (LANs). This system provides terminal and computer linkage among host and user systems thereby providing E-mail services, file exchange capability, and certain distributed computing opportunities. The Environment is designed to be transparent and supports multiple protocols. Networking at Goddard has a short history and has been under coordinated control of a Network Steering Committee for slightly more than two years; network growth has been rapid with more than 1500 nodes currently addressed and greater expansion expected. A new RF cable system with a different topology is being installed during summer 1989; consideration of a fiber optics system for the future will begin soon. Summmer study was directed toward Network Steering Committee operation and planning plus consideration of Center Network Environment analysis and modeling. Biweekly Steering Committee meetings were attended to learn the background of the network and the concerns of those managing it. Suggestions for historical data gathering have been made to support future planning and modeling. Data Systems Dynamic Simulator, a simulation package developed at NASA and maintained at GSFC was studied as a possible modeling tool for the network environment. A modeling concept based on a hierarchical model was hypothesized for further development. Such a model would allow input of newly updated parameters and would provide an estimation of the behavior of the network.

Dalphin, John F.↗

NASA NTRS2018

Significance of DSMC Computed Aerothermal Environments in the Rarefied Regime for Atmospheric Entry Material Response

During Mars atmospheric entry, the Mars Science Laboratory (MSL) was protected by a 4.5 meters diameter ablative heatshield assembled in 113 tiles. The heatshield was made of NASA's flagship ablative material, the Phenolic Impregnated Carbon Ablator (PICA). Prior work compared the traditional one-dimensional and three-dimensional material response models at different locations in the heatshield. It was observed that the flow was basically one-dimensional in the nose and flank regions, but three-dimensional flow effects were observed in the outer flank. The objective of this work is to study the effects of the aerothermal environment on the material response. We extend prior work by computing aerothermal environments using the direct simulation Monte Carlo (DSMC) code SPARTA and the CFD code Data Parallel Line Relaxation (DPLR). SPARTA is used to compute environment in the rarefied regime prior to 48.4s of entry where the Knudsen number is such that the Navier-Stokes equations can be inaccurate. Similarly to previous work, the DPLR software is used to compute the hypersonic environment for laminar then turbulent boundary layer assumptions from 48.4 s up to 100 s after Entry Interface (EI) along the MSL 08-TPS-02/01a trajectory. We observe that extending the aerothermal environments to times prior to 48.4 s modifies the thermal response of the heat shield at the surface and in-depth; however the effects on the recession are minimal. Additionally, using the assumption of a turbulent boundary layer versus a laminar one leads to higher surface and in-depth temperatures, larger recession, and a displacement of the peak heating and peak recession location.

Aerothermal↗

NASA NTRS1994

Visual Environments for CFD Research

This viewgraph presentation gives an overview of the visual environments for computational fluid dynamics (CFD) research. It includes details on critical needs from the future computer environment, features needed to attain this environment, prospects for changes in and the impact of the visualization revolution on the human-computer interface, human processing capabilities, limits of personal environment and the extension of that environment with computers. Information is given on the need for more 'visual' thinking (including instances of visual thinking), an evaluation of the alternate approaches for and levels of interactive computer graphics, a visual analysis of computational fluid dynamics, and an analysis of visualization software.

Watson, Val↗

NASA NTRS2024

GlennICE Manual 4.1.0

GlennICE (Glenn Icing Computational Environment) is a computational tool designed to calculate ice growth on complex three-dimensional geometries using the input from a user-supplied computational fluid dynamics (CFD) solution for the geometry of interest. The NASA John H. Glenn Research Center at Lewis Field is developing this tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This domestically available software is being developed to enable the introduction of new icing physics into a computational environment in a manner that is open for evaluation and eventual use by industry, academia, and other government organizations.

Icing↗

NASA NTRSDate not supplied

GlennICE 2.2 Capabilities and Results

GlennICE (Glenn Icing Computational Environment) is a computational tool designed to calculate ice growth on complex three-dimensional geometries using the input from a user-supplied computational fluid dynamics (CFD) solution for the geometry of interest. The NASA John H. Glenn Research Center at Lewis Field is developing this tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This domestically available software is being developed to enable the introduction of new icing physics into a computational environment in a manner that is open for evaluation and eventual use by industry, academia, and other government organizations. This paper will document the current capabilities for version 2.1 of this software and provide example cases with comparison to available experimental data.

Icing↗

NASA NTRSDate not supplied

GlennICE 2.2 Capabilities and Results

GlennICE (Glenn Icing Computational Environment) is a computational tool designed to calculate ice growth on complex three-dimensional geometries using the input from a user-supplied computational fluid dynamics (CFD) solution for the geometry of interest. The NASA John H. Glenn Research Center at Lewis Field is developing this tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This domestically available software is being developed to enable the introduction of new icing physics into a computational environment in a manner that is open for evaluation and eventual use by industry, academia, and other government organizations. This paper will document the current capabilities for version 2.1 of this software and provide example cases with comparison to available experimental data.

Icing↗

NASA NTRSDate not supplied

Improvements to GlennICE Collection Efficiency Algorithm

GlennICE (Glenn Icing Computational Environment) is a computational tool designed to calculate ice growth on complex three-dimensional geometries using the input from a user-supplied computational fluid dynamics (CFD) solution for the geometry of interest. The NASA John H. Glenn Research Center at Lewis Field is developing this tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This domestically available software is being developed to enable the introduction of new icing physics into a computational environment in a manner that is open for evaluation and eventual use by industry, academia, and other government organizations. This paper will document recent improvements that reduce the number of trajectories needed to converge on collection efficiency. These improvements are documented using example cases with complex geometries.

Aircraft Icing↗

NASA NTRSDate not supplied

Improvements to GlennICE Collection Efficiency Algorithm

GlennICE (Glenn Icing Computational Environment) is a computational tool designed to calculate ice growth on complex three-dimensional geometries using the input from a user-supplied computational fluid dynamics (CFD) solution for the geometry of interest. The NASA John H. Glenn Research Center at Lewis Field is developing this tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This domestically available software is being developed to enable the introduction of new icing physics into a computational environment in a manner that is open for evaluation and eventual use by industry, academia, and other government organizations. This paper will document recent improvements that reduce the number of trajectories needed to converge on collection efficiency. These improvements are documented using example cases with complex geometries.

Aircraft Icing↗

NASA NTRS1997

pV3-Gold Visualization Environment for Computer Simulations

A new visualization environment, pV3-Gold, can be used during and after a computer simulation to extract and visualize the physical features in the results. This environment, which is an extension of the pV3 visualization environment developed at the Massachusetts Institute of Technology with guidance and support by researchers at the NASA Lewis Research Center, features many tools that allow users to display data in various ways.

Babrauckas, Theresa L.↗

NASA NTRS2011

Fault recovery for real-time, multi-tasking computer system

System and methods for providing a recoverable real time multi-tasking computer system are disclosed. In one embodiment, a system comprises a real time computing environment, wherein the real time computing environment is adapted to execute one or more applications and wherein each application is time and space partitioned. The system further comprises a fault detection system adapted to detect one or more faults affecting the real time computing environment and a fault recovery system, wherein upon the detection of a fault the fault recovery system is adapted to restore a backup set of state variables.

Hess, Richard↗

NASA NTRS1994

The software analysis project for the Office of Human Resources

There were two major sections of the project for the Office of Human Resources (OHR). The first section was to conduct a planning study to analyze software use with the goal of recommending software purchases and determining whether the need exists for a file server. The second section was analysis and distribution planning for retirement planning computer program entitled VISION provided by NASA Headquarters. The software planning study was developed to help OHR analyze the current administrative desktop computing environment and make decisions regarding software acquisition and implementation. There were three major areas addressed by the study: current environment new software requirements, and strategies regarding the implementation of a server in the Office. To gather data on current environment, employees were surveyed and an inventory of computers were produced. The surveys were compiled and analyzed by the ASEE fellow with interpretation help by OHR staff. New software requirements represented a compilation and analysis of the surveyed requests of OHR personnel. Finally, the information on the use of a server represents research done by the ASEE fellow and analysis of survey data to determine software requirements for a server. This included selection of a methodology to estimate the number of copies of each software program required given current use and estimated growth. The report presents the results of the computing survey, a description of the current computing environment, recommenations for changes in the computing environment, current software needs, management advantages of using a server, and management considerations in the implementation of a server. In addition, detailed specifications were presented for the hardware and software recommendations to offer a complete picture to OHR management. The retirement planning computer program available to NASA employees will aid in long-range retirement planning. The intended audience is the NASA civil service employee with several years until retirement. The employee enters current salary and savings information as well as goals concerning salary at retirement, assumptions on inflation, and the return on investments. The program produces a picture of the employee's retirement income from all sources based on the assumptions entered. A session showing features of the program was conducted for key personnel at the Center. After analysis, it was decided to offer the program through the Learning Center starting in August 1994.

Tureman, Robert L., Jr.↗

NASA NTRS2003

Additional Security Considerations for Grid Management

The use of Grid computing environments is growing in popularity. A Grid computing environment is primarily a wide area network that encompasses multiple local area networks, where some of the local area networks are managed by different organizations. A Grid computing environment also includes common interfaces for distributed computing software so that the heterogeneous set of machines that make up the Grid can be used more easily. The other key feature of a Grid is that the distributed computing software includes appropriate security technology. The focus of most Grid software is on the security involved with application execution, file transfers, and other remote computing procedures. However, there are other important security issues related to the management of a Grid and the users who use that Grid. This note discusses these additional security issues and makes several suggestions as how they can be managed.

Eidson, Thomas M.↗

NASA NTRS2003

Control Law Design in a Computational Aeroelasticity Environment

A methodology for designing active control laws in a computational aeroelasticity environment is given. The methodology involves employing a systems identification technique to develop an explicit state-space model for control law design from the output of a computational aeroelasticity code. The particular computational aeroelasticity code employed in this paper solves the transonic small disturbance aerodynamic equation using a time-accurate, finite-difference scheme. Linear structural dynamics equations are integrated simultaneously with the computational fluid dynamics equations to determine the time responses of the structure. These structural responses are employed as the input to a modern systems identification technique that determines the Markov parameters of an "equivalent linear system". The Eigensystem Realization Algorithm is then employed to develop an explicit state-space model of the equivalent linear system. The Linear Quadratic Guassian control law design technique is employed to design a control law. The computational aeroelasticity code is modified to accept control laws and perform closed-loop simulations. Flutter control of a rectangular wing model is chosen to demonstrate the methodology. Various cases are used to illustrate the usefulness of the methodology as the nonlinearity of the aeroelastic system is increased through increased angle-of-attack changes.

Newsom, Jerry R.↗

NASA NTRS1968

Techniques developed to determine aerodynamic coefficients for Apollo applications program vehicles in an orbital environment

Computer programs to determine aerodynamic coefficients for Apollo Applications Program vehicles in orbital environment

Johnson, J. D.↗

NASA NTRS1998

Heterogeneous Distributed Computing for Computational Aerosciences

The research supported under this award focuses on heterogeneous distributed computing for high-performance applications, with particular emphasis on computational aerosciences. The overall goal of this project was to and investigate issues in, and develop solutions to, efficient execution of computational aeroscience codes in heterogeneous concurrent computing environments. In particular, we worked in the context of the PVM[1] system and, subsequent to detailed conversion efforts and performance benchmarking, devising novel techniques to increase the efficacy of heterogeneous networked environments for computational aerosciences. Our work has been based upon the NAS Parallel Benchmark suite, but has also recently expanded in scope to include the NAS I/O benchmarks as specified in the NHT-1 document. In this report we summarize our research accomplishments under the auspices of the grant.

Sunderam, Vaidy S.↗

NASA NTRS2010

A Chess-Like Game for Teaching Engineering Students to Solve Large System of Simultaneous Linear Equations

Solving large (and sparse) system of simultaneous linear equations has been (and continues to be) a major challenging problem for many real-world engineering/science applications [1-2]. For many practical/large-scale problems, the sparse, Symmetrical and Positive Definite (SPD) system of linear equations can be conveniently represented in matrix notation as [A] {x} = {b} , where the square coefficient matrix [A] and the Right-Hand-Side (RHS) vector {b} are known. The unknown solution vector {x} can be efficiently solved by the following step-by-step procedures [1-2]: Reordering phase, Matrix Factorization phase, Forward solution phase, and Backward solution phase. In this research work, a Game-Based Learning (GBL) approach has been developed to help engineering students to understand crucial details about matrix reordering and factorization phases. A "chess-like" game has been developed and can be played by either a single player, or two players. Through this "chess-like" open-ended game, the players/learners will not only understand the key concepts involved in reordering algorithms (based on existing algorithms), but also have the opportunities to "discover new algorithms" which are better than existing algorithms. Implementing the proposed "chess-like" game for matrix reordering and factorization phases can be enhanced by FLASH [3] computer environments, where computer simulation with animated human voice, sound effects, visual/graphical/colorful displays of matrix tables, score (or monetary) awards for the best game players, etc. can all be exploited. Preliminary demonstrations of the developed GBL approach can be viewed by anyone who has access to the internet web-site [4]!

Nguyen, Duc T.↗

NASA NTRS2006

ASPEN Version 3.0

The Automated Scheduling and Planning Environment (ASPEN) computer program has been updated to version 3.0. ASPEN is a modular, reconfigurable, application software framework for solving batch problems that involve reasoning about time, activities, states, and resources. Applications of ASPEN can include planning spacecraft missions, scheduling of personnel, and managing supply chains, inventories, and production lines. ASPEN 3.0 can be customized for a wide range of applications and for a variety of computing environments that include various central processing units and random access memories.

Rabideau, Gregg↗

NASA NTRS2006

Tool for Analysis and Reduction of Scientific Data

The Automated Scheduling and Planning Environment (ASPEN) computer program has been updated to version 3.0. ASPEN as a whole (up to version 2.0) has been summarized, and selected aspects of ASPEN have been discussed in several previous NASA Tech Briefs articles. Restated briefly, ASPEN is a modular, reconfigurable, application software framework for solving batch problems that involve reasoning about time, activities, states, and resources. Applications of ASPEN can include planning spacecraft missions, scheduling of personnel, and managing supply chains, inventories, and production lines. ASPEN 3.0 can be customized for a wide range of applications and for a variety of computing environments that include various central processing units and randomaccess memories. Domain-specific reasoning modules (e.g., modules for determining orbits for spacecraft) can easily be plugged into ASPEN 3.0. Improvements over other, similar software that have been incorporated into ASPEN 3.0 include a provision for more expressive time-line values, new parsing capabilities afforded by an ASPEN language based on Extensible Markup Language, improved search capabilities, and improved interfaces to other, utility-type software (notably including MATLAB).

James, Mark↗