Control Optimization, Stabilization and Computer Algorithms for Space Applications First Status Report, Mar. 1 - Aug. 31 1966
Control optimization, stabilization, and computer algorithms for space applications
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Control optimization, stabilization, and computer algorithms for space applications
This report provides an overview and commands description of the Computational Materials mini-application, Aladyn. Aladyn is a simple molecular dynamics code written in FORTRAN 2008, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of quantum mechanics-based energy calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. The Aladyn code is being released to serve as a training testbed for students and professors in academia to explore possible optimization algorithms for parallel computing on multicore central processing unit (CPU) computers or computers utilizing many core architectures based on graphic processing units (GPUs). The effort is related to the High Performance Computing Incubator (HPCI) project at NASA Langley Research Center.
Highlights: • X-ray Tomography is a powerful technique for graphite morphology characterization. • 3D characterization reveals true nodularity and spatial connectivity of graphite. • Tri-modal distribution of SG suggests a multi-stage graphite nucleation process. - Abstract: In the present study, high-energy X-ray tomography technique was used to characterize the graphite morphology of compact graphite iron. The size, shape, spatial connectivity and structure of different graphite morphologies were examined in 3D using computer-aided image analysis. In addition, nodularity analysis was performed in 3D and the results are compared to the traditional 2D technique. It is found that the variation of nodularity within 2 × 2 × 1.2 mm{sup 3} of the sample can be as high as 20 (%) from 2D analysis and the averaged nodularity (2D) is higher than that from 3D analysis. The size distribution of spheroidal graphite shows a tri-modal distribution, which suggests a multi-step nucleation process during solidification.
Abstract Not Provided
Computer program requirements for onboard checkout and data management system of Saturn/Apollo application program
Nuclear fuel performance computer codes have been developed over the last 50 years to analyze fuel behavior under various operating conditions. Traditionally, these codes used quasi-two-dimensional (also commonly known as 1.5D) representations of the fuel rod, which model the rod using a set of one-dimensional axisymmetric models that represent the behavior at specific axial positions on the rod. Modern fuel performance codes have the ability to investigate full three-dimensional (3D) effects and couple to other physics-based codes for true multiphysics simulations. However, with increasing complexity comes increasing computational costs. Many phenomena of interest involve azimuthally-varying behavior that cannot be represented using the aforementioned quasi-two-dimensional approach, but do not require the use of a full 3D model. To efficiently address these problems, there is a need for a computational framework that provides a compromise between the quasi-two-dimensional and full 3D models. In this paper, we present a new quasi-three-dimensional approach that represents the fuel as a set of 2D planar models that represent the behavior of the fuel cross-section at various axial positions. Presented here are the theory behind the methodology, test cases to illustrate proper implementation, and practical applications of its use in the BISON fuel performance code for a variety of cases in nuclear fuel analysis, such as fuel fracture, axial fuel relocation, and cladding distension and oxidation.
Research in man/machine interactions and graphics hardware/software that will enhance applications to engineering design was described. Research aspects of executive systems, command languages, and networking used in the computer applications laboratory are mentioned. Finally, a few areas where little or no research is being done were identified.
As computer systems grow in both size and complexity, the need for applications and run-time systems to adjust to their dynamic environment also grows. The goal of the RAAMP LDRD was to combine static architecture information and real-time system state with algorithms to conserve power, reduce communication costs, and avoid network contention. We devel- oped new data collection and aggregation tools to extract static hardware information (e.g., node/core hierarchy, network routing) as well as real-time performance data (e.g., CPU uti- lization, power consumption, memory bandwidth saturation, percentage of used bandwidth, number of network stalls). We created application interfaces that allowed this data to be used easily by algorithms. Finally, we demonstrated the benefit of integrating system and application information for two use cases. The first used real-time power consumption and memory bandwidth saturation data to throttle concurrency to save power without increasing application execution time. The second used static or real-time network traffic information to reduce or avoid network congestion by remapping MPI tasks to allocated processors. Results from our work are summarized in this report; more details are available in our publications [2, 6, 14, 16, 22, 29, 38, 44, 51, 54].
This report provides an overview and description of commands used in the Computational Materials mini-application, AladynPi. AladynPi is an extension of a previously released mini-application, Aladyn (https://github.com/nasa/aladyn; Yamakov, V.I., and Glaessgen, E.H., NASA/TM-2018-220104). Aladyn and AladynPi are basic molecular dynamics codes written in FORTRAN 2003, which are designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory method. An input for the ANN is a set of structure coefficients, characterizing the local atomic environment of each atom, for which the atomic energy is obtained in the ANN inference process. In Aladyn, the ANN gives directly the energy of interatomic interactions. In AladynPi, the ANN gives optimized parameters for a predefined empirical function, known as bond-order-potential (BOP). The parameterized BOP function is then used to calculate the energy. AladynPi code is being released to serve as a training testbed for students and professors in academia to explore possible optimization algorithms for parallel computing on multicore central processing unit (CPU) computers or computers utilizing manycore architectures based on graphic processing units (GPUs). The effort is supported by the High Performance Computing incubator (HPCi) project at NASA Langley Research Center.
This paper presents viewgraphs on computational physics for space flight applications. The topics include: 1) Introduction to space radiation effects in microelectronics; 2) Using applied physics to help NASA meet mission objectives; 3) Example of applied computational physics; and 4) Future directions in applied computational physics.
The applications of computers and data processing to astronomy are discussed. Among the topics covered are the emerging national information infrastructure, workstations and supercomputers, supertelescopes, digital astronomy, astrophysics in a numerical laboratory, community software, archiving of ground-based observations, dynamical simulations of complex systems, plasma astrophysics, and the remote control of fourth dimension supercomputers.
NASA-Ames hybrid computer facilities in flight simulations using slender coupling design in computer linkage
This paper is intended as a review and summary of the advances made in a recently developed approach for rapid numerical solution of the equations of inviscid transonic aerodynamics. The investigation has been limited to two-dimensional, steady, inviscid flow over airfoils in a subsonic free stream, with emphasis on development of a rapid computational technique, rather than on generality of application. The approach uses finite-difference algorithms called "fast direct elliptic solvers" within an iteration scheme. "Direct" means that the entire computation field is solved at once, rather than in successive traverses over the field as in a point- or line-relaxation method. Such an iterative method is referred to as "semidirect." The iterative convergence can be faster than in other relaxation methods because changes are felt simultaneously at all points in each succeeding iteration. Direct elliptic solvers and semidirect methods have restrictions, but these are gradually being removed. Direct solvers were first developed for solving Poisson's equation on a rectangle without interior boundaries. A method to treat first-order systems, a direct Cauchy-Riemann solver has also been developed. Numerical treatment of part of a system of nonlinear equations by a Poisson solver has been reported. Also Poisson solvers in semidirect methods were used for nonseparable elliptic equations. The semidirect method was extended to the solution of a problem of mixed type, where the improved Murman-Cole transonic small-disturbance difference equations were solved. A slightly supercritical flow over a biconvex airfoil was treated successfully, but the iterations did not converge for more strongly supercritical conditions In another work the addition of terms ot both sides of the difference equations stabilized the iteration for supercritical conditions with large supersonic zones. For this, the Cauchy-Riemann solver was revised to incl,ude the needed terms. Most recently, the evaluation of parameters for rapid convergence and comparisons, with Murman's line-relaxation method was described. The method was extended to full second order accuracy in a fully conservative formulation in another work.
Computational mechanics is that discipline of applied science and engineering devoted to the study of physical phenomena by means of computational methods based on mathematical modeling and simulation, utilizing digital computers. The discipline combines theoretical and applied mechanics, approximation theory, numerical analysis, and computer science. Computational mechanics has had a major impact on engineering analysis and design. When applied to structural mechanics, the discipline is referred to herein as computational structural mechanics. Complex structures being considered by NASA for the 1990's include composite primary aircraft structures and the space station. These structures will be much more difficult to analyze than today's structures and necessitate a major upgrade in computerized structural analysis technology. NASA has initiated a research activity in structural analysis called Computational Structural Mechanics (CSM). The broad objective of the CSM activity is to develop advanced structural analysis technology that will exploit modern and emerging computers, such as those with vector and/or parallel processing capabilities. Here, the current research directions for the Methods and Application Studies Team of the Langley CSM activity are described.
Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer composed of compute nodes that execute a parallel application, each compute node including application processors that execute the parallel application and at least one management processor dedicated to gathering information regarding data communications. The PAMI is composed of data communications endpoints, each endpoint composed of a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications through the PAMI and through data communications resources. Embodiments function by gathering call site statistics describing data communications resulting from execution of data communications instructions and identifying in dependence upon the call cite statistics a data communications algorithm for use in executing a data communications instruction at a call site in the parallel application.
Ullage collapse predictions made using Computational Fluid Dynamics (CFD) were validated then made for an in-space cryogenic propellant unsettling application. Ullage collapse is the decrease in propellant tank pressure due to cooling of the ullage gas, which can be significant for cryogenic propulsion systems. Vehicles may be developed that are robust to temperature and pressure changes caused by heat leaks, e.g., propellant tanks with high maximum operation pressures, technologies yielding active thermal conditioning, and systems with ample pressurant for conditioning. These methods are robust because additional mass, cost, and complexity are used to address cryogenic fluid management (CFM). As vehicles are optimized for increased payload capacity, tracking of events such as ullage collapse and self-pressurization in tanks will become increasingly important for propellant inventory calculations. Some ullage collapse events can be studied through ground experimentation, but propellant unsettling in and around in-space coast mission phases must be studied in the absence of an acceleration field. Computational Fluid Dynamics is a powerful tool to address this need, enabling prediction of complex physics prior to flight. Validation of the chosen CFD tool and modeling methodology was done using data from a previously conducted subscale slosh-induced ullage collapse ground test performed in part by the Japan Aerospace Exploration Agency (JAXA). A small tank was partially filled with liquid nitrogen and pressurized with gaseous nitrogen at various temperatures. The tank was oscillated laterally to induce high amplitude slosh dynamics resulting in wave breakup. Successful qualitative validation of slosh wave dynamics and quantitative validation of ullage collapse promoted confidence in extending ullage collapse predictions to a flight application. Mechanisms of ullage collapse caused by main engine cutoff while in-space were identified. Both slosh dynamics leading to engine shutdown and body dynamics following shutdown were shown to contribute to propellant unsettling and ullage collapse.
The application of computer graphics techniques in NASA space missions is reviewed. Telemetric monitoring of the Space Shuttle and its components is discussed, noting the use of computer graphics for real-time visualization problems in the retrieval and repair of the Solar Maximum Mission. The use of the world map display for determining a spacecraft's location above the earth and the problem of verifying the relative position and orientation of spacecraft to celestial bodies are examined. The Flight Dynamics/STS Three-dimensional Monitoring System and the Trajectroy Computations and Orbital Products System world map display are described, emphasizing Space Shuttle applications. Also, consideration is given to the development of monitoring systems such as the Shuttle Payloads Mission Monitoring System and the Attitude Heads-Up Display and the use of the NASA-Goddard Two-dimensional Graphics Monitoring System during Shuttle missions and to support the Hubble Space Telescope.
A computer oriented time code designed for users with various time resolution requirements is presented. It is intended as a time code for spacecraft and ground applications where direct code compatibility with automatic data processing equipment is of primary consideration. The principal features of this time code are: byte oriented format, selectable resolution options (from seconds to nanoseconds); and long ambiguity period. The time code is compatible with the new data handling and management concepts such as the NASA End-to-End Data System and the Telemetry Data Packetization format.