SEARCH · Search NASA
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.
A user guide for a library of interactive computer routines used to develop performance analysis models of specific environmental control and life support subsystems is presented.
Automation reduces input length and potential data-entry errors. Matrix Automated Reduction and Coupling (MARC) program used for combining NASTRAN substructural models with primary structural model MARC also constructs job-control language (JCL) stream for NASTRAN batch job that utilizes previously-written user library of dynamic models. Minimizes lengthy input and reduces potential data-entry errors. MARC procedure used in assembling Space Shuttle orbiter dynamic models since 1983 and reduced NASTRAN modeling input time by as much as 50 percent. MARC program written in FORTRAN IV for interactive execution.
The main objective is the investigation, formulation, and generation of graphical representations of algorithms, structures, and processes for Ada (GRASP/Ada). The presented task, in which various graphical representations that can be extracted or generated from source code are described and categorized, is focused on reverse engineering. The following subject areas are covered: the system model; control structure diagram generator; object oriented design diagram generator; user interface; and the GRASP library.
This thesis discusses the development of firmware for the 68HC11 gripper controller. A general description of the software and hardware interfaces is given. The C library interface for the gripper is then described and followed by a detailed discussion of the software architecture of the firmware. A procedure to assemble and download 68HC11 programs is presented in the form of a tutorial. The tools used to implement this environment are then described. Finally, the implementation of the configuration management scheme used to manage all CIRSSE software is presented.
Testing is an essential part of any digital system design and one that can be made much easier if testing is considered during the design process rather than after the system is complete. There are a number of techniques for integrating testability into system design, but many of these traditional testing methods used for synchronous circuits are not directly applicable to non-clocked asynchronous circuits. As a result, many asynchronous circuits do not employ design for testability techniques. A method of using the familiar model of scan paths modified to test self-timed systems are presented. Specifically, circuits designed using a library of self-timed modules to assemble systems with two-phase transition control and bundled data paths are considered. The method involves modifying these self-timed modules such that circuits designed from them have a built-in scan path.
Linear Algebra is essential for numerous aerospace problems of interest. Formal reasoning about hybrid systems that contain variables modeled by differential equations rely on concepts from Linear Algebra such as eigenvalues, matrix decompositions, and matrix valued functions. For example, the long-term dynamics of a system of differential equations depend on the stability/instability of its equilibrium points, which often reduces to an eigenvalue problem. This talk will embark on a quest to formalize theorems and results about eigenvalues and eigenvectors using PVS. We shall start our journey with 2 x 2 complex matrices, where we will apply our PVS code to a simple example of a dynamical system. Since it can be difficult or impossible to give simple expressions of eigenvalues for larger matrices (i.e. 5 x 5 or higher), we then move towards specifying the power method for verified computation of eigenvalue approximations in PVS. This effort requires development of multivariate complex arithmetic. At the end of the day, having such additions to the PVS NASA libraries will help move towards the use of formal methods to verify concepts of control theory and system level verification.
ODIN/RLV is a digital computing system for the synthesis and optimization of reusable launch vehicle preliminary designs. The system consists of a library of technology modules in the form of independent computer programs and an executive program, ODINEX, which operates on the technology modules. The technology module library contains programs for estimating all major military flight vehicle system characteristics, for example, geometry, aerodynamics, economics, propulsion, inertia and volumetric properties, trajectories and missions, steady state aeroelasticity and flutter, and stability and control. A general system optimization module, a computer graphics module, and a program precompiler are available as user aids in the ODIN/RLV program technology module library.
A G189A simulation of the shuttle orbiter EC/lSS was prepared and used to study payload support capabilities. Two master program libraries of the G189A computer program were prepared for the NASA/JSC computer system. Several new component subroutines were added to the G189A program library and many existing subroutines were revised to improve their capabilities. A number of special analyses were performed in support of a NASA/JSC shuttle orbiter EC/LSS payload support capability study.
Message passing is among the most popular techniques for parallelizing scientific programs on distributed-memory architectures. The reasons for its success are wide availability (MPI), efficiency, and full tuning control provided to the programmer. A major drawback, however, is that incremental parallelization, as offered by compiler directives, is not generally possible, because all data structures have to be changed throughout the program simultaneously. Charon remedies this situation through mappings between distributed and non-distributed data. It allows breaking up the parallelization into small steps, guaranteeing correctness at every stage. Several tools are available to help convert legacy codes into high-performance message-passing programs. They usually target data-parallel applications, whose loops carrying most of the work can be distributed among all processors without much dependency analysis. Others do a full dependency analysis and then convert the code virtually automatically. Even more toolkits are available that aid construction from scratch of message passing programs. None, however, allows piecemeal translation of codes with complex data dependencies (i.e. non-data-parallel programs) into message passing codes. The Charon library (available in both C and Fortran) provides incremental parallelization capabilities by linking legacy code arrays with distributed arrays. During the conversion process, non-distributed and distributed arrays exist side by side, and simple mapping functions allow the programmer to switch between the two in any location in the program. Charon also provides wrapper functions that leave the structure of the legacy code intact, but that allow execution on truly distributed data. Finally, the library provides a rich set of communication functions that support virtually all patterns of remote data demands in realistic structured grid scientific programs, including transposition, nearest-neighbor communication, pipelining, gather/scatter, and redistribution. At the end of the conversion process most intermediate Charon function calls will have been removed, the non-distributed arrays will have been deleted, and virtually the only remaining Charon functions calls are the high-level, highly optimized communications. Distribution of the data is under complete control of the programmer, although a wide range of useful distributions is easily available through predefined functions. A crucial aspect of the library is that it does not allocate space for distributed arrays, but accepts programmer-specified memory. This has two major consequences. First, codes parallelized using Charon do not suffer from encapsulation; user data is always directly accessible. This provides high efficiency, and also retains the possibility of using message passing directly for highly irregular communications. Second, non-distributed arrays can be interpreted as (trivial) distributions in the Charon sense, which allows them to be mapped to truly distributed arrays, and vice versa. This is the mechanism that enables incremental parallelization. In this paper we provide a brief introduction of the library and then focus on the actual steps in the parallelization process, using some representative examples from, among others, the NAS Parallel Benchmarks. We show how a complicated two-dimensional pipeline-the prototypical non-data-parallel algorithm- can be constructed with ease. To demonstrate the flexibility of the library, we give examples of the stepwise, efficient parallel implementation of nonlocal boundary conditions common in aircraft simulations, as well as the construction of the sequence of grids required for multigrid.
This report documents the research conducted to update computer models for dynamic fluid flow simulation of the E-1 test stand subsystems at te NASA John C. Stennis Space Center.Work also involved significant upgrades to the capabilities of EASY/ROCKETS library through the inclusion of the NIST-12 thermodynamic property database and development of new control system modules.
The generation and operational use of the SEL 840MP multiprocessing control system (MPCS) are considered. System initialization, job task table generation, the MPCS command language, display library generation, and system error summary are reviewed.
Some of the problems unique to building a very large Ada system are addressed. This is done through examples from experience. In the winter of 1985 and 1986, Intermetrics bootstrapped the Ada compiler, which was being built over the last few years. This system consists of about one million lines of full Ada. Over the last few years a number of procedures and tools were adopted for managing the life cycle of each of the many parts of an Ada system. Many of these procedures are well known to most system builders: release management, quality assurance testing; and source file revision control. Others are unique to working in an Ada language environment; i.e., recompilation management, Ada program library management, and managing multiple implementations. First a look is taken at how a large Ada system is broken down into pieces. The Ada definition leaves unspecified a number of issues that the system builder must address: versions, subsystems, multiple implementations, and synchronization of branched development paths. Having introduced how the Ada systems are decomposed, a look is taken, via a series of examples, at how the life cylces of those parts is managed. The procedures and tools used to manage the evolution of the system are examined. It is hoped that other Ada system builders can build upon the experience of the last few years.
Two silicon CMOS application specific integrated circuits (ASICs), a data generation chip, and a data checker chip were designed. The conversion of the data generator circuitry into a pair of CMOS ASIC chips using the 1.2 micron standard cell library is documented. The logic design of the data checker is discussed. The functions of the control circuitry is described. An accurate estimate of timing relationships is essential to make sure that the logic design performs correctly under practical conditions. Timing and delay information are examined.
In this paper we report on the work we performed to extend the logic model checker SPIN with built-in support for the verification of periodic, real-time embedded software systems, as commonly used in aircraft, automobiles, and spacecraft. We first extended the SPIN verification algorithms to model priority based scheduling policies. Next, we added a library to support the modeling of periodic tasks. This library was used in a recent application of the SPIN model checker to verify the engine control software of an automobile, to study the feasibility of software triggers for unintended acceleration events.
The Mission Analysis, Operations, and Navigation Toolkit Environment (MONTE) is the Jet Propulsion Laboratory’s (JPL) signature astrodynamic computing platform. It was built to support JPL’s deep space exploration program, and has been used to fly robotic spacecraft to Mars, Jupiter, Saturn, Ceres, and many solar system small bodies. At its core, MONTE consists of low-level astrodynamic libraries that are written in C++ and presented to the end user as an importable Python language module. These libraries form the basis on which Python-language applications are built for specific astrodynamic applications, such as trajectory design and optimization, orbit determination, flight path control, and more. The first half of this paper gives context to the MONTE project by outlining its history, the field of deep space navigation and where MONTE fits into the current Python landscape. The second half gives an overview of the main MONTE libraries and provides a narrative example of how it can be used for astrodynamic analysis.
Seismic analysis is a technique which pertains to loading described in terms of boundary accelerations. Earthquake shocks to buildings is the type of excitation which usually comes to mind when one hears the word seismic, but this technique also applied to a broad class of acceleration excitations which are applied at the base of a structure such as vibration shaker testing or shocks to machinery foundations. Four different solution paths are available in NASTRAN for seismic analysis. They are: Direct Seismic Frequency Response, Direct Seismic Transient Response, Modal Seismic Frequency Response, and Modal Seismic Transient Response. This capability, at present, is invoked not as separate rigid formats, but as pre-packaged ALTER packets to existing RIGID Formats 8, 9, 11, and 12. These ALTER packets are included with the delivery of the NASTRAN program and are stored on the computer as a library of callable utilities. The user calls one of these utilities and merges it into the Executive Control Section of the data deck to perform any of the four options are invoked by setting parameter values in the bulk data.
Nonlinear programming, preliminary design problems, performance simulation problems trajectory optimization, flight computer optimization, and linear least squares problems are among the topics covered. The nonlinear programming applications encountered in a large aerospace company are a real challenge to those who provide mathematical software libraries and consultation services. Typical applications include preliminary design studies, data fitting and filtering, jet engine simulations, control system analysis, and trajectory optimization and optimal control. Problem sizes range from single-variable unconstrained minimization to constrained problems with highly nonlinear functions and hundreds of variables. Most of the applications can be posed as nonlinearly constrained minimization problems. Highly complex optimization problems with many variables were formulated in the early days of computing. At the time, many problems had to be reformulated or bypassed entirely, and solution methods often relied on problem-specific strategies. Problems with more than ten variables usually went unsolved.
ESMOSS is a specialized software system for the construction of geometric descriptive and discrete analytical models of engine parts, components and substructures which can be transferred to finite element analysis programs such as NASTRAN. The software architecture of ESMOSS is designed in modular form with a central executive module through which the user controls and directs the development of the analytical model. Modules consist of a geometric shape generator, a library of discretization procedures, interfacing modules to join both geometric and discrete models, a deck generator to produce input for NASTRAN and a 'recipe' processor which generates geometric models from parametric definitions. ESMOSS can be executed both in interactive and batch modes. Interactive mode is considered to be the default mode and that mode will be assumed in the discussion in this document unless stated otherwise.