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At least 469 records · Page 26

All sources NASA NTRS DOE OSTI

NASA NTRS1993

Update of GRASP/Ada reverse engineering tools for Ada

The GRASP/Ada project (Graphical Representations of Algorithms, Structures, and Processes for Ada) successfully created and prototyped a new algorithmic level graphical representation for Ada software, the Control Structure Diagram (CSD). The primary impetus for creation of the CSD was to improve the comprehension efficiency of Ada software and, as a result, improve reliability and reduce costs. The emphasis was on the automatic generation of the CSD from Ada PDL or source code to support reverse engineering and maintenance. The CSD has the potential to replace traditional pretty printed Ada source code. In Phase 1 of the GRASP/Ada project, the CSD graphical constructs were created and applied manually to several small Ada programs. A prototype CSD generator (Version 1) was designed and implemented using FLEX and BISON running under VMS on a VAX 11-780. In Phase 2, the prototype was improved and ported to the Sun 4 platform under UNIX. A user interface was designed and partially implemented using the HP widget toolkit and the X Windows System. In Phase 3, the user interface was extensively reworked using the Athena widget toolkit and X Windows. The prototype was applied successfully to numerous Ada programs ranging in size from several hundred to several thousand lines of source code. Following Phase 3,e two update phases were completed. Update'92 focused on the initial analysis of evaluation data collected from software engineering students at Auburn University and the addition of significant enhancements to the user interface. Update'93 (the current update) focused on the statistical analysis of the data collected in the previous update and preparation of Version 3.4 of the prototype for limited distribution to facilitate further evaluation. The current prototype provides the capability for the user to generate CSD's from Ada PDL or source code in a reverse engineering as well as forward engineering mode with a level of flexibility suitable for practical application. An overview of the GRASP/Ada project with an emphasis on the current update is provided.

Cross, James H., II↗

DOE OSTI2021

MACCS (MELCOR Accident Consequence Code System) User Guide

The MELCOR Accident Consequence Code System (MACCS) is used by Nuclear Regulatory Commission (NRC) and various national and international organizations for probabilistic consequence analysis of nuclear power accidents. This User Guide is intended to assist analysts in understanding the MACCS/WinMACCS model and to provide information regarding the code. This user guide version describes MACCS Version 3.10.0. Features that have been added to MACCS in subsequent versions are described in separate documentation. This User Guide provides a brief description of the model history, explains how to set up and execute a problem, and informs the user of the definition of various input parameters and any constraints placed on those parameters. This report is part of a series of reports documenting MACCS. Other reports include the MACCS Theory Manual, MACCS Verification Report, Technical Bases for Consequence Analyses Using MACCS, as well as documentation for preprocessor codes including SecPop, MelMACCS, and COMIDA2. PAPERWORK REDUCTION ACT STATEMENT The NUREG does not contain information collection requirements and, therefore, is not subject to the requirements of the Paperwork Reduction Act of 1995 (44 USC 3501, et seq.). PUBLIC PROTECTION NOTIFICATION The NRC may not conduct or sponsor, and a person is not required to respond to, a request for information or an information collection requirement unless the requesting document displays a currently valid OMB control number. ACKNOWLEDGEMENTS Contributions to this User Guide were received from NRC and Sandia National Laboratories (SNL) project managers, technical experts, and code authors dedicated to the production of a valuable resource for the MACCS user community. Instructions and guidance included herein were developed over many years and include advancements in the code that provide users the ability to develop complex consequence modeling scenarios. WinMACCS and many of the early MACCS developments were due to vision of an earlier Project Manager, Jocelyn Mitchell. Jonathan Barr and AJ Nosek also contributed to the development of this report. The current NRC Project Manager, Salman Haq, provided the leadership to ensure this document was completed. Several other NRC and Sandia staff provided insights supporting development of the MACCS code and of this document.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

MACCS (MELCOR Accident Consequence Code System) User Guide -- Version 4.0

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

MACCS (MELCOR Accident Consequence Code System) User Guide Version 4.0, Revision 1

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Parsnip Parser Creation Application

Parsnip has three parts. The first part is the front-end user experience. The front end will be a graphical representation of the intermediate language. Once a user is satisfied with the information on the front end, Parsnip translates the data from the visual application into the second part of Parsnip - the intermediate language. More advanced users may skip the front end and generate their own intermediate language files. The final part is the backend which takes the intermediate language files and generates Zeek and Spicy code. Parsnip will not completely replace parser developers. Many protocols have unique challenges requiring manual effort; however, the goal of Parsnip is to automate at least 90% of the development that largely consists of repetitive tasks. Parsnip output will compile a functioning parser but may not include all PDU types or parse all data.

Huddleston, TimothyA.↗

DOE OSTI2021

RAVEN Theory Manual

RAVEN is a software framework able to perform parametric and stochastic analysis based on the response of complex system codes. The initial development was aimed at providing dynamic risk analysis capabilities to the thermohydraulic code RELAP-7, currently under development at Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose stochastic and uncertainty quantification platform, capable of communicating with any system code. In fact, the provided Application Programming Interfaces (APIs) allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by input files or via python interfaces. RAVEN is capable of investigating system response and explore input space using various sampling schemes such as Monte Carlo, grid, or Latin hypercube. However, RAVEN strength lies in its system feature discovery capabilities such as: constructing limit surfaces, separating regions of the input space leading to system failure, and using dynamic supervised learning techniques. The development of RAVEN started in 2012 when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework arose. RAVEN’s principal assignment is to provide the necessary software and algorithms in order to employ the concepts developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just to identify the frequency of an event potentially leading to a system failure, but the proximity (or lack thereof) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. peak pressure in a pipe) is exceeded under certain conditions. Most of the capabilities, implemented having RELAP-7 as a principal focus, are easily deployable to other system codes. For this reason, several side activates have been employed (e.g. RELAP5-3D, any MOOSE-based App, etc.) or are currently ongoing for coupling RAVEN with several different software. The aim of this document is to provide a set of commented examples that can help the user to become familiar with the RAVEN code usage.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

MELCOR Code Change History: Revision 18019 to 21402

This document summarily provides brief descriptions of the MELCOR code enhancement made between code revision number 18019and 21440. Revision 18019 represents the previous official code release; therefore, the modeling features described within this document are provided to assist users that update to the newest official MELCOR code release, 21440. Along with the newly updated MELCOR Users’ Guide [2] and Reference Manual [3], users are aware and able to assess the new capabilities for their modeling and analysis applications.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1979

Automatic color map digitization by spectral classification

A method of converting polygon map information into a digital form which does not require manual tracing of polygon edges is discussed. The maps must be in color-coded format with a unique color for each category in the map. Color scanning using a microdensitometer is employed and a three-channel color separation digital data set is generated. The digital data are then classified by using a Gaussian maximum likelihood classifier, and the resulting digitized map is evaluated. Very good agreement is observed between the classified and original map.

Chu, N. Y.↗

NASA NTRS1980

Small passenger car transmission test; Chevrolet LUV transmission

A 1978 Chevrolet LUV manual transmission tested per the applicable portions of a passenger car automatic transmission test code (SAE J65lb) which required drive performance, coast performance, and no load test conditions. Under these test conditions, the transmission attained maximum efficiencies in the upper ninety percent range for both drive performance tests and coast performance tests. The major results of this test (torque, speed, and efficiency curves) are presented. Graphs map the complete performance characteristics for the Chevrolet LUV transmission.

Bujold, M. P.↗

NASA NTRS1992

Let's go: Early universe 2. Primordial nucleosynthesis the computer way

This is a revised description and manual for the primordial nucleosynthesis program, NUC123, an updated and modified version of the code of R.V. Wagoner. NUC123 has undergone a number of changes, further enhancing its documentation and ease of use. Presented here is a guide to its use, followed by a series of appendices containing specific details such as a summary of the basic structure of the program, a description of the computational algorithm, and a presentation of the theory incorporated into the program.

Kawano, Lawrence↗

NASA NTRS2024

SMAnalytics Automated Shape Memory Test Analysis Software User's Manual: UCFTC, UPER, and DSC Test Methods, Version 1.0.2

Over the course of 60 years of shape memory alloy research and development, the properties of these alloys have been measured using various testing methods, which are often customized by the organization performing the test. However, commercial adoption of shape memory alloys in aeronautic actuator applications requires reducing property uncertainty through standardizing test methods. Historically, differential scanning calorimetry (DSC) has been used to measure transformation temperatures under stress-free conditions. This testing method is well established, and tests are run under the applicable standard, ASTM F2004-17: Standard Test Method for Transformation Temperature of Nickel-Titanium Alloys by Thermal Analysis. Two other test methods for measuring strains and transformation temperatures under constant load or free recovery after prestraining have only recently been standardized—ASTM E3097: Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of SMAs (UCFTC) and ASTM E3098: Standard Test Method for Mechanical Uniaxial Pre-Strain and Thermal Free Recovery of SMAs (UPFR). These standards represent a critical step forward in producing reliable material property data for the use of these alloys in aeronautics and other commercial areas. However, no standard programs or software packages were previously available for postprocessing UCFTC- and UPFR-type test data to extract property data. Each organization that performed the testing analyzed data using its own custom manual methods, such as using a plot and a straight edge, spreadsheet plotting methods, or custom code routines, to extract the required values for strains, stresses, and transformation temperatures. SMAnalytics represents the first publicly available uniform software package for processing data generated using the DSC, UCFTC, and UPFR test methods, as well as many modifications of these methods, including loading in martensite versus austenite and performing multiple thermal cycles at stress. In doing so, it provides a tool for reducing potential error or variability in the measured values due to the precision of the technique used and person-to-person variability. It is also expected that this automated data-parsing tool can accelerate the data analysis phase of the test campaign, especially for large data files. This User’s Manual describes how the SMAnalytics software works and the method for its use.

Shape Memory Alloy↗

NASA NTRS2008

A Grid Sourcing and Adaptation Study Using Unstructured Grids for Supersonic Boom Prediction

NASA created the Supersonics Project as part of the NASA Fundamental Aeronautics Program to advance technology that will make a supersonic flight over land viable. Computational flow solvers have lacked the ability to accurately predict sonic boom from the near to far field. The focus of this investigation was to establish gridding and adaptation techniques to predict near-to-mid-field (<10 body lengths below the aircraft) boom signatures at supersonic speeds using the USM3D unstructured grid flow solver. The study began by examining sources along the body the aircraft, far field sourcing and far field boundaries. The study then examined several techniques for grid adaptation. During the course of the study, volume sourcing was introduced as a new way to source grids using the grid generation code VGRID. Two different methods of using the volume sources were examined. The first method, based on manual insertion of the numerous volume sources, made great improvements in the prediction capability of USM3D for boom signatures. The second method (SSGRID), which uses an a priori adaptation approach to stretch and shear the original unstructured grid to align the grid and pressure waves, showed similar results with a more automated approach. Due to SSGRID s results and ease of use, the rest of the study focused on developing a best practice using SSGRID. The best practice created by this study for boom predictions using the CFD code USM3D involved: 1) creating a small cylindrical outer boundary either 1 or 2 body lengths in diameter (depending on how far below the aircraft the boom prediction is required), 2) using a single volume source under the aircraft, and 3) using SSGRID to stretch and shear the grid to the desired length.

Carter, Melissa B.↗

NASA NTRS2016

Automation of Flight Software Regression Testing

NASA is developing the Space Launch System (SLS) to be a heavy lift launch vehicle supporting human and scientific exploration beyond earth orbit. SLS will have a common core stage, an upper stage, and different permutations of boosters and fairings to perform various crewed or cargo missions. Marshall Space Flight Center (MSFC) is writing the Flight Software (FSW) that will operate the SLS launch vehicle. The FSW is developed in an incremental manner based on "Agile" software techniques. As the FSW is incrementally developed, testing the functionality of the code needs to be performed continually to ensure that the integrity of the software is maintained. Manually testing the functionality on an ever-growing set of requirements and features is not an efficient solution and therefore needs to be done automatically to ensure testing is comprehensive. To support test automation, a framework for a regression test harness has been developed and used on SLS FSW. The test harness provides a modular design approach that can compile or read in the required information specified by the developer of the test. The modularity provides independence between groups of tests and the ability to add and remove tests without disturbing others. This provides the SLS FSW team a time saving feature that is essential to meeting SLS Program technical and programmatic requirements. During development of SLS FSW, this technique has proved to be a useful tool to ensure all requirements have been tested, and that desired functionality is maintained, as changes occur. It also provides a mechanism for developers to check functionality of the code that they have developed. With this system, automation of regression testing is accomplished through a scheduling tool and/or commit hooks. Key advantages of this test harness capability includes execution support for multiple independent test cases, the ability for developers to specify precisely what they are testing and how, the ability to add automation, and the ability of the harness and cases to be executed continually. This test concept is an approach that can be adapted to support other projects.

Tashakkor, Scott B.↗

NASA NTRS1990

Calculation of Weibull strength parameters, Batdorf flaw density constants and related statistical quantities using PC-CARES

This manual describes the operation and theory of the PC-CARES (Personal Computer-Ceramic Analysis and Reliability Evaluation of Structures) computer program for the IBM PC and compatibles running PC-DOS/MS-DOR OR IBM/MS-OS/2 (version 1.1 or higher) operating systems. The primary purpose of this code is to estimate Weibull material strength parameters, the Batdorf crack density coefficient, and other related statistical quantities. Included in the manual is the description of the calculation of shape and scale parameters of the two-parameter Weibull distribution using the least-squares analysis and maximum likelihood methods for volume- and surface-flaw-induced fracture in ceramics with complete and censored samples. The methods for detecting outliers and for calculating the Kolmogorov-Smirnov and the Anderson-Darling goodness-of-fit statistics and 90 percent confidence bands about the Weibull line, as well as the techniques for calculating the Batdorf flaw-density constants are also described.

Szatmary, Steven A.↗

NASA NTRS1993

Software to model AXAF image quality

This draft final report describes the work performed under this delivery order from May 1992 through June 1993. The purpose of this contract was to enhance and develop an integrated optical performance modeling software for complex x-ray optical systems such as AXAF. The GRAZTRACE program developed by the MSFC Optical Systems Branch for modeling VETA-I was used as the starting baseline program. The original program was a large single file program and, therefore, could not be modified very efficiently. The original source code has been reorganized, and a 'Make Utility' has been written to update the original program. The new version of the source code consists of 36 small source files to make it easier for the code developer to manage and modify the program. A user library has also been built and a 'Makelib' utility has been furnished to update the library. With the user library, the users can easily access the GRAZTRACE source files and build a custom library. A user manual for the new version of GRAZTRACE has been compiled. The plotting capability for the 3-D point spread functions and contour plots has been provided in the GRAZTRACE using the graphics package DISPLAY. The Graphics emulator over the network has been set up for programming the graphics routine. The point spread function and the contour plot routines have also been modified to display the plot centroid, and to allow the user to specify the plot range, and the viewing angle options. A Command Mode version of GRAZTRACE has also been developed. More than 60 commands have been implemented in a Code-V like format. The functions covered in this version include data manipulation, performance evaluation, and inquiry and setting of internal parameters. The user manual for these commands has been formatted as in Code-V, showing the command syntax, synopsis, and options. An interactive on-line help system for the command mode has also been accomplished to allow the user to find valid commands, command syntax, and command function. A translation program has been written to convert FEA output from structural analysis to GRAZTRACE surface deformation file (.dfm file). The program can accept standard output files and list files from COSMOS/M and NASTRAN finite analysis programs. Some interactive options are also provided, such as Cartesian or cylindrical coordinate transformation, coordinate shift and scale, and axial length change. A computerized database for technical documents relating to the AXAF project has been established. Over 5000 technical documents have been entered into the master database. A user can now rapidly retrieve the desired documents relating to the AXAF project. The summary of the work performed under this contract is shown.

Ahmad, Anees↗

DOE OSTI2023

VERA Integration in the NEAMS Workbench

The Virtual Environment for Reactor Applications (VERA) is a cutting edge simulation code suite used to solve complex multiphysics problems for nuclear reactors. VERA makes use of high performance computing (HPC) systems to solve large problems that were not historically tractable. While extensive work has been put into the usability of VERA, it still takes significant effort to build reactor models, ensure their correctness, properly execute the calculations, and conduct the necessary analysis of the results. This difficulty is common for many complex codes such as VERA. As part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the NEAMS Workbench has been developed and maintained. The goal of the NEAMS Workbench is to provide a single interface with which to execute a wide variety of physics codes, from building the input models to analyzing the results. This document serves as a manual detailing the current integration of VERA with the NEAMS Workbench and a guide for configuring Workbench to allow remote execution of VERA.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1974

A users manual for a computer program which calculates time optical geocentric transfers using solar or nuclear electric and high thrust propulsion

This manual is a guide for using a computer program which calculates time optimal trajectories for high-and low-thrust geocentric transfers. Either SEP or NEP may be assumed and a one or two impulse, fixed total delta V, initial high thrust phase may be included. Also a single impulse of specified delta V may be included after the low thrust state. The low thrust phase utilizes equinoctial orbital elements to avoid the classical singularities and Kryloff-Boguliuboff averaging to help insure more rapid computation time. The program is written in FORTRAN 4 in double precision for use on an IBM 360 computer. The manual includes a description of the problem treated, input/output information, examples of runs, and source code listings.

Sackett, L. L.↗