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DOE OSTI2022

SIERRA/Aero User Manual - Version 5.8

SIERRA/Aero is a compressible fluid dynamics program intended to solve a wide variety compressible fluid flows including transonic and hypersonic problems. This document describes the commands for assembling a fluid model for analysis with this module, henceforth referred to simply as Aero for brevity. Aero is an application developed using the SIERRA Toolkit (STK). The intent of STK is to provide a set of tools for handling common tasks that programmers encounter when developing a code for numerical simulation. For example, components of STK provide field allocation and management, and parallel input/output of field and mesh data. These services also allow the development of coupled mechanics analysis software for a massively parallel computing environment. In the definitions of the commands that follow, the term Real_Max denotes the largest floating point value that can be represented on a given computer. Int_Max is the largest such integer value.

42 ENGINEERING↗

DOE OSTI2022

SIERRA/Aero Theory Manual - Version 5.8

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

SIERRA/Aero User Manual (V.5.10)

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

SIERRA/Aero Theory Manual - V.5.10

42 ENGINEERING↗

NASA NTRS1972

The development of hurricane Inez, 1966, as shown by satellite nighttime radiometric and daytime television coverage

A complete documentation of Numbus 2 High Resolution infrared Radiometer data and ESSA-1 and 3 television photographs is presented for the life-time of Hurricane Inez, 1966. Ten computer produced radiation charts were analyzed in order to delineate the three dimensional cloud structure during the formative, mature and dissipating stages of this tropical cyclone. Time sections were drawn throughout the storm's life cycle to relate the warm core development and upper level outflow of the storm with their respective cloud canopies, as shown by the radiation data. Aerial reconnaissance weather reports, radar photographs and conventional weather analyses were used to complement the satellite data. A computer program was utilized to accept Nimbus 2 HRIR equivalent blackbody temperatures within historical maximum and minimum sea surface temperature limits over the tropical Atlantic Ocean.

Allison, L. J.↗

NASA NTRS1990

AEOSS design guide for system analysis on Advanced Earth-Orbital Spacecraft Systems

Advanced Earth Orbital Spacecraft System (AEOSS) enables users to project the requried power, weight, and cost for a generic earth-orbital spacecraft system. These variables are calculated on the component and subsystem levels, and then the system level. The included six subsystems are electric power, thermal control, structure, auxillary propulsion, attitude control, and communication, command, and data handling. The costs are computed using statistically determined models that were derived from the flown spacecraft in the past and were categorized into classes according to their functions and structural complexity. Selected design and performance analyses for essential components and subsystems are also provided. AEOSS has the feature permitting a user to enter known values of these parameters, totally and partially, at all levels. All information is of vital importance to project managers of subsystems or a spacecraft system. AEOSS is a specially tailored software coded from the relational database program of the Acius; 4th Dimension with a Macintosh version. Because of the licensing agreement, two versions of the AEOSS documents were prepared. This version AEOSS Design Guide, is for users to exploit the full capacity of the 4th Dimension. It is for a user who wants to alter or expand the program structures, the program statements, and the program procedures. The user has to possess a 4th Dimension first.

Lee, Hwa-Ping↗

NASA NTRS1990

AEOSS runtime manual for system analysis on Advanced Earth-Orbital Spacecraft Systems

Advanced earth orbital spacecraft system (AEOSS) enables users to project the required power, weight, and cost for a generic earth-orbital spacecraft system. These variables are calculated on the component and subsystem levels, and then the system level. The included six subsystems are electric power, thermal control, structure, auxiliary propulsion, attitude control, and communication, command, and data handling. The costs are computed using statistically determined models that were derived from the flown spacecraft in the past and were categorized into classes according to their functions and structural complexity. Selected design and performance analyses for essential components and subsystems are also provided. AEOSS has the feature permitting a user to enter known values of these parameters, totally and partially, at all levels. All information is of vital importance to project managers of subsystems or a spacecraft system. AEOSS is a specially tailored software coded from the relational database program of the Acius' 4th Dimension with a Macintosh version. Because of the licensing agreements, two versions of the AEOSS documents were prepared. This version, AEOSS Runtime Manual, is permitted to be distributed with a finite number of the restrictive 4D Runtime version. It can perform all contained applications without any programming alterations.

Lee, Hwa-Ping↗

DOE OSTI2021

Simulation Dataset - Input files

The input data that are required to run the model are divided into fundamental data and advanced data. The fundamental data are essential to run the model, while the advanced data allow optional model features to be activated. The names of all input data files are to be entered as ASCII characters in a tabular format. Spaces, commas, or tabs can separate numeric fields, the use of any other special visible or hidden characters must be avoided. It may be useful to note that all files are generally read in using standard free-format style FORTRAN READ statements. The input data files can be generated/modified using any standard editor, spreadsheet or word processor (in non-document mode), given that the above guidelines are complied with. However, the inclusion of special formatting characters and the insertion of blank lines must be avoided. The input data files may also be generated through the use of special purpose translation programs that convert the input data files that were initially generated for another traffic simulation or transportation planning model into an INTEGRATION format.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Rattlesnake User's Manual

Rattlesnake is a combined-environments, multiple input/multiple output control system for dynamic excitation of structures under test. It provides capabilities to control multiple responses on the part using multiple exciters using various control strategies. Rattlesnake is written in the Python programming language to facilitate multiple input/multiple output vibration research by allowing users to prescribe custom control laws to the controller. Rattlesnake can target multiple hardware devices, or even perform synthetic control to simulate a test virtually. Rattlesnake has been used to execute control problems with up to 200 response channels and 12 drives. This document describes the functionality, architecture, and usage of the Rattlesnake controller to perform combined environments testing.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Towards a Benchmark Experiment with the Compact Nuclear Power Source

The Compact Nuclear Power Source (CNPS) was a high-assay low enriched uranium (HALEU) tristructural isotropic (TRISO)-fueled, graphite-moderated microreactor constructed in 1987 at Los Alamos National Laboratory. The reactor, conceived as a power source for short-range radar stations, was designed to be "walk-away safe," and was cooled by heat pipes and ambient air. Though the project was formally cancelled after the fuel and moderator material had been received, its potential to meaningfully advance the body of critical and integral data was evident, and critical experiments with a mock-up of the reactor proceeded at TA-18 until its disassembly in 1991. The reflector and some components of the core would later go on to see service as part of the New Production Reactor Modular High-Temperature Gas-Cooled Reactor (NP-MHTGR) critical experiments. In light of the progress made by groups like Westinghouse and X-Energy towards contemporary graphite-moderated microreactors, the system remains an attractive candidate for the basis of a benchmark experiment even today. Uncertainties remain, however, in some features of the system–inconsistencies in the dimensions and composition of the reactor’s components as described in literature and implemented in current computational models. The identification, quantification, and to the extent possible, the minimization of these uncertainties is a crucial task on the path towards creating a benchmark based on the CNPS system. The present work seeks to initiate this process with a survey of available documentation and improvements to the accuracy of CNPS neutronics models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

2011.2 Revision of the Evaluated Nuclear Data Library (ENDL2011.2)

LLNL's Computational Nuclear Physics Group and Nuclear Theory and Modeling Group have col- laborated to create the 2011.2 revised release of the Evaluated Nuclear Data Library (ENDL2011.2). ENDL2011.2 is designed to support LLNL's current and future nuclear data needs and will be em- ployed in nuclear reactor, nuclear security and stockpile stewardship simulations with ASC codes. This database is currently the most complete nuclear database for Monte Carlo and deterministic transport of neutrons and charged particles. This library was assembled with strong support from the ASC PEM and Attribution programs, leveraged with support from Campaign 4 and the DOE/O ce of Science's US Nuclear Data Program. This document lists the revisions made in ENDL2011.2 compared with the data existing in the original ENDL2011.0 release and the ENDL2011.1-rc4 re- lease candidate of April 2015. These changes are made in parallel with some similar revisions for ENDL2009.2.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Software Quality Assurance for the MOOSE-Based Open-Source Multiphysics Code Cardinal - An Expanded CI Testing Suite

Cardinal is a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and the Monte Carlo particle transport code OpenMC within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Cardinal provides high-resolution thermal-hydraulics and/or radiation transport feedback to MOOSE multiphysics simulations. Multiphysics feedback is implemented in a geometry-agnostic manner which eliminates the need for rigid one-to-one mappings. A generic data transfer implementation also allows NekRS and OpenMC to couple to any MOOSE application, enabling a broad set of multiphysics capabilities. Cardinal simulations can also leverage combinations of MPI, OpenMP, and GPU resources. Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on developing, enhancing and, maintaining Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework and SQA program. To facilitate compliance with SQA standards, the Cardinal SQA Program has been initiated during Fiscal Year 2023 (FY23). During the development of the Cardinal SQA Program, multiple gaps have been identified. These gaps are primarily related to model verification and code pedigree as they relate to the use of Cardinal as a safety analysis tool. These gaps have been captured in a report published in 2023. A second report highlighted the progress made during Fiscal Year 2024 (FY24) and described Argonne’s effort to document and integrate software verification within Cardinal’s software development process. This report documents a snapshot of the verification test cases currently available for Cardinal and NekRS in their assimilation into a Continuous Integration (CI) platform. Following the CI practice permits the integrating of source code changes frequently and ensuring that the integrated codebase clears the verification testing for the software. It should be noted that the SQA program itself, including the program plans, procedures, configuration management, and testing strategies, need to be developed in a future step of this task.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

COTS Data Analytics Software User Manual: Version 1.0

Large volumes of data are being collected by Sandia National Laboratories as part of an active commercial-off-the-shelf (COTS) part testing and surveillance program. This user manual documents Python-based COTS Data Analytics software that has been developed for standardizing, displaying, visualizing, and analyzing the resulting COTS part testing and surveillance data. It is the objective of these software tools to streamline the analysis of COTS testing and surveillance data and improve the efficiency with which test engineers and data analytics experts can pinpoint possible performance and reliability problems in COTS parts.

42 ENGINEERING↗

DOE OSTI2024

Rattlesnake User's Manual (V.3)

Rattlesnake is a combined-environments, multiple input/multiple output control system for dynamic excitation of structures under test. It provides capabilities to control multiple responses on the part using multiple exciters using various control strategies. Rattlesnake is written in the Python programming language to facilitate multiple input/multiple output vibration research by allowing users to prescribe custom control laws to the controller. Rattlesnake can target multiple hardware devices, or even perform synthetic control to simulate a test virtually. Rattlesnake has been used to execute control problems with up to 200 response channels and 24 shaker drives. This document describes the functionality, architecture, and usage of the Rattlesnake controller to perform combined environments testing.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Executive Summary for the DOE Genesis Mission AI-Assisted Conceptual Development of a Pre-Geometric Cosmological Framework

This document provides a concise overview of a research program developed in support of the DOE Genesis Mission, illustrating how a modern semantic AI system can accelerate conceptual exploration in fundamental physics. The work summarized here accompanies three Fermilab Technical Notes that present a speculative—yet rigorously structured—framework for a pre-geometric cosmology emerging from a finite spectral substrate.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2002

1999 NCCS Highlights

The NASA Center for Computational Sciences (NCCS) is a high-performance scientific computing facility operated, maintained and managed by the Earth and Space Data Computing Division (ESDCD) of NASA Goddard Space Flight Center's (GSFC) Earth Sciences Directorate. The mission of the NCCS is to advance leading-edge science by providing the best people, computers, and data storage systems to NASA's Earth and space sciences programs and those of other U.S. Government agencies, universities, and private institutions. Among the many computationally demanding Earth science research efforts supported by the NCCS in Fiscal Year 1999 (FY99) are the NASA Seasonal-to-Interannual Prediction Project, the NASA Search and Rescue Mission, Earth gravitational model development efforts, the National Weather Service's North American Observing System program, Data Assimilation Office studies, a NASA-sponsored project at the Center for Ocean-Land-Atmosphere Studies, a NASA-sponsored microgravity project conducted by researchers at the City University of New York and the University of Pennsylvania, the completion of a satellite-derived global climate data set, simulations of a new geodynamo model, and studies of Earth's torque. This document presents highlights of these research efforts and an overview of the NCCS, its facilities, and its people.

Bennett, Jerome↗

DOE OSTI2017

GridAPPS-D Conceptual Design (V.1.0)

The purpose of this document is to provide a conceptual design of the distribution system application development platform being developed for the U.S. Department of Energy’s Advanced Distribution Management System (ADMS) Program by the Grid Modernization Laboratory Consortium project GM0063. The platform will be referred to as GridAPPS-D. This document provides a high level, conceptual view of the platform and provides related background and contextual information. This document is intended to both educate readers about the technical work of the project and to serve as a point of reference for the project team. The document will be updated as the project progresses.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2006

Algorithms for Maneuvering Spacecraft Around Small Bodies

A document describes mathematical derivations and applications of autonomous guidance algorithms for maneuvering spacecraft in the vicinities of small astronomical bodies like comets or asteroids. These algorithms compute fuel- or energy-optimal trajectories for typical maneuvers by solving the associated optimal-control problems with relevant control and state constraints. In the derivations, these problems are converted from their original continuous (infinite-dimensional) forms to finite-dimensional forms through (1) discretization of the time axis and (2) spectral discretization of control inputs via a finite number of Chebyshev basis functions. In these doubly discretized problems, the Chebyshev coefficients are the variables. These problems are, variously, either convex programming problems or programming problems that can be convexified. The resulting discrete problems are convex parameter-optimization problems; this is desirable because one can take advantage of very efficient and robust algorithms that have been developed previously and are well established for solving such problems. These algorithms are fast, do not require initial guesses, and always converge to global optima. Following the derivations, the algorithms are demonstrated by applying them to numerical examples of flyby, descent-to-hover, and ascent-from-hover maneuvers.

Acikmese, A. Bechet↗