Managing Sandia's Mission IT Software Portfolio through a Common Engineering Environment.
Abstract not provided.
Kuhlman, Philip S.↗
SEARCH · Search NASA
Results for “Mission manager software”
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.
Software Resilience using Kokkos Ecosystem
Due to the cost of hardware failures within mission critical and scientific applications, it is necessary for software to provide a mechanism to prevent or recover from interruptions. The Kokkos ecosystem is a programming environment that provides performance and portability to many applications that run on DOE supercomputers as well as smaller scale systems. These applications require a higher level of service due to the cost associated with each simulation or the critical nature of the mission. Software resilience enables an application of manage hardware failures reducing the cost of an interruption. Two different resilience methodologies have been added to the Kokkos ecosystem: checkpointing has been added for restart capabilities and a resilient execution model has been added to account for failures in compute devices. The design and implementation of each of these additions are described, and appropriate examples are included for end users.
97 MATHEMATICS AND COMPUTING↗
M-Star ® Software Test and Verification
Savannah River Mission Completion (SRMC) currently manages the risk for retained hydrogen in the Defense Waste Processing Facility (DWPF) vessels by implementing a Retained Hydrogen Program. The current program relies on Sludge Batch (SB) 8 Gas Chromatograph data and on conservative assumptions concerning gas release and retention to determine allowable vessel Quiescent time (Q-time). The authors identified M-Star ® CFD as a software that could simulate processes such as fluid flow, heat transfer, species transport, chemical reactions, particle transport, and retained hydrogen gas release. Preliminary simulation results suggest that more realistic assumptions on gas retention and release may be feasible for the DWPF retained hydrogen program. Because of the desire to use the M-Star ® software to perform analyses that support nuclear safety, SRMC has requested Savannah River National Laboratory (SRNL) to upgrade the software classification level of M-Star ® CFD from level D to level A to perform analyses that support nuclear safety.
08 HYDROGEN↗
ROS-DOE: Leveraging Open-Source Robotics Software for the DOE-EM Mission? - 17181
In order to establish a common software framework for its robotic systems, the United States Department of Energy - Environmental Management (DOE-EM) is considering the possibility of extending the Robot Operating System (ROS) open source robotics software to address the varied, complex challenges facing DOE-EM. The effort, preliminarily called ROS-DOE, would enhance the reliability, robustness, security, and user friendliness of ROS to meet the requirements of the nuclear waste remediation mission, and those of DOE as a whole. As envisioned, the ROS DOE program would also support rapid progress to mature cross-cutting capabilities including supervised autonomy, inter-operability with off-the-shelf industrial equipment, and physics-based robot simulation (i.e., Gazebo). This paper provides background context about the current state of ROS software and its supporting community, surveys DOE-EM needs and requirements for robotic solutions, and analyzes the gaps between the current state of ROS and those needed for DOE-EM robotics. It then identifies new capabilities that are recommended for ROS-DOE and outlines software development practices that could be leveraged to blend the best of the open-source world with high-reliability software development practices. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Evaluation of Data Catalog Software for Hanford Site Environmental Datasets
Environmental information and data underpin achievement of the U.S. Department of Energy (DOE) Office of Environmental Management (EM) mission at the Hanford Site. The Hanford Environmental Data Management (HEDM) Program is the DOE Richland Operations Office (RL) approach to develop and implement a formal program for managing environmental data and the associated records, materials, and systems at the Hanford Site. The current project, contract, organization, and contractor-specific efforts at managing environmental data sets are insufficient to provide orderly, long-term, site-wide access. A vital element to be created within the HEDM program plan is a catalog of data sources, called the Hanford Environmental Information and Data Index (HEIDI), that will enable long-term access and retrievability for the multiple independent sources of data that might otherwise be difficult to discover. This report compares leading open source and commercial data catalog platforms using criteria to assess the functionality needed to develop the HEIDI catalog of Hanford data sources that connects and exchanges data with established Hanford Local Area Network (HLAN) enterprise information technology systems. Proprietary platforms evaluated included ArcGIS Enterprise Sites, Junar, OpenDataSoft, and Socrata, and non-proprietary platforms included Energy Data eXchange (EDX), Comprehensive Knowledge Archive Network (CKAN), and DKAN (a Drupal-based open data portal based on CKAN). Capabilities supporting data discoverability, retrieval, and archival, as well as metadata standard requirements and integration into the HLAN were rated as either failing to meet requirements (F), meeting requirements (M), or exceeding requirements by delivering additional desired features (E). The lowest rating for any capability area was assigned as the overall rating for the platform. These findings enable DOE-RL and the contractors implementing the HEDM plan to focus on candidate tools likely to meet the requirements for implementing HEIDI. All of the platforms receiving an overall rating of ‘F’ were unable to be deployed on Hanford infrastructure or within dedicated cloud resources. A propriety software-as-a-service (SaaS) model of delivering a data catalog (e.g., found in software such as Junar and OpenDataSoft) favors consistency across customers at the expense of customization and configurable roles that are needed for Hanford work. Hosting data on a shared commercial platform places limits on dataset size (maximum of 240 Mb for OpenDataSoft), a significant limitation for HEIDI implementation. EDX, a government data catalog based on CKAN, received the ‘F’ rating due to an inability to incorporate authentication from HLAN into the system. Among platforms rated ‘M’ or ‘E’, only the Socrata platform had a SaaS delivery model. In contrast to other SaaS platforms, Socrata provided custom roles and gateways that allow local datasets to be incorporated into an online catalog. Socrata also complies with the Federal Risk and Authorization Management Program, a significant benefit for cloud-based management of Hanford data. The other platforms rated ‘M’ or ‘E’, ArcGIS Enterprise Sites, CKAN, and DKAN, provide fully self-hosted options, allowing for greater control and flexibility with the HEIDI catalog. These widely used tools have supportive communities of practice, extensive customization options, and demonstrated deployments that provide evidence that they can meet requirements, often deliver additional desired features, and work well with federal government systems. Completely customized alternatives built on a collection of applications were not evaluated because achieving similar performance to CKAN or DKAN requires substantial resources, especially in the absence of the active communities that have grown to support these tools. ArcGIS Enterprise Sites, Socrata, CKAN, and DKAN were evaluated as strong candidates for successful implementation with HEIDI.
54 ENVIRONMENTAL SCIENCES↗
OpenCHAMI Developer Summit [Slides]
The mission of the OpenCHAMI consortium is to steward the collaborative development and continuous evolution of cloud-like software to manage High Performance Computing capacity regardless of the size or deployment platform. We are guided by the operators and practitioners who use modern tooling and concepts to address the needs of classical HPC applications and the growing AI/ML and Data Science community that wish to leverage HPC capacity within their own workflows, to meet their needs with their own tools.
97 MATHEMATICS AND COMPUTING↗
Discrete-event Simulation Process Model for the Pyrochemical Processing of Plutonium at Los Alamos National Laboratory
The pyrochemical metal production operations that occur in the Plutonium Facility at Los Alamos National Laboratory perform plutonium purification with the aim to provide plutonium metal for a variety of defense- and non-defense missions within the National Nuclear Security Administration. The demands and constraints associated with the pyrochemical processing of plutonium are complex, making decision analyses challenging for program managers who require plutonium production for their mission applications. The construction of a discrete-event simulation process model is proposed to measure and report the process capacity, material throughput, equipment requirements, and dose accumulation for operators of the pyrochemical metal production operations. The process model, constructed in the ExtendSim™ software, will represent the cause-and-effect relationships between the pyrochemical processing environment and the process constraints, including criticality limitations, material control and accountability measures, chemical analysis requirements, and equipment availability. An accurate representation of the pyrochemical metal production process capacity through simulation modeling will be helpful to program managers in their efforts to forecast plutonium availability for mission applications. Furthermore, the proposed process model will be vital for future analyses that will measure the interactions between the pyrochemical metal production operations and the aqueous reprocessing operations and their ability to minimize transuranic waste disposal.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
FRMAC Laboratory Analysis RadResponder Gap Analysis and Web Portal Enhancements
The Federal Radiological Monitoring and Assessment Center (FRMAC) relies on accurate and defensible analytical laboratory data to support its mission. FRMAC Laboratory Analysis personnel are responsible for (1) receiving samples, (2) managing samples, and (3) providing data quality assurance. Currently, the RadResponder software application does not meet all these needs. With some modifications, RadResponder could meet the needs for sample receiving functions, but it does not meet the needs of sample management and data quality assurance functions. The FRMAC Laboratory Analysis team has discussed and reviewed the following options moving forward: Option 1: Make minor revisions to RadResponder to improve sample receiving capability, purchase and configure a commercial laboratory information management system (LIMS) to perform sample management and data quality assurance, and build an interface between RadResponder and the commercial-off-the-shelf LIMS. Option 2: Make major revisions to RadResponder for all FRMAC Laboratory Analysis functions to support required sample management and data quality assurance activities. Option 3: Create a custom-built LIMS system to interface with RadResponder. Note: All three options will require the development of a Laboratory Analysis web portal and will require funding for ongoing maintenance and training. The FRMAC Laboratory Analysis team highly recommends Option 1 as the best and most efficient path forward. Commercial-off-the-shelf LIMS products have been proven successful in the laboratory community for decades. Option 1 leverages these proven technologies and takes advantage of RadResponder's current strengths.
61 RADIATION PROTECTION AND DOSIMETRY↗
Hanford SMART System: Calculation of Radionuclide Emissions, Ambient Air Concentrations and Error Propagation (Final Report)
This document, authored by Radiological Assessment Corporation (RAC), details the calculations used to convert laboratory radiological analytical sample data and field measurement data for both ambient air samplers and stack air samples to concentration values with associated uncertainty. The RAC supported an effort by Mission Support Alliance (MSA) to replace the Automated Bar Coding of All Samples at Hanford (ABCASH) and Environmental Release Summary (ERS) database software with a commercial off-the-shelf (COTS) data management software system. The ABCASH and ERS databases were not compatible with the Hanford system standards Windows 10 Operating System deployed in calendar year 2018. The replacement software, Sample Management and Analytical Results Tracking (SMART), is used for environmental data collection, analyses, and regulatory reporting for the Hanford Environmental Surveillance and Effluent Monitoring programs.
54 ENVIRONMENTAL SCIENCES↗
Modular Subsurface Sensors and Integrated Software for Advanced Subsurface Characterization and Monitoring using Unoccupied Vehicles
The advent and subsequent proliferation of autonomous airborne, waterborne, and groundbased vehicles (i.e., “drones”) promises to broadly transform the geosciences and associated industries, including fossil energy exploration and development, mineral resource exploration and development, water-resource management, and environmental remediation. For geophysical characterization and monitoring, the prospect of programming highly repeatable and low-cost drone missions for subsurface imaging will allow for deployments in hazardous and previously inaccessible areas. Coupled with autonomous workflows for data processing, management, and visualization, drone-based geophysical characterization and monitoring will enable unprecedented, real-time insight into diverse subsurface properties and processes of scientific and engineering importance. Toward this end, the objectives of this Lab Directed Research and Development (LDRD) project were to develop new (1) instrumentation for dronebased electromagnetic induction (EMI) geophysical imaging, including separated transmitter and receivers and associated electronics, (2) software for real-time data telemetry, processing, management, and visualization. Although EMI has been previously deployed using unoccupied aerial systems (UASs), these applications failed to capitalize on the game-changing capabilities of drone platforms. Whereas drone-based data acquisition allows for collection of rich, three-dimensional (3D) multi-offset/multi-angle configurations between transmitters and receivers, past efforts have relied on conventional instrumentation that was designed for ground-based data collection with the transmitter and a single receiver housed in the same unit; nor did these previous applications demonstrate real-time delivery of results to support rapid management decisions in the field. In this 1-year project, we (1) designed and constructed new lightweight independent transmitter and receiver antenna platforms that communicate with a laptop computer; (2) developed software to control data acquisition, manage/transfer data, and visualize data as its collected; and (3) demonstrated the operation of the new hardware and software systems in a ground-based field test. Our work entails major technological advances for EMI and established a foundation on which to build a new drone-based, real-time geophysical EMI imaging capability to support diverse challenges facing the nation.
47 OTHER INSTRUMENTATION↗
Biosecurity Risk Assessment Methodology (BioRAM) v. 2.0
Sandia National Laboratories International Biological Threat Reduction Dept (SNL/IBTR) has an ongoing mission to enhance biosecurity assessment methodologies, tools, and guise. These will aid labs seeking to implement biosecurity as advocated in the recently released WHO's Biorisk Management: Lab Biosecurity Guidance. BioRAM 2.0 is the software tool developed initially using the SNL LDRD process and designed to complement the "Laboratory Biosecurity Risk Handbook" written by Ren Salerno and Jennifer Gaudioso defining biosecurity risk assessment methodologies.
Caskey, Susan↗
FY 2021 Mid-Year HPC Utilization Report M3UF-21IN0701018
Idaho National Laboratory (INL), supported by the Department of Energy Office of Nuclear Energy (DOE-NE) through the Nuclear Science User Facilities, provides access to supercomputer systems and data storage along with support staff for system management, software installation, cybersecurity and user support to the broader DOE-NE user community. Users include individuals at universities, industry, and government laboratories enabling a wide range of research and development and mission-supporting activities. The availability of high-performance computing (HPC) capabilities is a key foundation of collaboration and innovation in nuclear energy systems research. HPC resources and INL directly support the mission and objectives of DOE-NE. From October 2020 through March 2021, INL HPC capabilities were utilized by a diverse set of computing and applied researchers, for a wide range of research and engineering activities. This report focuses on current INL HPC systems and utilization from October 1, 2020 through March 31, 2021.
99 GENERAL AND MISCELLANEOUS↗
Microcontroller-based aerosol jet printer control software
This software is used with a microcontroller to control an aerosol jet printing system. It was written for a 32-bit ARM microcontroller, providing greater processing speed and complexity relative to more conventional low-cost printer controllers. The microcontroller software was written using a real-time operating system (FreeRTOS), which simplifies parallel operation of multiple functions and further customization. It supports simultaneous motion planning, pulse generation for stepper motors, reading encoder feedback, communicating with multiple mass flow controllers, controlling solid state relays, handling a software-based emergency stop, and sending data to the client PC. The program is written in C and communicates with the client PC via USB connection. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-0436 O
Secor, EthanBenjamin↗
In Recognition of Sandia's SCRM Program, Delivering Over 500 Subcontractor Risk Assessments in 2018
The globalization of modern supply chains has resulted in many new risks to Sandia's NW programs and mission. The potential impact of counterfeit products, tampering, theft, malicious software, poor manufacturing and/or development practices, and the influence of foreign governments has become more obvious as new threats and compromises continuously emerge. The Supply Chain Risk Management (SCRM) team was formed specifically to understand and address these risks. We were able to coalesce around these principles to develop and optimize an effective risk assessment process for critical suppliers, called Subcontractor Risk Assessments (SRAs). These elevated screening techniques are planned and delivered in a cost-effective way for Sandia's programs (no increase to purchasing burden rates) and also demonstrate due diligence to DOE/NNSA as a component of Sandia's overall SCRM strategy. SRAs are communicated in a concise 1-page format complete with recommendations as well as links to reference materials for those who require additional details about the SRA process and results.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Improving Efficiency of DWPF Operations via Automating Process Calculations and Vitrifying High-Curie Feed- 24529
The Liquid Waste Organization (LWO) at the Savannah River Site (SRS) uses a “Power As One®” motto to process and dispose of radioactive waste. The Defense Waste and Processing Facility (DWPF) treats the high-level waste through a process of vitrification. The DWPF receives three incoming waste streams that are added to the Sludge Receipt and Adjustment Tank (SRAT): sludge, Monosodium Titanate/Sludge Solids (MST/SS), and Strip Effluent (SE). The liquid waste is mixed with pre-fabricated frit and treated with high temperatures in the melter prior to being poured into stainless steel canisters. The liquid cools to form solid glass within these canisters that are suitable for long-term storage and disposal. Savannah River Mission Completion (SRMC), the SRS liquid waste contractor for the U.S. Department of Energy, has implemented several facility improvements to further enhance the operations to support the Liquid Waste Operation (LWO) mission. Two of these operational enhancements include implementing the electronic Material Tracking Program Calculator (eMTPC)software and increasing the DWPF canister heat rate limit.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Basic Energy Sciences Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Basic Energy Sciences, November 3-5, 2015, Rockville, Maryland
Computers have revolutionized every aspect of our lives. Yet in science, the most tantalizing applications of computing lie just beyond our reach. The current quest to build an exascale computer with one thousand times the capability of today’s fastest machines (and more than a million times that of a laptop) will take researchers over the next horizon. The field of materials, chemical reactions, and compounds is inherently complex. Imagine millions of new materials with new functionalities waiting to be discovered — while researchers also seek to extend those materials that are known to a dizzying number of new forms. We could translate massive amounts of data from high precision experiments into new understanding through data mining and analysis. We could have at our disposal the ability to predict the properties of these materials, to follow their transformations during reactions on an atom-by-atom basis, and to discover completely new chemical pathways or physical states of matter. Extending these predictions from the nanoscale to the mesoscale, from the ultrafast world of reactions to long-time simulations to predict the lifetime performance of materials, and to the discovery of new materials and processes will have a profound impact on energy technology. In addition, discovery of new materials is vital to move computing beyond Moore’s law. To realize this vision, more than hardware is needed. New algorithms to take advantage of the increase in computing power, new programming paradigms, and new ways of mining massive data sets are needed as well. This report summarizes the opportunities and the requisite computing ecosystem needed to realize the potential before us. In addition to pursuing new and more complete physical models and theoretical frameworks, this review found that the following broadly grouped areas relevant to the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR) would directly affect the Basic Energy Sciences (BES) mission need. Simulation, visualization, and data analysis are crucial for advances in energy science and technology. Revolutionary mathematical, software, and algorithm developments are required in all areas of BES science to take advantage of exascale computing architectures and to meet data analysis, management, and workflow needs. In partnership with ASCR, BES has an emerging and pressing need to develop new and disruptive capabilities in data science. More capable and larger high-performance computing (HPC) and data ecosystems are required to support priority research in BES. Continued success in BES research requires developing the next-generation workforce through education and training and by providing sustained career opportunities.
97 MATHEMATICS AND COMPUTING↗
Integrating quantum computing resources into scientific HPC ecosystems
Quantum Computing (QC) offers significant potential to enhance scientific discovery in fields such as quantum chemistry, optimization, and artificial intelligence. Yet QC faces challenges due to the noisy intermediate-scale quantum era’s inherent external noise issues. Here, this paper discusses the integration of QC as a computational accelerator within classical scientific high-performance computing (HPC) systems. By leveraging a broad spectrum of simulators and hardware technologies, we propose a hardware-agnostic framework for augmenting classical HPC with QC capabilities. Drawing on the HPC expertise of the Oak Ridge National Laboratory (ORNL) and the HPC lifecycle management of the Department of Energy (DOE), our approach focuses on the strategic incorporation of QC capabilities and acceleration into existing scientific HPC workflows. This includes detailed analyses, benchmarks, and code optimization driven by the needs of the DOE and ORNL missions. Our comprehensive framework integrates hardware, software, workflows, and user interfaces to foster a synergistic environment for quantum and classical computing research. This paper outlines plans to unlock new computational possibilities, driving forward scientific inquiry and innovation in a wide array of research domains.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Automating Testing of DUNE Electronics via a Finite State Machine
The Deep Underground Neutrino Experiment (DUNE) is a flagship international collaboration designed to study neutrinos—tiny, nearly massless particles that may hold answers to fundamental questions about the Universe. Fermilab’s Robotic Test Stand (RTS) plays a critical role in ensuring the quality of approximately 50,000 Application-Specific Integrated Circuit (ASIC) chips that will be used in DUNE’s massive liquid argon detectors. These electronics will be inside the cryostat; therefore, they will need to have a high yield of working chips and low noise. To improve the automation and reliability of the RTS, this project focused on designing and implementing a Python-based finite state machine (FSM) to manage chip handling workflows. The FSM was developed as a modular software framework to coordinate robotic arm movements, manage chip tray positions, and monitor system states during testing. Key features include robust error handling routines, a pause/resume system for safe mid-cycle interruptions, and a simulation mode for iterative testing without hardware dependencies. The system was designed to prepare for seamless integration with RTS hardware components such as the robotic arm and vision system. This integration will streamline collaboration and enable efficient deployment of updates across the six institutions performing testing. The outcomes of this internship contribute to Fermilab’s mission to advance high-energy physics and support the DOE’s national goals by directly improving the testing of equipment to be used in DUNE. The project also provided valuable experience in software design and contributing to the success of DUNE.
Kang, Caleb [Fermilab]↗