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.
smwflow imports and exports Cray system management configurations to and from git repositories. smwflow implements both the mechanism for this and, in combination with git, implements a systems engineering workflow that can be used to manage multiple systems, enable rational implementation of features, and add traceability to systems management activities.
The One System Integrated Project Team (IPT) was formed in late 2011 as a way for improving the efficiency of delivery and treatment of highly radioactive waste stored in underground tanks at the U.S. Department of Energy's (DOE's) 586-square-mile Hanford Site in southeastern Washington State. The purpose of the One System IPT is to improve coordination and integration between the Hanford's Waste Treatment Plant (WTP) contractor and the Tank Operations Contractor (TOC). The vision statement is: One System is a WTP and TOC safety conscious team that, through integrated management and implementation of risk-informed decision and mission-based solutions, will enable the earliest start of safe and efficient treatment of Hanford's tank waste, to protect the Columbia River, environment and public. The IPT is a formal collaboration between Bechtel National, Inc. (BNI), which manages design and construction of the WTP for the U.S. Department of Energy's Office of River Protection (DOEORP), and Washington River Protection Solutions (WRPS), which manages the TOC for ORP. More than fifty-six (56) million gallons of highly radioactive liquid waste are stored in one hundred seventy-seven (177) aging, underground tanks. Most of Hanford's waste tanks - one hundred forty-nine (149) of them - are of an old single-shell tank (SST) design built between 1944 and 1964. More than sixty (60) of these tanks have leaked in the past, releasing an estimated one million gallons of waste into the soil and threatening the nearby Columbia River. There are another twenty-eight (28) new double-shelled tanks (DSTs), built from 1968 to 1986, that provide greater protection to the environment. In 1989, DOE, the U.S. Environmental Protection Agency (EPA), and the Washington State Department of Ecology (Ecology) signed a landmark agreement that required Hanford to comply with federal and state environmental standards. It also paved the way for agreements that set deadlines for retrieving the tank wastes and for building and operating the WTP. The tank wastes are the result of Hanford's nearly fifty (50) years of plutonium production. In the intervening years, waste characteristics have been increasingly better understood. However, waste characteristics that are uncertain and will remain as such represent a significant technical challenge in terms of retrieval, transport, and treatment, as well as for design and construction ofWTP. What also is clear is that the longer the waste remains in the tanks, the greater the risk to the environment and the people of the Pacific Northwest. The goal of both projects - tank operations and waste treatment - is to diminish the risks posed by the waste in the tanks at the earliest possible date. About two hundred (200) WTP and TOC employees comprise the IPT. Individual work groups within One System include Technical, Project Integration & Controls, Front-End Design & Project Definition, Commissioning, Nuclear Safety & Engineering Systems Integration, and Environmental Safety and Health and Quality Assurance (ESH&QA). Additional functions and team members will be added as the WTP approaches the operational phase. The team has undertaken several initiatives since its formation to collaborate on issues: (1) alternate scenarios for delivery of wastes from the tank farms to WTP; (2) improvements in managing Interface Control Documents; (3) coordination on various technical issues, including the Defense Nuclear Facilities Nuclear Safety Board's Recommendation 2010-2; (4) deployment of the SmartPlant Foundation-configuration Management System; and (5) preparation of the joint contract deliverable of the Operational Readiness Support Plan.
In the past decade software has grown significantly in complexity and scale. Likewise the number of dependencies for most software has increased with typical software packages depending on tens to hundreds of other packages. Such large numbers of dependencies place a significant burden on package managers to correctly maintain dependency lists and constraints between them. Due to this package managers have incorporated sophisticated tooling such as SAT solvers into their dependency management mechanisms. Despite these tools package managers still rely on many human annotated constraints for dependency and version selection. These are error-prone and require a significant amount of labor to constantly update and test. In this paper we propose a methodology to make use of historical build results in selecting the version for package dependencies. Our method utilizes the flexibility of the Spack package manager’s heavily parameterized package configurations to incorporate a machine learning model trained to predict the probability of build outcomes. This work is able to build and install packages with a 13% higher success rate than the default version selection mechanism in Spack.
The One System Integrated Project Team (IPT) was formed in late 2011 as a way for improving the efficiency of delivery and treatment of highly radioactive waste stored in underground tanks at the U.S. Department of Energy's (DOE's) 586-square-mile Hanford Site in southeastern Washington State. The purpose of the One System IPT is to improve coordination and integration between the Hanford's Waste Treatment Plant (WTP) contractor and the Tank Operations Contractor (TOC). The vision statement is: One System is a WTP and TOC safety-conscious team that, through integrated management and implementation of risk-informed decision and mission-based solutions, will enable the earliest start of safe and efficient treatment of Hanford's tank waste, to protect the Columbia River, environment and public. The IPT is a formal collaboration between Bechtel National, Inc. (BNI), which manages design and construction of the WTP for the U.S. Department of Energy's Office of River Protection (DOEORP), and Washington River Protection Solutions (WRPS), which manages the TOC for ORP. More than fifty-six (56) million gallons of highly radioactive liquid waste are stored in one hundred seventy-seven (177) aging, underground tanks. Most of Hanford's waste tanks - one hundred forty-nine (149) of them - are of an old single-shell tank (SST) design built between 1944 and 1964. More than sixty (60) of these tanks have leaked in the past, releasing an estimated one million gallons of waste into the soil and threatening the nearby Columbia River. There are another twenty-eight (28) new double-shelled tanks (DSTs), built from 1968 to 1986, that provide greater protection to the environment. In 1989, DOE, the U.S. Environmental Protection Agency (EPA), and the Washington State Department of Ecology (Ecology) signed a landmark agreement that required Hanford to comply with federal and state environmental standards. It also paved the way for agreements that set deadlines for retrieving the tank wastes and for building and operating the WTP. The tank wastes are the result of Hanford's nearly fifty (50) years of plutonium production. In the intervening years, waste characteristics have been increasingly better understood. However, waste characteristics that are uncertain and will remain as such represent a significant technical challenge in terms of retrieval, transport, and treatment, as well as for design and construction of WTP. What also is clear is that the longer the waste remains in the tanks, the greater the risk to the environment and the people of the Pacific Northwest. The goal of both projects - tank operations and waste treatment - is to diminish the risks posed by the waste in the tanks at the earliest possible date. About two hundred (200) WTP and TOC employees comprise the IPT. Individual work groups within One System include Technical, Project Integration and Controls, Front-End Design and Project Definition, Commissioning, Nuclear Safety and Engineering Systems Integration, and Environmental Safety and Health and Quality Assurance (ESH and QA). Additional functions and team members will be added as the WTP approaches the operational phase. The team has undertaken several initiatives since its formation to collaborate on issues: (1) alternate scenarios for delivery of wastes from the tank farms to WTP; (2) improvements in managing Interface Control Documents; (3) coordination on various technical issues, including the Defense Nuclear Facilities Nuclear Safety Board's Recommendation 2010-2; (4) deployment of the SmartPlant{sup R} Foundation-Configuration Management System; and (5) preparation of the joint contract deliverable of the Operational Readiness Support Plan. (authors)
Axonius, a cybersecurity asset management tool used at INL, provides visibility into users, devices, software, and hardware in use at the lab. This visibility, provided by aggregating data on lab entities from many tools' perspectives, makes incident response, configuration management, and IT operations more capable.
In this work, utilization of Natural gas and Hydrogen to support current and future building energy needs to offset the total electric demand while improving the grid resiliency and energy efficiency was investigated. Demand side energy management will play an important role in efficiently managing the available energy resources. Performance assessment of different power generation and energy management configurations is presented in this paper. Development of solutions in addressing grid resiliency by providing the ability to design suitable configurations for meeting individual building energy needs is discussed. Primary movers (PM) such as internal combustion engines (ICE) and fuel cells (FC) along with small scale auxiliary renewable energy source such as photovoltaics (PV) were considered. Key attributes of total carbon foot-print, life cycle costs including capital and operational expenditure, electric grid offset or peak shaving capability, thermal energy availability and its further potential to offset total electric demand, and primary energy intensity are analyzed and discussed in detail.
Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world’s energy demands and build energy security.
Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world?s energy demands and build energy security.
Savannah River Remediation (SRR) developed a new software application, Safety Requirement Management System (SRMS), to improve Documented Safety Analysis (DSA) safety requirement implementation in the Savannah River Site's Liquid Waste facilities. Technical Safety Requirement (TSR) Limited Conditions of Operations (LCOs) and related surveillances were previously tracked using four different applications. Due to their differences and their age, the applications introduced a number of operational challenges and vulnerabilities, including outdated platforms, usage demands beyond original design, and different organizational work processes. SRMS was developed to resolve these issues by using a single web-based approach that provides consistency, wider accessibility, simpler maintenance, and a platform for additional functionality. Other SRS facilities are evaluating the application for its applicability as a standard practice across the site. The new SRMS application decreased the administrative overhead for application maintenance, provided the needed TSR change management functionality, and reduced error precursors with the following advantages: - Consistent process/application across all SRR facilities - More efficient way to track and communicate compliance with DSA time-related requirements (i.e., TSR LCOs and surveillances). - Web-based search capability for LCO entries/exits and a record of surveillance performances. - TSR change management and independent reviews through electronic approvals. For example, the application provides the ability to bundle and stage LCO and surveillance changes associated with a TSR revision. The approval process involves multiple roles from the facility to ensure validity. - Formal configuration management program, fully supported by software life cycle documents. SRMS was implemented at Defense Waste Processing Facility (DWPF) in June 2017, with implementation in all Liquid Waste facilities expected by the end of 2017. Next, SRR plans to expand SRMS functionality to include a linking document database (LDD) to support the DSA requirements. (authors)
This document is the distribution integrity management plan (Plan) for the Los Alamos National Laboratory (LANL) Natural Gas Distribution System. This Plan meets the requirements of 49 CFR Part 192, Subpart P Distribution Integrity Management Programs (DIMP) for the LANL Natural Gas Distribution System. This Plan was developed by reviewing records and interviewing LANL personnel. The records consist of the design, construction, operation and maintenance for the LANL Natural Gas Distribution System. The records system for the LANL Natural Gas Distribution System is limited, so the majority of information is based on the judgment of LANL employees; the maintenance crew, the Corrosion Specialist and the Utilities and Infrastructure (UI) Civil Team Leader. The records used in this report are: Pipeline and Hazardous Materials Safety Administration (PHMSA) 7100.1-1, Report of Main and Service Line Inspection, Natural Gas Leak Survey, Gas Leak Response Report, Gas Leak and Repair Report, and Pipe-to-Soil Recordings. The specific elements of knowledge of the infrastructure used to evaluate each threat and prioritize risks are listed in Sections 6 and 7, Threat Evaluation and Risk Prioritization respectively. This Plan addresses additional information needed and a method for gaining that data over time through normal activities. The processes used for the initial assessment of Threat Evaluation and Risk Prioritization are the methods found in the Simple, Handy Risk-based Integrity Management Plan (SHRIMP™) software package developed by the American Pipeline and Gas Agency (APGA) Security and Integrity Foundation (SIF). SHRIMP™ uses an index model developed by the consultants and advisors of the SIF. Threat assessment is performed using questions developed by the Gas Piping Technology Company (GPTC) as modified and added to by the SHRIMP™ advisors. This Plan is required to be reviewed every 5 years to be continually refined and improved. Records for all piping system installed after the effective date of this Plan will be captured and retained in the UI records documentation system. Primary Utility Asbuilts are maintained by Utilities Mapping (UMAP) and additional records are maintained on the N drive. Engineering Change Notices (ECNs) are stored on the N drive under configuration management and kept up by Utilities and Infrastructure Division Office (UI-DO). Records include, at a minimum, the location where new piping and appurtenances are installed and the material of which they are constructed.
Shot planning and analysis tools (SPLAT) integrate components necessary to help achieve a high over-all operational efficiency of the National Ignition Facility (NIF) by combining near and long-term shot planning, final optics demand and supply loops, target diagnostics planning, and target fabrication requirements. Currently, the SPLAT project is comprised of two primary tool suites for shot planning and optics demand. The shot planning component provides a web-based interface to selecting and building a sequence of proposed shots for the NIF. These shot sequences, or 'lanes' as they are referred to by shot planners, provide for planning both near-term shots in the Facility and long-term 'campaigns' in the months and years to come. The shot planning capabilities integrate with the Configuration Management Tool (CMT) for experiment details and the NIF calendar for availability. Future enhancements will additionally integrate with target diagnostics planning and target fabrication requirements tools. The optics demand component is built upon predictive modelling of maintenance requirements on the final optics as a result of the proposed shots assembled during shot planning. The predictive models integrate energetics from a Laser Performance Operations Model (LPOM), the status of the deployed optics as provided by the online Final Optics Inspection system, and physics-based mathematical 'rules' that predict optic flaw growth and new flaw initiations. These models are then run on an analytical cluster comprised of forty-eight Linux-based compute nodes. Results from the predictive models are used to produce decision-support reports in the areas of optics inspection planning, optics maintenance exchanges, and optics beam blocker placement advisories. Over time, the SPLAT project will evolve to provide a variety of decision-support and operation optimization tools.
Continuous security and configuration monitoring of information systems has been a time consuming and laborious task for system administrators at the High Performance Computing (HPC) center. Prior to this project, system administrators had to manually check the settings of thousands of nodes, which required a significant number of hours rendering the old process ineffective and inefficient. This paper explains the application of Splunk Enterprise, a software agent, and a reporting tool in the development of a user application interface to track and report on critical system updates and security compliance status of HPC Clusters. In conjunction with other configuration management systems, the reporting tool is to provide continuous situational awareness to system administrators of the compliance state of information systems. Our approach consisted of the development, testing, and deployment of an agent to collect any arbitrary information across a massively distributed computing center, and organize that information into a human-readable format. Using Splunk Enterprise, this raw data was then gathered into a central repository and indexed for search, analysis, and correlation. Following acquisition and accumulation, the reporting tool generated and presented actionable information by filtering the data according to command line parameters passed at run time. Preliminary data showed results for over six thousand nodes. Further research and expansion of this tool could lead to the development of a series of agents to gather and report critical system parameters. However, in order to make use of the flexibility and resourcefulness of the reporting tool the agent must conform to specifications set forth in this paper. This project has simplified the way system administrators gather, analyze, and report on the configuration and security state of HPC clusters, maintaining ongoing situational awareness. Rather than querying each cluster independently, compliance checking can be managed from one central location.
ANSI/ANS-8.1-1998;2007, Nuclear Criticality Safety in Operations with Fissionable Material Outside Reactors, and ANSI/ANS-8.24-2007, Validation of Neutron Transport Methods for Nuclear Criticality Safety Calculations, require validation of a computer code and the associated data through benchmark evaluations based on physical experiments. The performance of the code and data are validated by comparing the calculated and the benchmark results. A SCALE procedure has been established to generate a Verified, Archived Library of Inputs and Data (VALID). This procedure provides a framework for preparing, peer reviewing, and controlling models and data sets derived from benchmark definitions so that the models and data can be used with confidence. The procedure ensures that the models and data were correctly generated using appropriate references with documented checks and reviews. Configuration management is implemented to prevent inadvertent modification of the models and data or inclusion of models that have not been subjected to the rigorous review process. VALID entries for criticality safety are based on critical experiments documented in the International Handbook of Evaluated Criticality Safety Benchmark Experiments (IHECSBE). The findings of a criticality safety validation of SCALE 6.1 utilizing the benchmark models vetted in the VALID library at Oak Ridge National Laboratory are summarized here.
Highlights: • Attached office nurses more recovered medical waste from patients’ homes. • Most nurses educated their patients on how to store home medical care waste in their homes and on how to separate them. • Around half of nurses educated their patients on where to dispose of their home medical care waste. - Abstract: To determine current practices in the disposal and handling of home medical care (HMC) waste, a questionnaire was mailed to 1965 offices nationwide. Of the office that responded, 1283 offices were analyzed. Offices were classified by management configuration: those attached to hospitals were classified as ”attached offices” and others as “independent offices”. More nurses from attached offices recovered medical waste from patients’ homes than those from independent offices. Most nurses educated their patients on how to store HMC waste in their homes (79.3% of total) and on how to separate HMC waste (76.5% of total). On the other hand, only around half of nurses (47.3% from attached offices and 53.2% from independent offices) educated their patients on where to dispose of their HMC waste. 66.0% of offices replied that patients had separated their waste appropriately. The need for patient education has emerged in recent years, with education for nurses under the diverse conditions of HMC being a key factor in patient education.
Autotuning refers to the automatic generation of a search space of possible implementations of a computation that are evaluated through models and/or empirical measurement to identify the most desirable implementation. Autotuning has the potential to dramatically improve the performance portability of petascale and exascale applications. To date, autotuning has been used primarily in high-performance applications through tunable libraries or previously tuned application code that is integrated directly into the application. This paper draws on the authors' extensive experience applying autotuning to high-performance applications, describing both successes and future challenges. If autotuning is to be widely used in the HPC community, researchers must address the software engineering challenges, manage configuration overheads, and continue to demonstrate significant performance gains and portability across architectures. In particular, tools that configure the application must be integrated into the application build process so that tuning can be reapplied as the application and target architectures evolve.
An open application platform distributes the intelligence and control capability to local endpoints (or nodes) reducing total network traffic, improving speed of local actions by avoiding latency, and improving reliability by reducing dependencies on numerous devices and communication interfaces. The platform must be multi-tasking and able to host multiple applications running simultaneously. Given such a system, the core functions of power grid control systems include grid state determination, low level control, fault intelligence and reconfiguration, outage intelligence, power quality measurement, remote asset monitoring, configuration management, power and energy management (including local distributed energy resources, such as wind, solar and energy storage) can be eventually distributed. However, making this move requires extensive regression testing of systems to prove out new technologies, such as phasor measurement units (PMU). Additionally, as the complexity of the systems increase with the inclusion of new functionality (especially at the distribution and consumer levels), hidden coupling issues becomes a challenge with possible N-way interactions known and not known by device and application developers. Therefore, it is very important to provide core abstractions that ensure uniform operational semantics across such interactions. Here in this paper, we describe the pattern for abstracting device interactions we have developed for the RIAPS platform in the context of a microgrid control application we have developed.
This tool helps red teamers and penetration testers to conduct post exploitation activities through various Configuration Management tools such as Puppet, Chef, Ansible, and Salt.
This report describes the planning and initial development of an advanced disposal system PA modeling capability to facilitate the science-based evaluation of disposal system performance for a range of fuel cycle alternatives in a variety of geologic media and generic disposal system concepts. The advanced modeling capability will provide a PA model framework that facilitates PA model development, execution, and evaluation within a formal PA methodology. The PA model framework will provide a formalized structure that enables (a) representation and implementation of a range of generic geologic disposal system options, (b) representation of subsystem processes and couplings at varying levels of complexity in an integrated disposal system model, (c) flexible, modular representation of multi-physics processes, including the use of legacy codes, (d) evaluation of system- and subsystem-level performance, (e) uncertainty and sensitivity analyses to isolate key subsystem processes and components, (f) data and configuration management functions, and (g) implementation in HPC environments.