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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.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

HERMES Shield Door Event Causal Analysis

Description Of Event: On June, 28, 2016, the HERMES III accelerator (TA-IV, Building 970) operations team began preparing for the third test shot of the day. Prior to the shot, operations personnel conducted the required pre-shot clearance and lock-up process. Following the shot, an operator and RCT re-entered the controlled area to perform post-shot clearance activities and found the shield door in the open position. All other control measures (interlocks and other access controls) were in place during this event and there was no personnel exposure. The test cell shield door is a six-inch thick steel door; it's principal function is to privide shielding, however, it also serves as a pedestrian entrance into the test cell. The shield door is located on the north side of the test cell and, aside from distance, is a primary control to mitigate personnel exposure to ionizing radiation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Occurrence Causal Analysis Report: Inadvertent Reaction During the Pressuring of Energetic Material

On June 30, 2020, an inadvertent reaction occurred during pressing of the energetic material pentaerythritol tetranitrate (PETN). The location of the event was the energetic component Rapid Prototype Facility (RPF), where similar operations performed on a variety of energetic materials are routinely provided for customers throughout Sandia National Laboratories (SNL). A background on pressing of energetic materials is provided to enhance clarity in the description of the event. This background includes a description of the equipment, materials, and tooling present during the event.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Causal Analysis Report for Thunder Range Block VIII Test - Management Concern

From July 24th -27th, 2018, Sandia National Laboratories (SNL) was conducting a series of explosive tests (referred to as Block VIII Tests) at Thunder Range. Thunder Range is an explosive testing range located on Kirtland Air Force Base and operated by SNL. The testing occurred on Range 7, a fragmentation range that is authorized for activities up to a maximum of 2,000 pounds net explosive weight (NEW). The maximum NEW for the Block VIII tests was 114 lbs. The specific management concern is that although the Thunder Range team identified controls to provide protection for essential personnel, those controls were not adequately evaluated before testing occurred. There were several controls in place at Thunder Range when the block VW test was executed. Engineered controls including Fire Control Point (FCP) placement, FCP structure design, and administrative controls involving communications. These controls were in place but not thoroughly evaluated for adequacy in meeting requirements related to sound pressure and fragments before the test was executed. Compliance with the remaining requirements was achieved. The lack of evaluation did not result in harm to personnel, equipment, or structures but was deemed as an opportunity to further understand how compliance with DOE-STD-1212-2012 could be better achieved with defensible evidence. The information provided in the remainder of this report discusses these controls and the deficiencies that contributed to this management concern.

42 ENGINEERING↗
DOE OSTI2018

NA-SS-SN L-5000-2018-0005 858EL Arsenic Release Above Permit Level (Causal Analysis Report)

On November 28, 2018 at approximately 4:17pm the arsenic monitor in the Acid Waste Neutralization (AWN) room located in 858N was registering a concentration above the permit level of 51ppb as stated in ABCWUA Permit 2069G Daily Composite Limit. 100ml samples had been drawn from the waste stream at - 6pm November 28, 2018. The samples were analyzed, results received on November 29, 2018 confirmed an arsenic concentration above the permit level.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deep Analysis Net with Causal Embedding for Coal-fired Power Plant Fault Detection and Diagnosis (DANCE4CFDD)

Fault detection and diagnosis is critical to power plant operation to ensure attaining high reliability while reducing operation cost. As more renewable power is introduced to the power grid, traditional fossil power plants take on the extra burden of excessive load cycling to compensate the generation variability from renewable power. Such load cycling will pose more reliability challenges to power plant operation. There are a number of challenges faced by today’s asset health management system in coal- fired (or gas) power plants: 1) high-dimensional nonlinear interaction among multiple time series measurements; 2) high measurement variance induced by operational conditions/modes; 3) variation among asset types and plant configurations; and 4) a small number of faulty events to learn from. To cope with these challenges, today’s fielded asset health management systems rely heavily on manual efforts from domain experts and hand-crafted features or rules based on domain knowledge. Despite its role in plant reliability, such a practice is costly and hinders its scalability and sustainability, particularly when a plant undergoes modifications. The objective of this project is to develop a novel end-to-end AI learning system that is trainable (i.e., the AI representation of a complex system behavior can be directly learned from properly labeled data) for accurate fault detection and root cause analysis. The ability to create a fault detection model directly from time series could alleviate the efforts associated with today’s asset management solution development. In the course of this project, we have achieved the following: Created an AI model development environment incorporating state-of-the-art neural network architectures for rapid model development and evaluation; Developed novel learning strategies for training of fault detection model; Developed special-purpose neural network architecture embedded with variable association graph aiming for better interpretability; Developed a learning strategy to leverage a small number of faulty events for enhanced fault detection capability; Conducted detailed experimental study based on public benchmark datasets and demonstrated the effectiveness of the proposed solution; and Validated the developed system with data from both a coal-fired plant boiler dynamic simulation model and real-world coal-fired power plant covering multiple asset and fault types. Overall, the project attained a technology readiness level of TRL 5 from TRL 2 at the beginning of the project.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Using Systems Theoretic Process Analysis and Causal Analysis to Map and Manage Organizational Information to Enable Digitalization and Information Automation

The overarching goal of this Light Water Reactor Sustainability Program–supported research and development project is to provide planning tools and comprehensive guidance to utilities considering or undertaking full nuclear plant modernization. The results of this research will provide the nuclear industry with a comprehensive and usable solution, including guidance, lessons learned, methods, and planning tools. This research is currently working to provide guidance on digitalization and information automation to enable the evolution of data to information, insight, and action—thereby allowing utilities to operate safely and cost-competitively with all other electrical generation sources. Light Water Reactor Sustainability Program researchers have also recently started investigating how human and technology integration principles, information automation, and digitalization enable data evolution. These researchers are currently in the process of validating the use of System-Theoretic Process Analysis to define high-level safety constraints in the United States Nuclear Regulatory Commission’s problem identification and resolution process (i.e., a plant compliance information gathering activity). The next step in this research, which is described in the following sections of this report, is to map out data evolution in a use case to identify inefficiencies in another aspect of plant compliance information gathering and communication activities—event investigations and root cause analyses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗