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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

ON THE LANGUAGE OF RELIABILITY: A SYSTEM ENGINEER PERSPECTIVE

In its classical definition, risk is defined by three elements: what can go wrong, what are its consequences and how likely is it to occur. While this definition makes sense in a regulatory based framework to estimate risk associated to power plants (in terms of core damage frequency and large early release frequency), this approach does not provide a useful snapshot of the health of the plant. A possible alternate path can start by redefining the word “risk” to a broader meaning that better reflects the needs of a system health and asset management decision making process. Rather than asking how likely an event can occur (in probabilistic terms), we can ask how far this event is from occurring. We will show how, given the data available from plant equipment reliability and monitoring/diagnostic/prognostic centers, a margin can be described and determined for all type of maintenance approaches (e.g., corrective or predictive maintenance). We will show how to link SSC margin-based reliability models to system reliability models (i.e., fault trees) in order to assess system/plant health and how to perform margin-based system calculations. These calculations are not solved using classical probabilistic calculations applied to sets (as performed by any PRA code) but, instead, through metric spaces operations (i.e., distance/margin based approach).

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Building Energy Asset Score for Real Estate Managers

The Building Energy Asset Score is a national standardized tool for evaluating the physical and structural energy efficiency of commercial and multifamily residential buildings. The Asset Score generates a simple energy efficiency rating that enables comparison among buildings, and identifies opportunities for users to invest in energy efficiency upgrades. It is web-based and free to use. This fact sheet discusses the value of the score for real estate managers.

Building energy simulation, building envelope, hot↗
DOE OSTI2015

Prognostic and health management of active assets in nuclear power plants

This study presents the development of diagnostic and prognostic capabilities for active assets in nuclear power plants (NPPs). The research was performed under the Advanced Instrumentation, Information, and Control Technologies Pathway of the Light Water Reactor Sustainability Program. Idaho National Laboratory researched, developed, implemented, and demonstrated diagnostic and prognostic models for generator step-up transformers (GSUs). The Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software developed by the Electric Power Research Institute was used to perform diagnosis and prognosis. As part of the research activity, Idaho National Laboratory implemented 22 GSU diagnostic models in the Asset Fault Signature Database and two wellestablished GSU prognostic models for the paper winding insulation in the Remaining Useful Life Database of the FW-PHM Suite. The implemented models along with a simulated fault data stream were used to evaluate the diagnostic and prognostic capabilities of the FW-PHM Suite. Knowledge of the operating condition of plant asset gained from diagnosis and prognosis is critical for the safe, productive, and economical long-term operation of the current fleet of NPPs. This research addresses some of the gaps in the current state of technology development and enables effective application of diagnostics and prognostics to nuclear plant assets.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2016

Implementing Reliability Centered Maintenance (RCM) with State of the Art PT&I Technologies

Building on the work that was started two decades ago, Jacobs Space Operations Group has utilized state of the art PTI technologies to assess the current condition of the assets they manage under the Test and Operations Support Contract (TOSC). Specifically, the Asset Management department leveraged the benefits of ultrasound technology to quantify a motor issue in the Liquid Oxygen Storage Area, and troubleshoot the sources prior to loading the tank to perform Verification and Validation (VV) activities. This technology was efficient, easy to implement, and provided system engineers with data on a possible source of the problem. In situations where legacy motors are exhibiting unexpected noises, it may seem easier to remove and refurbish the motor and replace the bearings because that solution resolves most of the common causes of the noise. However, that solution would have involved additional spending and may not have solved issues stemming from the foundation, if those existed. By utilizing the ultrasound equipment provided by UE Systems, the sound profiles allowed Jacobs TOSC team to determine that the issue resembled a faulty bearing. After replacing the bearing, the unexpected noise ceased.

Reliability Centered Maintenance↗
DOE OSTI2018

Transactive Approach for Engaging Distribution Network Assets for Voltage Management in Southern California Edison Distribution Feeders

This report documents an effort by Pacific Northwest National Laboratory (PNNL) investigating the utility of using incentive signals to elicit useful responses from smart inverters associated with customer-owned distributed energy resources (DERs). This project was an element of the Southern California Edison (SCE) Integrated Grid Project (IGP) funded by the California Public Utilities Commission’s (CPUC’s) Electric Program Investment Charge (EPIC) program (CPUC 2018) to support applied research and development, technology demonstration and deployment, and the market facilitation of clean energy technologies and approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗
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↗
NASA NTRS2014

Imagery Integration Team

The Human Exploration Science Office (KX) provides leadership for NASA's Imagery Integration (Integration 2) Team, an affiliation of experts in the use of engineering-class imagery intended to monitor the performance of launch vehicles and crewed spacecraft in flight. Typical engineering imagery assessments include studying and characterizing the liftoff and ascent debris environments; launch vehicle and propulsion element performance; in-flight activities; and entry, landing, and recovery operations. Integration 2 support has been provided not only for U.S. Government spaceflight (e.g., Space Shuttle, Ares I-X) but also for commercial launch providers, such as Space Exploration Technologies Corporation (SpaceX) and Orbital Sciences Corporation, servicing the International Space Station. The NASA Integration 2 Team is composed of imagery integration specialists from JSC, the Marshall Space Flight Center (MSFC), and the Kennedy Space Center (KSC), who have access to a vast pool of experience and capabilities related to program integration, deployment and management of imagery assets, imagery data management, and photogrammetric analysis. The Integration 2 team is currently providing integration services to commercial demonstration flights, Exploration Flight Test-1 (EFT-1), and the Space Launch System (SLS)-based Exploration Missions (EM)-1 and EM-2. EM-2 will be the first attempt to fly a piloted mission with the Orion spacecraft. The Integration 2 Team provides the customer (both commercial and Government) with access to a wide array of imagery options - ground-based, airborne, seaborne, or vehicle-based - that are available through the Government and commercial vendors. The team guides the customer in assembling the appropriate complement of imagery acquisition assets at the customer's facilities, minimizing costs associated with market research and the risk of purchasing inadequate assets. The NASA Integration 2 capability simplifies the process of securing one-of-a-kind imagery assets and skill sets, such as ground-based fixed and tracking cameras, crew-in the-loop imaging applications, and the integration of custom or commercial-off-the-shelf sensors onboard spacecraft. For spaceflight applications, the Integration 2 Team leverages modeling, analytical, and scientific resources along with decades of experience and lessons learned to assist the customer in optimizing engineering imagery acquisition and management schemes for any phase of flight - launch, ascent, on-orbit, descent, and landing. The Integration 2 Team guides the customer in using NASA's world-class imagery analysis teams, which specialize in overcoming inherent challenges associated with spaceflight imagery sets. Precision motion tracking, two-dimensional (2D) and three-dimensional (3D) photogrammetry, image stabilization, 3D modeling of imagery data, lighting assessment, and vehicle fiducial marking assessments are available. During a mission or test, the Integration 2 Team provides oversight of imagery operations to verify fulfillment of imagery requirements. The team oversees the collection, screening, and analysis of imagery to build a set of imagery findings. It integrates and corroborates the imagery findings with other mission data sets, generating executive summaries to support time-critical mission decisions.

Calhoun, Tracy↗
DOE OSTI2020

Substation Secondary Asset Health Monitoring and Management System (SSHM)

Electric Power Group, LLC (EPG) was awarded DOE OE0000850 to design, develop, and demonstrate a real-time software application for substation secondary equipment health monitoring and management at host utility American Electric Power (AEP), a cost share partner. This project addresses the need for monitoring substation equipment health and providing operators with tools to identify and take pre-emptive action to avoid catastrophic equipment failure. By monitoring synchrophasor data in real time, data anomalies that indicate potential asset failure can be detected and alerts can be sent to operators in time to take corrective actions. EPG developed two data driven algorithms to identify abnormal equipment signature patterns as well as a method using substation linear state estimation (SLSE). The software has been deployed on hardened PC’s and tested and validated for cost share partner AEP’s substations - 138kV and 765 kV. The SSHM software has been accepted by AEP and final demonstration of DOE - OE0000850 for AEP and DOE was successfully completed on March 17th, 2020. EPG developed the Substation Secondary Asset Health Monitoring (SSHM) Platform to analyze equipment failure signatures in PMU data and alert substation personnel when pre-emptive inspection, repairs and other actions are warranted to prevent potential catastrophic failures. This is the first system that automatically monitors the health of substation secondary assets and alerts users to emerging failures using synchrophasor measurements. SSHM uses high resolution PMU data from PTs, CTs, and CCVTs to analyze equipment signatures and identify anomalies that are precursor indicators of potential equipment failure. When an anomaly is detected, there is a likelihood of potential failure of monitored equipment, the system alerts the user with visual alarms including alarm trend charts and indicator lights on a oneline diagram of the substation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Online Monitoring of Plant Assets in the Nuclear Industry

Today’s online monitoring technologies provide opportunities to perform predictive and proactive health management of assets within many different industries, in particular the defense and aerospace industries. The nuclear industry can leverage these technologies to enhance safety, productivity, and reliability of the aging fleet of existing nuclear power plants. The U.S. Department of Energy’s Light Water Reactor Sustainability Program is collaborating with the Electric Power Research Institute’s (EPRI’s) Long-Term Operations program to implement online monitoring in existing nuclear power plants. Proactive online monitoring in the nuclear industry is being explored using EPRI’s Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software, a set of web-based diagnostic and prognostic tools and databases that serves as an integrated health monitoring architecture. This paper focuses on development of asset fault signatures used to assess the health status of generator step-up transformers and emergency diesel generators in nuclear power plants. Asset fault signatures describe the distinctive features based on technical examinations that can be used to detect a specific fault type. Fault signatures are developed based on the results of detailed technical research and on the knowledge and experience of technical experts. The Diagnostic Advisor of the FW-PHM Suite software matches developed fault signatures with operational data to provide early identification of critical faults and troubleshooting advice that could be used to distinguish between faults with similar symptoms. This research is important as it will support the automation of predictive online monitoring techniques in nuclear power plants to diagnose incipient faults, perform proactive maintenance, and estimate the remaining useful life of assets.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2011

Portfolio Management

Enterprise Business Information Services Division (EBIS) supports the Laboratory and its functions through the implementation and support of business information systems on behalf of its business community. EBIS Five Strategic Focus Areas: (1) Improve project estimating, planning and delivery capability (2) Improve maintainability and sustainability of EBIS Application Portfolio (3) Leap forward in IT Leadership (4) Comprehensive Talent Management (5) Continuous IT Security Program. Portfolio Management is a strategy in which software applications are managed as assets

Information Technology Applications↗
DOE OSTI2022

Earned Value Management Systems for Operations Activities

An earned value management system (EVMS), which monitors contractor performance, is a requirement for program and project management for all major acquisitions by the United States Federal Government with development effort: (i.e., an asset requiring management attention because of its importance to an agency’s mission; high development, operating, or maintenance costs; high risk and/or high return). As an area less explored in earned value management (EVM) practices, this paper will survey the application of an EVMS for operations activities defined as: (1) Non-capital asset activities that are projects (or project - like) with definable start and end dates, with discrete scopes of work, and measurable accomplishments; as well as (2) Routine or recurring facility or environmental operations. This paper will examine the use of an EVMS to evaluate performance of operations and maintenance activities required once construction of a capital asset is complete and being used as intended. Such activities include upgrades and maintenance in order for capital assets to meet their mission function over a life-cycle (through repair, replacement, etc.). This paper will provide background on this topic from the perspective of the Department of Energy (DOE) Environmental Management (EM) Program. In addition, it will provide material from a panel discussion provided by a group of experts from the October 2019 Office of Environmental Management Project Management Workshop, as well as material from subsequent research on this topic.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

POWER ELECTRONICS GRID TIED SYSTEM FINAL REPORT

Across the country, electric utilities are grappling with the persistent hurdles of integrating Distributed Energy Resources (DERs). Managing these assets safely and effectively is a complex endeavor, complicated by varying ownership structures, management philosophies, and the diversity of the technologies themselves. Consequently, the industry has seen a proliferation of bespoke system designs, control strategies, and communication frameworks—forcing utilities to spend significant time and resources developing one-off integration solutions. This project addressed these integration hurdles through a scalable demonstration of intelligent devices designed to coordinate and control diverse resources in low-voltage applications. This concept minimized the need for complex integration by transforming the separate DERs into a dispatchable virtual power plant (VPP) with integrated resiliency functions (called a Node). By collaborating with a utility partner, the project focused on developing rapidly implementable use cases that bridged the gap between theoretical control and real-world deployment

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Distribution Transformer Health Monitoring using Smart Meter Data

The distribution electric grid has become a highly complex and intelligent network with changing load and customer types. This has generated unprecedented challenges and opportunities for utility companies–opportunities especially in the area of asset health/performance management. Moreover, several utilities are increasingly moving from the traditional reactive and time-based asset monitoring approach to a more proactive condition based method. However, this needs to be done in a low-cost and efficient manner. Here, this paper explores how existing sensor infrastructure such as smart meters can be utilized to provide utility operators with more visibility into the health and operation of their assets. The paper focuses primarily on service transformers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Enabling a Decentralized Smart Grid Using Autonomous Edge Control Devices

As a large number of distributed devices are connected to the modern smart grid, the traditional centralized connectivity models fail to provide economic value. These models have relied on sending data to the cloud for processing and receiving commands to exert control actions, resulting in an ‘on-demand system’ with high bandwidth, low latency and an overload of data on the cloud. For realizing a decentralized system, there is a strong need to embed intelligence at the ‘edge of the network’. These intelligent devices, capable of sensing, local data processing and exerting control actions, report only actionable information to the cloud, acting as an edge control node. The system can then function autonomously, without constant cloud inputs, tolerating longer delays in communication, making the overall system ultra-low cost. The Global Asset Monitoring, Management and Analytics (GAMMA) Platform is a novel ultralow- cost, secure platform that operates through a Bluetooth based delay tolerant network. It relies on so-called ‘data mules’ to bridge the last mile connectivity gap in an inherently secure way. Due to this model, the platform requires no in-country certifications, does not rely on a dedicated backhaul technology and is immune to technology migration. This architecture also addresses some gaps identified in traditional IoT-based solutions in remote areas and sparse connectivity. A functional unit of the edge computing node has been built, taking into account various constraints like costs, customizations, data storage, cybersecurity and power management. Here, the platform has been built, deployed and has demonstrated distributed smart grid applications like power quality sensing, automated metering infrastructure and utility asset monitoring.

42 ENGINEERING↗