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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Maintenance Engineering Basics & Best Practices

The purpose of this document is to concisely describe the basics of maintenance engineering, summarize maintenance policies at Los Alamos National Laboratory, and also review current industry best-practices through the use of case studies. Maintenance engineering incorporates the study of failure, reliability, policies, and procedures in order to optimize cost and equipment availability. Each of these topics will be covered within this report.

42 ENGINEERING↗
DOE OSTI2021

Reliability and Maintainability Changing the Culture

The Reliability and Maintainability team strives to ensure the reliability, availability, and maintainability of plant assets throughout their life cycle. This objective is accomplished by providing world-class maintenance engineering support and maintenance processes. University of Tennessee’s Reliability and Maintainability Center (UT RMC) Partnership – Provided subject matter expert (SME) analysis of current state of both sites integrated work control (IWC) and maintenance execution processes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Photographic Mitigation Documentation Related to the Engine Assembly and Disassembly Facility, Area 25, Nevada National Security Site, Nye County, Nevada

This letter report provides documentation in partial fulfillment of the mitigation of adverse effects to the Engine Maintenance Assembly and Disassembly (E-MAD) facility, a major component of the Nuclear Rocket Development Station (NRDS) Historic District located in Area 25 of the Nevada National Security Site (NNSS). Construction of the E-MAD facility began in 1962 for the purpose of disassembling and maintaining nuclear-powered rocket engines. Once the building was complete in 1967, the E-MAD facility remained in continuous operation until the nuclear rocket program was terminated in 1973. The mothballed facility was repurposed in 1977 for spent nuclear fuel handling and packaging activities. By the mid-1980s, all activities at the E-MAD facility had ceased (Reno et al. 2019). This submission is intended to comply with Stipulation III.D.1 of the Memorandum of Agreement DE-GM58-20NA25534 between the U.S. Department of Energy and the Nevada State Historic Preservation Officer Regarding Corrective Action Activities and Demolition of the Engine Maintenance Assembly and Disassembly Facility and the Test Cell C Historic District, Major Components of the Nuclear Rocket Development Station Historic District Located in Area 25 at the Nevada National Security Site Nye County (hereafter referred to as the MOA). Stipulation III.D.1 states the U.S. Department of Energy (DOE) will submit the existing supplementary collection of the large-format, black-and-white photographic prints taken during the 1996 Historic American Engineering Record (HAER) documentation of the E-MAD facility to the Nuclear Testing Archive (NTA), located on the second floor of the Rogers Building at Desert Research Institute (DRI) in Las Vegas, Nevada.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

An Architectural Survey of the Area 25 Nuclear Rocket Development Station, Nevada National Security Site, Nye County, Nevada (Volume 1 of 3)

The U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office (NNSA/NFO), and the U.S. Department of Energy Environmental Management Nevada Program (EM NV) plan to implement corrective action activities (under the Federal Facility Agreement and Consent Order, agreed to by the State of Nevada) and demolition of the Engine Maintenance, Assembly, and Disassembly (E-MAD) facility and the Test Cell C Historic District. These are major components of the unrecorded Nuclear Rocket Development Station (NRDS) Historic District, which is eligible for inclusion in the National Register of Historic Places (NRHP, National Register). The NRDS is in Area 25 of the Nevada National Security Site (NNSS), formerly known as the Nevada Test Site, in Nye County, Nevada. Demolition and removal of the buildings and accessories constitutes an undertaking subject to review under Section 106 of the National Historic Preservation Act (54 United States Code [USC] § 306101) and its implementing regulations, 36 Code of Federal Regulations (CFR) Part 800.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

1016516285-AA - Handling Frame Assembly Table Structural and Seismic Analysis

Within the NIF (National Ignition Facility) sustainment project, LLNL is replacing all 1,728 blast shields with new ones. Before the new blast shield glass can be installed on NIF, it must pass through the AMOL (Amplifier Main Optics Loop). The AMOL process involves cleaning and coating the glass, assembling it into a Line Replaceable Unit (LRU), and performing testing and inspection. This work will be conducted in the OPFX cleanroom facility (Building 391, Room 1250) and requires several pieces of custom equipment. One key piece of equipment within the loop is the Handling Frame Assembly Table (see Figure 1.1). Its purpose is to assist operators in installing the blast shield glass into handling frames (1014442709) (see Figure 1.2). The table is also used to store handling frame assembly components. The primary components stored are the L-frames (1015208271), which are kept in a drawer underneath the table (see Figure 1.3). The purpose of this safety note is to ensure that the system does not pose a risk of injury to personnel during a seismic event. The system owner is OMST Engineering & Maintenance.

42 ENGINEERING↗
DOE OSTI2022

Fault Characterization and Diagnostics Supporting Condition-Based Operation and Maintenance of Gas Turbine Engines

Condition-Based Operation and Maintenance (CBOM) is the state-of-the-art in maintenance approaches for gas turbine engines. CBOM applies engine sensor information to the optimization of future operation and maintenance procedures; this technique reduces costs for engine operators by minimizing unplanned outages and catastrophic engine degradation. However, due to the complexities of gas turbine operation and the lack of available engine sensors, further development is required to fully realize the benefits of CBOM. In the turbine section, rotating components interact with high temperature flows, which creates intense thermal and mechanical stresses. As a result, there are numerous mechanisms of component degradation in the turbine section. Furthermore, turbine components – like stator vanes and rotor blades – are among the most expensive in the engine because they are complex to design and manufacture. For these reasons, this dissertation addresses two main questions: (i) which parameters or faults within the turbine section are most important to monitor, and (ii) how can these parameters or faults be monitored in an engine-relevant environment? Although many turbine parameters and faults have been investigated in the open literature, there are some faults that are still not well understood. Rotor-casing eccentricity, which causes a non-constant blade tip clearance around the annulus, has not been investigated in terms of its effects on turbine efficiency. Therefore, the first study in this dissertation quantifies overall and local turbine efficiency for varying levels of rotor-casing eccentricity. Results showed negligible variations to overall turbine efficiency, meaning rotor-casing eccentricity only becomes relevant to CBOM when its severity causes rotordynamic issues. Purge flow is critical to turbine hardware longevity because it prevents ingestion of hot main gas path (MGP) flow into the under-platform regions. Despite its importance, there are currently no methods for monitoring purge flow performance in an engine environment. Therefore, the second study in this dissertation develops a predictive model for sealing effectiveness using inputs from two fast-response pressure sensors. Results exhibited low prediction errors across a full range of purge flow rates, which supports the viability of the modelling approach for CBOM. The final two studies in this dissertation address blade coolant flow monitoring. This cooling flow is responsible for protecting the turbine blades from the MGP flow, which exits the combustor at temperatures greater than the blade melting point. These studies showed that temperature measurements on the blade surface can be used to accurately predict blade coolant flow rate, and that defining the candidate features relative to the coolant trajectory is important for maintaining accuracy as coolant flow rate degradation occurs. This work enables blade coolant flow monitoring, which is currently not possible through existing condition monitoring techniques.

condition-based, gas turbines, diagnostics,↗
DOE OSTI2025

System Engineers and Decisions: It?s All about Knowledge

In order to guarantee that a system meets adequate levels of reliability and availability, system performances are continuously monitored and analyzed thanks to the technological advancements driving the Industry 4.0 revolution. An Industry 4.0 approach is typically based on advanced statistical, big data mining, machine learning, and internet-of-things methods designed to detect anomalies in the behavior of system, detect the most likely failure modes, and provide indications to system engineers on when maintenance activities should be performed before system performance are deemed unacceptable (which can be generated by diagnostic and prognostic methods). However, these analyses, which are designed to automatize and increase the efficacy of the system maintenance program, require large amount of data which can come in various forms: numeric, textual, images, sounds etc. Such data constitutes the historic knowledge benchmark to track system performances and support system engineer decisions. Here we claim that data is not sufficient to support this kind of analyses when applied to systems characterized by complex architectures and behaviors. Robust system engineer decisions require the ability to understand the system operational context that lies behind the observed data elements. In this respect, system models are in fact necessary to “put data in context” and capture relationships between data elements. Industry 4.0 methods require in fact contextual knowledge as a basis upon which hypotheses can be generated and assumptions tested. In our view, for complex systems, model-based system engineering (MBSE) models can afford this contextual knowledge, as they are typically used to describe systems architecture and dynamic behaviors. System knowledge is here intended as the blending of collected data and system architecture which takes the form of a “knowledge graph”. A knowledge graph is a database which consists of a large set of nodes (in our case an entity can be either a data or an MBSE element) which are linked to each other. The types of nodes and links follow a pre-defined topology, sometimes also refers as an ontology, that is designed to fit the actual decisions that needs to be performed. We show here how a knowledge graph can be defined to support system engineer maintenance decisions and how the same graph can be built based on system MBSE models and pre-processed data from numeric (through anomaly detections and diagnostic methods) and textual elements (through technical language processing TLP).

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Mechanisms Engineering Test Loop (METL) Operations, Maintenance, and Testing - FY2025

This report documents the operations, maintenance, and improvements that were performed at the Mechanisms Engineering Test Loop (METL) and its supporting infrastructure during FY2024. The METL facility had a very successful seventh year of operations while supporting the testing of multiple test article experiments in the facility. The METL facility continued supporting the Gear Test Assembly (GTA) testing and the Thermal Hydraulic Experimental Test Article (THETA) with the full testing with both the primary and secondary systems. Work to accommodate two additional experiments, a flow sensor test article (F-STAr) gripper test and a fuel handling gripper test article (GrTA) continued as they are expected to undergo testing in METL in FY2025. In addition, a new 18” test article, the Sample Testing Basket (STB) was used a few times to provide screening tests for sodium service materials. A fifth test vessel was installed in the location of Test Vessel 6, and a wet vapor nitrogen sodium processing system was developed and initially tested.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

The Corrective Maintenance Paradigm Shift at Hanford's Tank Farms - 20077

Hanford's Tank Farms facilities have been used to safely store waste for over 70 years, with the first single-shell tanks being constructed in 1943. Tank Farm facilities consist of 149 single-shell tanks, 28 double-shell tanks, an evaporator facility, and wastewater treatment facilities. Tank Farm facilities are aging, with a tremendous corrective maintenance burden on the Tank Farm contractor. The mission of Tank Farm facilities is soon changing from waste storage to waste staging for the Hanford Waste Treatment and Immobilization Plant (WTP). WTP operations will demand a significant increase in Tank Farm facility operations, in which corrective maintenance outage windows will shrink drastically. This realization has forced the Tank Farm contractor to consider a paradigm shift in Tank Farm facilities Maintenance planning, and the use of reliability Engineering tools. The Tank Farm Production Operations Engineering Cognizant System Engineering (CSE) organization has led the way in motivating this paradigm shift. This shift has been realized through the use of: 1) technical exchange with other Department of Energy (DOE) contractors to develop improvements in the CSE program, 2) a shift from the use of lagging to leading system health indicators, and 3) a Plant Health Committee to unite Engineering, Operations, and Maintenance personnel toward a productive maintenance strategy. The CSE organization has held several technical exchanges with other DOE contractors to discuss CSE concepts, and how to better maintain aging infrastructure. The technical exchange with other contractors has greatly reduced the time required to make improvements in the Tank Farm CSE program. Other DOE contractors have already faced issues surrounding aging infrastructure, and have vast experience in improving the reliability and usable life of structures and components in nuclear facilities. The past CSE program used lagging health indicators to determine the health of systems. The key lagging indicator used to determine system health was availability, which is the percentage of time that a facility was ready for operation compared to the time the facility was demanded for operation. Availability was a good indicator of health in the waste storage mission of Tank Farms, where safe storage was the most important function of the facility, and where maintenance outage windows were typically long-duration. In current and future operations, outage windows are reducing, resulting in the need for much more reliable systems. Systems that have had high availability may suddenly become inoperable due to a failed component or sub-system. In several instances, the use of availability as an indicator of system health failed to predict system/equipment failure before its occurrence. In discussions with other DOE contractors, a set of reliability tools, including leading indicators of health, has been implemented in the CSE program. This primarily involves the use of failure modes and effects analysis and the study of equipment failure to develop system monitoring plans that focus on trending data to detect oncoming equipment failure ahead of time. In addition, the use of a Plant Health Committee has added significantly to the paradigm shift from a corrective maintenance philosophy to the use of predictive and preventive maintenance. The Plant Health Committee is a chartered team consisting of Engineering, Operations, and Maintenance personnel. CSEs use this forum to present the results of their performance monitoring, including the presentation of health via leading health indicators. The most positive aspect of this committee is the communication that it creates within these critical organizations. The Operations and Maintenance organization benefit from focusing maintenance on the reliability-centered focus provided by Engineering. Engineering benefits from the operational experience of the Operations organization and from the failure data that can be provided by Maintenance personnel. The continued use of the Plant Health Committee is expected to further decrease maintenance outage times, in better support of oncoming 24/7 operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Deploying Extended Reality (XR) for Digital Operations and Maintenance (O&M) at the Mechanisms Engineering Test Loop (METL)

This report documents the preliminary efforts to digitize operation and maintenance (O&M) activities for the Mechanisms Engineering Test Loop (METL). METL became operational in September 2018 with the mission to provide an ecosystem for Advanced Reactor Development (ARD). METLs flagship facility’s primary purpose is conducting small to intermediate scale tests for Sodium Fast Reactors (SFR). Its resemblance to commercial SFR’s intermediate heat transport system, prototypic operating conditions, and industrial construction practices/materials provides the overarching benefit of establishing a proving ground for emerging operations and maintenance (O&M) activities such as incorporating Extended Reality (XR) applications throughout the program lifecycle.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Hillsborough County Clear Sky Assessment Process: Prioritizing Solar + Storage for Resilient Facilities & Communities

The Clear Sky Tampa Bay project was a 15-month collaborative research effort to support solar + storage deployment for community resilience in Florida. The Clear Sky Decision Support Toolkit is a collection of resources designed to support users in conducting solar + storage prioritization and feasibility screening assessments at critical facilities. The Tampa Bay Regional Planning Council worked with four local governments in the region to test and apply the Toolkit. This case study series describes how each partner government used the Toolkit and highlights key insights and lessons learned that other users could follow to replicate the process. Hillsborough County used the Clear Sky Decision Support Toolkit to analyze solar + storage as an additional resiliency feature at its Brandon Support Operation Complex (BSOC). During normal operations, the BSOC houses water utility administration services and workspaces for water and wastewater engineers, facilities maintenance, and environmental management staff. During emergency management activation, the BSOC serves as an emergency hub for Emergency Support Function 3 (ESF-3), which includes public utilities, public works, and engineering staff support members. The BSOC is designated as a critical facility by the County.

14 SOLAR ENERGY↗
DOE OSTI2026

CRADA Number NFE-24-10110 with Qubit Engineering Inc. (CRADA Final Report)

Over the past year, the Qubit Engineering team has pushed the frontiers of power‑grid optimization, working in close collaboration with Oak Ridge National Laboratory (ORNL) and the Tennessee Valley Authority (TVA). Their progress is reflected in three newly submitted conference papers, “Unified Relational GNN Architecture for AC Optimal Power Flow Calculations in Electric Grids,” “Graph‑Based Attention Mechanisms for Solving the AC Optimal Power Flow Problem in Electrical‑Power Networks,” and “Enhanced Power‑Grid Maintenance Planning and Quantum‑Inspired Combinatorial Prospects.” These publications showcase state‑of‑the‑art graph‑neural‑network methods for AC‑OPF and novel quantum‑inspired heuristics for maintenance scheduling. Beyond the academic results, the Qubit team has converted the research into two production‑grade tools built on TVA data: Neuro‑Grid, an AI‑driven power‑flow simulator that provides instant, interactive full‑grid load‑flow visualizations, and Quanta‑Grid, a quantum‑inspired maintenance‑scheduling engine to support logistics optimization for power utilities. Together, these advances demonstrate how Qubit’s partnership with ORNL and TVA is delivering practical, physics‑grounded analytics for next‑generation grid management.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

INTEGRATION OF DATA ANALYTICS WITH SYSTEM HEALTH PROGRAMS

Industry equipment reliability and asset management programs are essential elements that help ensure the safe and economical operation of nuclear power plants. The effectiveness of these programs is addressed in several industry developed and regulatory programs. However, these programs have proven to be labor intensive and expensive. There is an opportunity to significantly enhance the collection, analysis, and use of this information to provide more cost-effective plant operation. Additionally, there is an acute industry need to leverage advanced technology to reduce costs and improve operational effectiveness. The goal of this paper is to provide effective and efficient analytical methods and tools to support risk-informed decisions for the equipment reliability and asset management programs at nuclear power plants. This is accomplished by creating a direct bridge between component health/lifecycle data and decision making (e.g., maintenance scheduling and project prioritization). Here we are supporting typical system engineer decisions regarding maintenance activity scheduling and component ageing management. This is performed in a risk-informed context where herein the term “risk” is broadly constructed to include both plant reliability and economics. This framework combines data analytics tools to analyze equipment reliability data with risk-informed methods designed to support system engineer decisions (e.g., maintenance and replacement schedules, optimal maintenance posture) in a customizable workflow. A challenge is that the structure of this workflow strongly depends on the decision that needs to be made, the type of data available, and the constraints that need to be considered. Current methods are designed to provide specific answers to specific problems; however, these methods might prove to be inadequate even when problem settings slightly change (e.g., different types of requirements, additional dependencies between system reliability and economics). We tackled this challenge by designing framework in a flexible and modular fashion such that the user can assemble and customize his/her own workflow that integrates SSC economic lifecycle models (e.g., maintenance and replacement costs), system reliability models, and optimization methods.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Unsupervised Image-Based Classification of Corrosion Severity in Automobile Engine Connecting Rods

Corrosion in engine connecting rods is a critical issue in the automotive industry, potentially leading to catastrophic engine failure, monetary losses, and safety hazards. The labor shortage in the industry further emphasizes the need for fast, accurate, and automated corrosion detection methods to ensure appropriate surface treatments can be applied to restore component integrity. We present an unsupervised image-based framework for classifying corrosion severity in automobile engine connecting rods using short-wave infrared (SWIR) and telecentric grayscale imaging. We employ the structural similarity index measure (SSIM) as a dissimilarity metric and the k-medians clustering algorithm for classification. Our algorithm achieves an overall accuracy of 80.64% for SWIR images, with 100% accuracy in classifying highly corroded samples. For grayscale images, the method attains an overall accuracy of 77.42%, with 90.91% accuracy for highly corroded samples. The method’s ability to work with different imaging modalities and its high accuracy in identifying severe corrosion cases make it a promising tool for automated corrosion assessment in the automotive industry, potentially improving efficiency and safety in engine component maintenance.

42 ENGINEERING↗
DOE OSTI2022

Overcoming Challenges to Continuous Integration in HPC

Continuous integration (CI) has become a ubiquitous practice in modern software development, with major code hosting services offering free automation on popular platforms. CI offers major benefits, as it enables detecting bugs in code prior to committing changes. While high-performance computing (HPC) research relies heavily on software, HPC machines are not considered “common” platforms. This presents several challenges that hinder the adoption of CI in HPC environments, making it difficult to maintain bug-free HPC projects, and resulting in adverse effects on the research community. Here we explore the challenges that impede HPC CI, such as hardware diversity, security, isolation, administrative policies, and non-standard authentication, environments, and job submission mechanisms. We propose several solutions that could enhance the quality of HPC software and the experience of developers. Implementing these solutions would require significant changes at HPC centers, but if these changes are made, it would ultimately enable faster and better science.

97 MATHEMATICS AND COMPUTING↗