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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Benchmarking burnup reconstruction methods for dynamically operated research reactors

The burnup of an HEU fueled dynamically operated research reactor, the Oak Ridge Research Reactor, was experimentally reconstructed using two different analytic methodologies and a suite of signature isotopes to evaluate techniques for estimating burnup for research reactor fuel. The methods studied include using individual signature isotopes and the complete mass spectrometry spectrum to recover the sample’s burnup. The individual, or sets of, isotopes include 148 Nd, 137 Cs+ 137 Ba, 139 La, and 145 Nd+ 146 Nd. The storage documentation from the analyzed fuel material provided two different measures of burnup: burnup percentage and the total power generated from the assembly in MWd. When normalized to conventional units, these two references differed by 7.8% (395.42GWd/MTHM and 426.27GWd/MTHM) in the resulting burnup for the spent fuel element used in the benchmark. Among all methods being evaluated, the results were within 11.3% of either reference burnup. The results were mixed in closeness to both reference burnups; however, consistent results were achieved from all three experimental samples.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

or-topas: Operations Research Toolkit for Pyomo Alternative Solutions

SAND2026-16702O OR-TOPAS: Operations Research Toolkit for Pyomo Alternative Solutions is a tool that enhances optimization applications defined by the Pyomo modeling library. It offers functions to generate optimal or near-optimal solutions, operating independently of Pyomo’s solver interface. Users can configure these functions with specific solver names and options, resulting in a custom solution object that returns a list of solutions. The OR-TOPAS library includes methods tailored to the properties of the model, such as binary integer programs versus linear programs, and specific solver interfaces like Gurobi. It does not provide models for specific applications, but it is applicable to a wide range of Pyomo optimization models. Sandia National Laboratories is a multimission 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.

Siirola, John [Sandia National Lab. (SNL-CA), Live↗
DOE OSTI2015

Operations research modeling in support of the Hanford direct feed low activity waste program - 15538

Operations Research (OR) modeling is a supplemental system planning tool for the Hanford Tank Farm Contractor. OR models are designed to quantify the impact of equipment failures and other constraints on mission duration; to determine overall system performance; and to identify any potential bottleneck areas and identify any potential improvement areas. OR models are being developed to provide critical insights into the expected operational performance of current and planned facilities and to help identify any operational risks which impact performance of plant and equipment. This information is used to aid decision making on facility design and operations. A new OR model is being developed in support of the Direct Feed Low Activity Waste (DFLAW) Program and will be a valuable tool in the development of overall operational and management strategies as well as providing input to facility design. The OR model will identify predicted system availability, process bottlenecks, and key equipment influencing system performance. The OR model will also test proposed solutions to improve system availability by resolving process bottlenecks and provide this information to the design agent for incorporation into the DFLAW process design. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Application of Artificial Intelligence/Machine Learning to Operations Research

This report examines the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) on operations research, private industry, and government sectors, highlighting their applications in automating processes, enhancing decision-making, and optimizing complex systems. AI/ML technologies have revolutionized industries through predictive maintenance, supply chain optimization, and autonomous systems, while also advancing public safety and defense operations. However, challenges such as data integrity, model transparency, and the need for human oversight persist, particularly in high-consequence environments. The report emphasizes the critical role of explainable AI (XAI) and human-computer interaction models like Human-in-the-Loop (HITL) and Human-on-the-Loop (HOTL) in fostering trust and accountability. Balancing automation with ethical responsibility and transparency is essential for the continued successful integration of AI/ML into operational and strategic decision-making frameworks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Accelerating Hanford Site Cleanup through Operations Research Modeling - 20238

The Hanford Site cleanup effort will require the integration of dozens of unique facilities and processes, many of which will be first-of-a-kind in implementation and design. Each facility will be governed by its own set of operating logic, configured with a unique array of unit operations, and subject to a set of constraints that will affect its behavior. The collection of facilities have multiple points of interface, making the operations of any one facility potentially significant to the operations of other up- or downstream processes. It is therefore highly desirable to accurately predict these operations, as it allows for Site officials to identify and preempt bottlenecks and vulnerabilities before they unexpectedly inhibit the cleanup mission. With the quantity and complexity of the processes that will be on Site, building a pen-and-paper or even a spreadsheet-assisted model of the cleanup mission quickly becomes overwhelming in scope and inaccurate in execution. The Engineering organization for the Site's Tank Operations Contract (TOC) has therefore implemented the use of operations research (OR) modeling to simulate and predict future operations of Site facilities. These models are created using a discrete event simulation tool that allows for the development of detailed, versatile, and robust models. Not only can these models account for complex logical behaviors, but they can also simulate process details down to the level of vessel sizing, labor utilization, equipment reliability, and resource availability. To date, the TOC has developed OR models for several facilities on Site, including for single-shell tank (SST) farms, double-shell tank (DST) farms, the Effluent Treatment Facility (ETF), and the waste transfer system. These models have focused on identifying bottlenecks and operational constraints, and have been used to quantify the effects of implementing process changes. This latter point is particularly valuable, as it allows for several alternatives to be studied in a virtual setting before committing resources to making a change in the field. The decision to develop OR models has gained tremendous support from the Site's stakeholders and the U.S. Department of Energy (DOE) management, and has prompted the use of the tool to support additional internal and external initiatives. Recently, an initiative was proposed to use the models to help identify and provide quantitative backing for risks and opportunities for the TOC. This application of OR could not only help inform how the TOC manages its risks (e.g. quantities and types of spare parts), but could also help drive process improvements whose benefits might otherwise be hard to quantify. The models have also been used to drive the TOC's cloud computing, artificial intelligence (AI), and machine learning (ML) initiatives. These initiatives will not only improve the ability of the TOC to more rapidly respond to the needs of its customers, but it will also aid in the ability of the TOC to analyze and improve the processes it studies. Partnership with two external software development and consulting companies (Lanner and Ynformed) has furthered not only the application of AI and ML within the TOC, but has also spurred the development of new/improved software tools and platforms used by the companies. These partnerships have proven to be mutually beneficial and productive, and have set a precedent for the types of gains that can be made by exploring such options. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

ROTOR: Research to Operations and Operations to Research

PNNL’s Research to Operations/Operations to Research (ROTOR) Program fosters a cybersecurity operations to researcher collaboration, identifying hard problems and challenges for cyber defenders and bringing researcher science disciplines to these challenges. ROTOR allows PNNL’s cyber defenders to better protect the laboratory but also fosters innovation and incubation of solutions for our sponsor missions across DOE, DOD, DHS and the intelligence community. Our sponsors and their missions are faced with many of the same cyber defense challenges that PNNL faces. By using our own laboratory security operations environment as an innovation generator and testing ground, allowing research to be tested and tried, our sponsors are directly benefitted. PNNL is in a unique position to combine our world class research organization with enterprise cybersecurity operations. ROTOR is taking advantage of this to bring PNNL cybersecurity research projects into an operational environment within PNNL’s Cyber Security Operations Center. With ROTOR, PNNL researchers gain the advantage of operational experience and expertise and have an avenue for showcasing research in an operational environment. This helps to advance PNNL research, prove operability of PNNL projects to its sponsors, and provide real-world insight to real-world problems for our cybersecurity research agenda. ROTOR is the conduit for PNNL cybersecurity research to find its way to operational use. PNNL researchers and engineers are informed by real-world operations and operations has access to current PNNL research and engineering capabilities. All of this leads to improved reputation for PNNL as a provider of national security solutions that are tried and tested. To date, ROTOR has collaborated with six projects, enabling each to conduct operational work within the CSOC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

SNOLAB Deep Underground Scientific Research Operations

Investigations at the frontiers of particle physics are driving key experiments deep underground to escape cosmic-rays and other backgrounds that overwhelm sensitive searches for dark matter, exotic particles, and neutrino properties. The international neutrino physics community has come together to develop the Deep Underground Neutrino Experiment (DUNE), a leading-edge experiment for neutrino science and proton decay studies. This experiment, together with the facility that will support it, the Long Baseline Neutrino Facility (LBNF), will be an internationally designed, coordinated and funded program, hosted at Fermilab in Batavia, Illinois. The DUNE experimental facility will be sited deep underground (1.5km) at Sanford Underground Research Facility (SURF) in Lead, SD, and will become the deepest experimental facility operated by Fermilab. SNOLAB is a unique world-class international facility for deep underground scientific research. Located 2 km underground near Sudbury, Ontario, SNOLAB hosts a suite of surface facilities and laboratories. The science program at SNOLAB is primarily focused on subatomic and astroparticle physics, specifically the search for dark matter and neutrino studies. As the second-deepest underground lab facility, SNOLAB has gained considerable experience in deep underground scientific research operations. The purpose of this agreement is to leverage the unique capabilities of both Fermilab and SNOLAB to accomplish the following: Provide Fermilab with additional, direct experience in deep underground scientific research operations at SNOLAB to help improve the operational support for SURF. Provide SNOLAB with an experienced leader to serve as Interim Associate Director for Program Integration & Operations, while SNOLAB conducts its search for a permanent hire.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Cybersecurity Operational Research, Experimentation, Innovation, and Integration (COREII)

The Department of Energy’s Cybersecurity, Energy Security, and Emergency Response Office (CESER) has partnered with Idaho National Laboratory (INL) and energy companies to develop COREII. This research initiative aims to align with the national cybersecurity strategy, enhance the resilience of critical energy infrastructure, facilitate efforts to improve grid-enhancing technologies (GET) and major effects from other critical and emerging technologies, and to enable discovery of innovative solutions for emerging cybersecurity challenges

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Enabling Power System Transformation Globally: A System Operator Research Agenda for Bulk Power System Issues

The primary objective of a power system is to safely provide reliable energy services to society at an affordable cost. In many countries, this objective has been supplemented by another: meeting the energy demand with sustainable resources, which has culminated in the energy transition to low-carbon and zero-carbon energy systems. This transition, occurring rapidly around the world, is characterized by the increasing penetration of variable renewable energy (VRE), inverter-based resources (IBRs), and distributed energy resources (DERs).

costs↗
DOE OSTI2019

Durable aluminate toughened zirconate composite thermal barrier coating (TBC) materials for high temperature operation

Research on advanced thermal barrier coating (TBC) materials capable of operating beyond 1200°C has primarily focused on the rare earth zirconate pyrochlores, particularly gadolinium zirconate (Gd 2 Zr 2 O 7 – GZO). The drawback of this material is a significant reduction in durability due to a low fracture toughness. This study investigates utilization of a thermodynamically compatible gadolinia alumina perovskite (GdAlO 3 – GAP) toughening phase to improve the durability of GZO. Dense pellets were fabricated to assess the material properties with minimal microstructural influence. Thermal stability, elastic modulus, hardness, indentation fracture resistance and erosion durability were evaluated for GZO, GAP, and composite pellets containing 10, 30, and 50 wt.% GAP. It was demonstrated that GAP and GZO are thermodynamically compatible through 1600°C and thus capable of operating well beyond the limits of traditional 7 wt.% yttria stabilized zirconia (YSZ). Grain sizes are maintained due to a lack of diffusion, and thus microstructural stability is enhanced. The GAP fracture toughness was shown to be over 2X that of GZO while exhibiting a lower elastic modulus and similar hardness. The 50:50 GZO-GAP composite exhibited a 63% reduction in the absolute erosion rate, demonstrating the immense toughening capabilities of this system. The implications for composite TBCs utilizing this system are discussed, along with future research.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Criticality Safety Evaluation Project Development for University of California Berkely Nuclear Criticality Safety Pipeline Course

The Nuclear Criticality Safety Division at Lawrence Livermore National Laboratory (LLNL) has taken a unique approach to developing criticality safety evaluation topics in support of the University of California Berkeley criticality safety pipeline course. The evaluation topics are designed to go beyond the typical evaluation examples used for many training courses including vault storage and variations on storage arrays. These types of evaluations provide in-depth analysis into the fundamentals of criticality safety and are complex but may be far off from what a new criticality safety engineer may actually be evaluating. To provide more practical examples of criticality safety evaluation topics that are better fit for the knowledge level of a criticality safety engineer in-training, variations of current and future operations and research operations performed at LLNL are used as evaluation topics. Additionally, an emphasis on research is included in all evaluation topics as it allows students to take advantage of the concepts learned in class to apply them for process improvement, engineering equipment that is favorable for criticality safety, and negotiation tactics to work with operations personnel. The process used by LLNL to develop project topics for the pipeline course is provided in this paper. The intent is to provide an alternative technique for training students and potentially younger staff members in criticality safety on developing criticality safety evaluations.

42 ENGINEERING↗
DOE OSTI2022

Evaluation of Oak Ridge National Laboratory Health Physics Research Reactor Operation Data for Critical Benchmark Creation [Slides]

During the evaluation of Oak Ridge National Laboratory Health Physics Research Reactor operation data for critical benchmark creation, a detailed, functional SCALE model was built, and experimental data was evaluated for the creation of a critical benchmark. The estimated experimental uncertainty is about 3800 pcm, which is considered very high. The relative difference between expected and calculated keff values is about 1.5 %, also considered very high. It was concluded that a good quality critical benchmark worthy of the ICSBEP standards cannot be created from HPRR data in the present conditions. Locating the HPRR fuel to obtain an uncertainty on the density would aid in solving this issue.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Atmospheric Radiation Measurement Climate Research Facility Operations Quarterly Report October 1-December 31, 2015

Research Facility fixed and mobile research sites are collected and routed to the Data Management Facility (DMF) for processing in near-real-time. Instrument and processed data are then delivered approximately daily to the ARM Data Archive, where they are made freely available to the research community. For each instrument, ARM calculates the ratio of the actual number of processed data records received daily at the ARM Data Archive to the expected number of data records. The results are tabulated by 1) individual datastream, site, and month for the current year, and 2) site and fiscal year dating back to 1998.

Source record↗