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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Development of High Temperature (>700°C) Molten Salt Pump Technology for Generation 3 Solar Power Tower Systems

Bearings are required for long-shafted pumps historically used in concentrating solar thermal power applications. For molten chloride salts, bearings for such service conditions are not commercially available, nor has a design been demonstrated to work. Therefore, a project was sponsored by the Department of Energy’s Solar Energy Technologies Office for the development and demonstration of a submerged bearing for use in chloride salt pumps. This project’s tasks covered the tribological testing of candidate materials and the design, fabrication, testing, and post-test analysis of full-scale salt-compatible bearings. This work expands upon previous work. The effects of potential particulate in the salt were investigated through tribological bench testing. Through 11 tests, the MgO particulate size and concentration in a molten chloride salt were varied, and the effects on friction, wear rate, and wear characteristics were recorded. Novel journal bearings for chloride salt service were designed and fabricated based on these results. The bearings were of a relevant scale (i.e., for a 1.5 in. pump shaft) to demonstrate the technology with respect to further scale-up. The bearings were made of Haynes 244 and Yttria Partially Stabilized Zirconia. A custom bearing test rig, salt tanks, and associated infrastructure (e.g., heaters, tanks, transfer lines, gas flow control) were designed, procured, and installed. A few issues were encountered in the system fabrication process, resulting in delay of the project schedule. The system was successfully fabricated and assembled. Heating, cover gas, and pump motor systems were integrated into the control logic. This progress of the bearing test system represents a significant step forward towards demonstrating this promising technology. Nevertheless, the project ended before testing of the full-scale bearings could be performed.

14 SOLAR ENERGY↗
DOE OSTI2022

Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART)

This report contains key findings from a project titled Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART), which was carried out through a collaborative effort of a team of researchers from Texas A&M Engineering Experiment Station, Temple University, and Quanta Technology, LLC. The in-kind support came from OSIsoft (acquired by AVEVA), which provided their PI Historian software to demonstrate the use case of streaming PMU data. The first section of the report describes the project goals and objectives related to the development of Machine Learning (ML) models capable of detecting and classifying events by processing phasor measurements captured in the field by Phasor Measurement Units (PMUs). The data for this study was contributed by the utilities/ISOs from the Western and Eastern interconnects and ERCOT, further referred to as Interconnect B (IC B), Interconnect A (IC A), and Interconnect C (IC C), respectively. The approach that the BDSMART Research Team proposed and the key research tasks defined by the team are outlined in this section. The next section describes the technical approach. We first discuss the data constraints related to the PMU measurements and data interpretation constraints imposed by the data contributors. They provided neither the topological information of the grid nor PMU placement locations and captured recorded data at very few locations in the system with the reporting rate of either 30 or 60 fps. The recordings are mostly positive sequence voltage, frequency, and ROCOF, and in some limited cases, three-phase voltages and currents. We then reflect on the bad data issues that stem from poor recording practices and vague definitions of the PMU status bits to supposedly be used for bad data identification. Finally, the data discovery points to imprecise time stamps with incomplete event start/end time, as well as inconsistent and incomplete event labeling, which combined make the implementation of the data models using supervising learning quite challenging. Following the data discovery study, we hypothesize that because the IC B data has the most complete labels, we should focus our model development on that data and then test it on data from other interconnects. We also define the common metrics used to evaluate the results from the ML algorithm tests. We concluded this section by summarizing the common ML models we used and explaining how we implemented and tested them. The issues from this section are expanded in the Training Dataset Report from this project. The final section of this report deals with the accomplishments and conclusions. As the accomplishments, we formulate the problem we are solving and what is achieved by solving the problem. We then reflect on each of the analytics tools we developed and point out the performance of each tool when applied to solving the mentioned problems. We reference this work for further details to the papers we published on each tool. In the conclusions, we give recommendations on how to improve future PMU recording practices to facilitate the ML algorithm implementation and guidance for the future standardization work aimed at clarifying the ambiguities associated with the PMU status bits. We finally list future tasks that can bring about further improvements in the proposed algorithms. The issues from this section are expanded in the Training, and Test Dataset Report filed at the project completion date.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Big Adaptive Rotor Phase I (Final Report)

The Big Adaptive Rotor (BAR) project was initiate by DOE in 2018 with the goal of identifying novel technologies that can enable large (>100m) blades for low specific power (SP) turbines. Five distinct tasks were completed to achieve this goal: 1. Assess trends, impacts, and value of low-SP turbines, 2. Wind turbine blade cost reduction roadmap study, 3. Research and Development (R&D) opportunity screening, 4. Detailed design and analysis, and 5. Low-cost carbon fiber. These tasks were completed by the national lab team consisting of Sandia National Laboratories (SNL), the National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory (LBNL). The objective of Task 1 was to assess the historical trends of low-SP of onshore deployments, and to assess the impact and value of low-SP turbines. Analysis under this task showed that there is significant value for low-SP turbines, especially in markets where there is a higher saturation of wind energy on the grid. This has to do with the fact that low-SP turbines have increased capacity factors, and can contribute more reliable energy to the grid, even in lower wind conditions. This bodes well as higher renewable scenarios are likely in the coming years. Task 2 was a detailed analysis on the logistical challenges of deploying very large (>100m) onshore blade. This work was completed by experts at DNV-GL. The report looked at various ways to get around the current transportation constraints which are estimated to be around 75m in length. The report concluded that there are viable solutions to this issue including: segmented blades (which the industry is already pursuing), lighter than air (LTA) transportation, on-site manufacturing, and controlled bending of blades on rail. The final option was recommended for further analysis and study by DOE and the national labs because keeping a single piece blade reduces manufacturing and operations and maintenance (O&M) costs. Task 3 focused on identifying novel concepts that are capable of enabling a cost effective 5MW 206m rotor for onshore deployment. The findings from the first two tasks were considered in the analysis, in that the concepts identified must be able to overcome the transportation logistics challenges. Around 20 concepts were identified and evaluated by experts within the industry. Additionally, science and engineering challenges were identified for each concept. Based on these evaluations six concepts were deemed the most impactful and were selected for further analysis in Task 4. The concepts were: highly flexible rail transportable blades, downwind rotors, distributed aerodynamic control (DAC) devices, inflatable blade, bi-wing blade, and 4/5 bladed rotors. Task 4 conducted detailed design, optimization, and analysis on the selected BAR concepts. A modeling gaps analysis was conducted, and modeling improvements were implemented that allowed for the study and design of the novel concepts. The BAR team established a set of baseline designs by which to compare the selected designs through a technoeconomic analysis. It was found that the highly flexible rail transportable blade, the downwind rotor, and the DAC devices have the most promise to deliver the BAR targets. A Phase II for BAR has been proposed to further mature these concepts and address the open science and engineering challenges identified in Task 3. Task 5 conducted research on optimized carbon fiber materials that were used throughout the BAR Phase I project. Overall, the BAR project has identified low-SP turbines as important to continued LCOE reductions for onshore turbines. Furthermore, the project has identified viable solutions to the technical and logistical challenges to realizing these goals. The most promising technologies that were identified in Phase I of the project will be further matured and de-risked in Phase II of the BAR project.

17 WIND ENERGY↗
DOE OSTI2016

The report of Task Group 100 of the AAPM: Application of risk analysis methods to radiation therapy quality management

The increasing complexity of modern radiation therapy planning and delivery challenges traditional prescriptive quality management (QM) methods, such as many of those included in guidelines published by organizations such as the AAPM, ASTRO, ACR, ESTRO, and IAEA. These prescriptive guidelines have traditionally focused on monitoring all aspects of the functional performance of radiotherapy (RT) equipment by comparing parameters against tolerances set at strict but achievable values. Many errors that occur in radiation oncology are not due to failures in devices and software; rather they are failures in workflow and process. A systematic understanding of the likelihood and clinical impact of possible failures throughout a course of radiotherapy is needed to direct limit QM resources efficiently to produce maximum safety and quality of patient care. Task Group 100 of the AAPM has taken a broad view of these issues and has developed a framework for designing QM activities, based on estimates of the probability of identified failures and their clinical outcome through the RT planning and delivery process. The Task Group has chosen a specific radiotherapy process required for “intensity modulated radiation therapy (IMRT)” as a case study. The goal of this work is to apply modern risk-based analysis techniques to this complex RT process in order to demonstrate to the RT community that such techniques may help identify more effective and efficient ways to enhance the safety and quality of our treatment processes. The task group generated by consensus an example quality management program strategy for the IMRT process performed at the institution of one of the authors. This report describes the methodology and nomenclature developed, presents the process maps, FMEAs, fault trees, and QM programs developed, and makes suggestions on how this information could be used in the clinic. The development and implementation of risk-assessment techniques will make radiation therapy safer and more efficient.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Modeling Mesoscale Processes of Scalable Synthesis (Final Report)

The main objective of the center is to develop tools that can help for the understanding of equilibrium and non-equilibrium properties of nanoparticles in aqueous electrolytes. To achieve this goal, we need to develop new computational methodologies that can integrate molecular level description such as the electronic structure analysis to mesoscale description such as generalized hydrodynamics. The challenge is to develop systematic coarse graining techniques that can adaptively choose the level of description needed for the particular task. For example, if bonding breaking is involved, then one should use appropriate models from quantum mechanics to accurately model the time scale and molecular mechanism for the breaking process. However, to model transport process or the process of self-assembly, much less detailed models can be used. There are two main components to this task. One is to develop accurate models that bridge different levels of description. The classical example is the QM/MM model that bridges quantum mechanics and molecular mechanics for studying chemical reactions of large molecules. This work was awarded the Nobel prize this year. For our purpose, we also need to develop methods that bridge molecular and continuum levels of description. Another main task is to develop systematic coarse-graining methods that can give rise to accurate mesoscale and macroscale models, starting from more detailed models at the atomic or molecular scale. None of these ideas are new. By now they have been fashionable topics for quite some time. But neither problem is satisfactorily resolved. The main problem is that uncontrolled approximations are used. As a result, we have very little idea about the validity and accuracy of these models. The main purpose of the center is to exploit the Mori-Zwanzig formalism to achieve the goals stated above. The Mori-Zwanzig formalism is a general tool for eliminating degrees of freedom from existing models. What is attractive about this formalism is its generality. The flip side is that it is also somewhat of a tautology. In order to make it a practical tool, one has to make approximations and this is where the trouble comes. Instead of focusing on Mori-Zwanzig formalism, the PI proposes to study the closely related renormalization group formalism (RG). Like Mori-Zwanzig, RG is a general strategy for eliminating small scale degrees of freedom in a model. Unlike Mori-Zwanzig, RG has the advantage that at least for some problems, one can write a PDE (partial differential equation) type of model for the exact RG flow, without any approximation. This gives us a solid starting point for discussing and analyzing approximations. The PI studied approximate RG flows for turbulent diffusion and related problems. However, extending it to more practical problems proved to be hard. The second line that the PI has pursued is to develop special numerical algorithms for studying particularly important events for dynamics processes in meso-scale systems. The PI succeeded in doing so for the problem of understanding phase transition in metallic systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Survey of Relevant Data from the MSRP to Guide Development of MSR Chemistry Modeling Benchmarks

The Multiphysics Applications technical area of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program is tasked with assessing, demonstrating, and applying NEAMS tools in solving multiphysics problems of nuclear reactors, such as liquid-fueled molten salt reactors (MSRs), which are the focus of this report. MSRs are actively being pursued as a potential candidate for power and heat generation by the nuclear industry. However, the inherent multiphysics nature of liquid-fueled MSRs, stemming from the strong interrelationship of neutronics, thermal fluids, and chemistry phenomena, provides unique challenges in modeling and simulation (mod/sim). Therefore, it will be important to develop mod/sim tools with varying types of multiphysics coupling that depend on the problem. The current work is focused on the initiation and development of MSR chemistry modeling benchmarks useful for validating current and potential future NEAMS tools. Development of such benchmarks include the following actions: 1) Summarize available chemistry data from the Oak Ridge National Laboratory (ORNL) MSR Program (MSRP) including operation of the Molten Salt Reactor Experiment (MSRE) and design studies for the Molten Salt Breeder Reactor (MSBR) concept; 2) Recommend simulation problems in MSR chemistry mod/sim based on (1); 3) Assess the current state of NEAMS tools that may support (2); 4) Demonstrate and validate the capabilities of the NEAMS tools in (3) while providing iterative feedback on future code development activities. The objective of this report is to initiate this effort by completing actions (1) and (2), which are discussed in Section 2. An overview of the relevant available MSRE experimental data is provided with examples of how this data may be useful in chemistry mod/sim problems, with the caveat that most of this data is over 50 years old, therefore some problem details as well as uncertainty estimates are often not provided. In Section 3, the current state of NEAMS tools is assessed for potential use in these mod/sim problems, with considerations for future code development activities, supporting action (3). Future work supporting this project under NEAMS may include a deeper dive into the specific phenomena discussed here including tasks such as the compilation of additional available data, updates in code development activities, and ultimately the demonstration and validation of these tools, supporting action (4).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Inductively Driven, 3D Liner Compression of a Magnetized Plasma to Megabar Energy Densities

To take advantage of the smaller scale, higher density regime of fusion an efficient method for achieving the compressional heating required to reach fusion gain conditions must be found. What is proposed is a more flexible metallic liner compression scheme that minimizes the kinetic energy required to reach fusion. It is believed that it is possible to accomplish this at sub-megajoule energies. This however will require operation at very small scale. To have a realistic hope of inexpensive, repetitive operation, it is essential to have the liner kinetic energy under a megajoule which allows for the survivability of the vacuum and power systems. At small scale the implosion speed must be reasonably fast to maintain the magnetized plasma (FRC) equilibrium during compression. For limited liner kinetic energy, it becomes clear that the thinnest liner imploded to the smallest radius consistent with the requirements for FRC equilibrium lifetime is desired. The proposed work is directed toward accomplishing this goal. Typically an axial (Z) current is employed for liner compression. There are however several advantages to using a θ-pinch coil. With the θ-pinch the liner currents are inductively driven which greatly simplifies the apparatus and vacuum system, and avoids difficulties with the post implosion vacuum integrity. With fractional flux leakage, the foil liner automatically provides for the seed axial compression field. To achieve it with optimal switching techniques, and at an accelerated pace however will require additional funding. This extra expense is well justified as the compression technique that will be enabled by this funding is unique in the ability to implode individual segments of the liner at different times. This is highly advantageous as the liner can be imploded in a manner that maximizes the energy transfer to the FRC. Production of shaped liner implosions for additional axial compression can thus be readily accomplished with the modified power modules. The additional energy and switching capability proposed will thus provide for optimal utilization of the liner energy. The following tasks were outlined for the three year effort: (1) Design and assemble the foil liner compression test structure and chamber including the compression bank and test foils [Year 1]. (2) Perform foil liner compression experiments and obtain performance data over a range on liner dimensions and bank parameters [Year 2]. (3) Carry out compression experiments of the FRC plasma to Megagauss fields and measure key fusion parameters [Year 3]. (4) Develop numerical codes and analyze experimental results, and determine the physics and scaling for future work [Year 1-3]. The principle task of the project was to design and assemble the foil liner FRC formation chamber, the full compression test structure and chamber including the compression bank. This task was completed successfully. The second task was to test foils in the test facility constructed in year one and characterize the performance obtained from liner compression. These experimental measurements were then compared with analytical predictions, and numerical code results. The liner testing was completed and compared with both the analytical results as well as the code work performed with the 3D structural dynamics package of ANSYS Metaphysics®. This code is capable of modeling the dynamic behavior of materials well into the non-linear regime (e.g. a bullet hit plate glass). The liner dynamic behavior was found to be remarkably close to that predicted by the 3D structural dynamics results. Incorporating a code that can also include the magnetics and plasma physics has also made significant progress at the UW. The remaining test bed construction and assembly task is was completed, and the FRC formation and merging experiments were carried out as planned. The liner compression of the FRC to Megagauss fields was not performed due to not obtaining a sufficiently long lived FRC during the final year of the grant. Modifications planned to correct this deficiency included a larger FRC source as well as a much larger liner driver energy storage system. Due to discontinuation of the grant neither of these improvements were carried out.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Final Report: Modifications and Optimization of the Organic Rankine Cycle to Improve the Recovery of Waste Heat

This research and development (R&D) project exemplifies a shared public private commitment to advance the development of energy efficient industrial technologies that will reduce the U.S. dependence upon foreign oil, provide energy savings and reduce greenhouse gas emissions. The purpose of this project was to develop and demonstrate a Direct Evaporator for the Organic Rankine Cycle (ORC) for the conversion of waste heat from gas turbine exhaust to electricity. In conventional ORCs, the heat from the exhaust stream is transferred indirectly to a hydrocarbon based working fluid by means of an intermediate thermal oil loop. The Direct Evaporator accomplishes preheating, evaporation and superheating of the working fluid by a heat exchanger placed within the exhaust gas stream. Direct Evaporation is simpler and up to 15% less expensive than conventional ORCs, since the secondary oil loop and associated equipment can be eliminated. However, in the past, Direct Evaporation has been avoided due to technical challenges imposed by decomposition and flammability of the working fluid. The purpose of this project was to retire key risks and overcome the technical barriers to implementing an ORC with Direct Evaporation. R&D was conducted through a partnership between the Idaho National Laboratory (INL) and General Electric (GE) Global Research Center (GRC). The project consisted of four research tasks: (1) Detailed Design & Modeling of the ORC Direct Evaporator, (2) Design and Construction of Partial Prototype Direct Evaporator Test Facility, (3) Working Fluid Decomposition Chemical Analyses, and (4) Prototype Evaluation. Issues pertinent to the selection of an ORC working fluid, along with thermodynamic and design considerations of the direct evaporator, were identified. The FMEA (Failure modes and effects analysis) and HAZOP (Hazards and operability analysis) safety studies performed to mitigate risks are described, followed by a discussion of the flammability analysis of the direct evaporator. A testbed was constructed and the prototype demonstrated at the GE GRC Niskayuna facility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

HEP Software Foundation Community White Paper Working Group – Visualization

In modern High Energy Physics (HEP) experiments visualization of experimental data has a key role in many activities and tasks across the whole data chain: from detector development to monitoring, from event generation to reconstruction of physics objects, from detector simulation to data analysis, and all the way to outreach and education. In this paper, the definition, status, and evolution of data visualization for HEP experiments will be presented. Suggestions for the upgrade of data visualization tools and techniques in current experiments will be outlined, along with guidelines for future experiments. This paper expands on the summary content published in the HSF \emph{Roadmap} Community White Paper~\cite{HSF-CWP-2017-01}

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Learning Latent Interactions for Event Identification via Graph Neural Networks and PMU Data

Phasor measurement units (PMUs) are being widely installed on power systems, providing a unique opportunity to enhance wide-area situational awareness. One essential application is the use of PMU data for real-time event identification. However, how to take full advantage of all PMU data in event identification is still an open problem. Thus, we propose a novel method that performs event identification by mining interaction graphs among different PMUs. The proposed interaction graph inference method follows an entirely data-driven manner without knowing the physical topology. Moreover, unlike previous works that treat interactive learning and event identification as two different stages, our method learns interactions jointly with the identification task, thereby improving the accuracy of graph learning and ensuring seamless integration between the two stages. Moreover, to capture multi-scale event patterns, a dilated inception-based method is investigated to perform feature extraction of PMU data. To test the proposed data-driven approach, a large real-world dataset from tens of PMU sources and the corresponding event logs have been utilized in this work. We report numerical results validate that our method has higher classification accuracy compared to previous methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Lab-Based Measurement of Remediation Techniques for Radiation Portal Monitors (Initial Report)

Radiation Portal Monitors (RPM) deployed by the Second Line of Defense (SLD) are known to be sensitive to the natural environmental radioactive background. There are several techniques used to mitigate the effects of background on the monitors, but since the installation environments can vary significantly from one another the need for a standardized, systematic, study of remediation techniques was proposed and carried out. This study is not meant to serve as the absolute last word on the subject. The data collected are, however, intelligible and useful. Some compromises were made, each of which will be described in detail. The hope of this initial report is to familiarize the SLD science teams with ORNL's effort to model the effect of various remediation techniques on simple, static backgrounds. This study provides a good start toward benchmarking the model, and each additional increment of data will serve to make the model more robust. The scope of this initial study is limited to a few basic cases. Its purpose is to prove the utility of lab-based study of remediation techniques and serve as a standard data set for future use. This importance of this first step of standardization will become obvious when science teams are working in parallel on issues of remediation; having a common starting point will do away with one category of difference, thereby making easier the task of determining the sources of disagreement. Further measurements will augment this data set, allowing for further constraint of the universe of possible situations. As will be discussed in the 'Going Forward' section, more data will be included in the final report of this work. Of particular interest will be the data taken with the official TSA lead collimators, which will provide more direct results for comparison with installation data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Generative large language models for predictive maintenance planning

Maintenance planning and the generation of necessary components for tasks can prove time-consuming and complex. Automating the creation of recurring or similar tasks by leveraging previous planning packages and data, while uncovering insights to automate planning package generation, presents an opportunity to conserve valuable time and resources. This work aims to harness the textual and probabilistic capabilities of large language models (LLMs) to automate the generation of planning packages. Utilizing diverse data sources ranging from raw data to handwritten text, both singular and collaborative LLMs are trained and tested. Results demonstrate their capability to generate essential planning package components, effectively replicating the statistical patterns in the data. This demonstrates the use of these tools inside a digital asset for automated planning. This work outlines a methodology for constructing datasets, a training suite, and evaluation methods for LLM-based textual and conversational planning tools utilized in an asset digital twin. Results indicate that the fine-tuned models generate estimated planning information within the statistical ranges observed in real maintenance data. The models achieve high accuracy (>90%) in document question-answering and instruction generation tasks. Furthermore, the conversational retrieval-augmented generation (RAG) assistant system achieves 100% document retrieval accuracy, while conversational information capture exceeds 98% across the majority of work-package assistant modules.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Application and Removal of Strippable Coatings via Remote Platform - 13133

Florida International University's (FIU's) Applied Research Center is currently supporting the Department of Energy (DOE) Environmental Management Office of D and D and Facility Engineering program. FIU is supporting DOE's initiative to improve safety, reduce technical risks, and limit uncertainty within D and D operations by identifying technologies suitable to meet specific facility D and D requirements, assessing the readiness of those technologies for field deployment, and conducting feasibility studies and technology demonstrations of selected technologies and working with technology vendors to optimize the design of their current technologies to accomplish dangerous and demanding tasks during D and D operations. To meet one identified technology gap challenge for a technology to remotely apply strippable coatings, fixatives and decontamination gels, FIU identified and performed an initial demonstration of an innovative remote fixative sprayer platform from International Climbing Machines (ICM). The selected technology was demonstrated spraying fixative products at the hot cell mockup facility at the Applied Research Center at FIU in November 2008 under cold (non-radioactive) conditions. The remotely controlled platform was remotely operated and entered the facility and sprayed a fixative onto horizontal and vertical surfaces. Based on the initial FIU demonstration and the specific technical requirements identified at the DOE facilities, a follow-up demonstration was expanded to include strippable coatings and a decontamination gel, which was demonstrated in June 2010 at the ICM facility in Ithaca, NY. This second technology evaluation documented the ability of the remote system to spray the selected products on vertical stainless steel and concrete surfaces to a height of 3 meters (10 feet) and to achieve sufficient coverage and product thickness to promote the ability to peel/remove the strippable coatings and decontamination gel. The next challenge was to determine if a remote platform could be used to remove the strippable coatings and decontamination gels. In 2012, FIU worked with the technology provider, ICM, to conduct feasibility and trade studies to identify the requirements for the remote removal of strippable coatings or decontamination gels using the existing remote controlled platform. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Denoising diffusion probabilistic models for generative alloy design

Inverse material design is an extremely challenging optimization task made difficult by, in part, the highly nonlinear relationship linking performance with composition. Quantitative approaches have improved significantly owing to advances in high throughput experimentation and computational thermodynamics. However, existing physics-based tools are mostly forward models; input a chemistry and obtain a prediction. More recently the materials community has leveraged advances in the machine learning community to establish novel inverse design frameworks. Very recently denoising diffusion probabilistic models have been shown to be extremely powerful generators producing synthetic data of various modalities e.g. images, text, audio, tables, etc.. In this work a novel framework for alloy design and optimization is proposed leveraging these class of models. Five key generative tasks are demonstrated (1) unconditional generation (2) composition conditioned generation (3) property conditioned generation (4) multi-feedstock conditioned generation and (5) generative optimization. These methods were tested on three case studies: high entropy alloy design, superalloy binder jet additive manufacturing, and in-situ dual-feedstock wire-arc additive manufacturing. Results indicate that the established models are extremely flexible, expressive, and robust. The architecture’s flexibility and training procedure empower the model to learn complex intra-compositional and composition-property relationships. Furthermore, the probabilistic nature of these models makes them well suited for addressing solution non-uniqueness and tackling uncertainty quantification tasks. While the fidelity and quantity of the underlying training data is paramount, we envision that future alloy design frameworks will make extensive use of these kinds of machine learning models as “search” tools bolstering the utility of experimental and computational approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Budget Period 2 Summary Report Part 3: Hywind Maine Project

This project was performed under the Work for Others—Funds in Agreement FIA-14-1793 between Statoil and the Alliance for Sustainable Energy, manager and operator of the National Renewable Energy Laboratory (NREL). To support the development of a 6-MW spar-mounted offshore wind turbine, NREL performed tasks on behalf of Statoil in the following three categories: 1. Design and analysis 2. Wake modeling 3. Concept resource assessment. This document summarizes the work performed in Work Package (WP) 3, where the spatial variability and influence that relevant parameters have on levelized cost of energy (LCOE) were analyzed. The study allows Statoil to identify areas of interest for floating wind technology and the Hywind concept in particular. This report describes the results of a study that NREL conducted to provide targeted insight into the United States (U.S.) offshore wind resource area that Statoil can use for taking strategic decisions about how to commercialize and market the company’s Hywind technology. The report centers on a new spatio-economic methodology that NREL has developed to assess how variability in spatial parameters can influence levelized cost of energy (LCOE) for different technologies. The method combines wind plant performance modeling, economic modeling, and national geospatial data layers to estimate the cost of potential projects using Hywind technology, considering the following parameters: • Water depth • Possible inshore assembly areas • Wind resource • Existing grid features and potential connection points • Wave regime • Environmentally sensitive areas • Seabed conditions • Competitive use areas • Prospective staging ports The scope of the study covers the major offshore regions within the contiguous United States, including the Atlantic Ocean, Gulf of Mexico, Pacific Ocean, and the Great Lakes. The spatio-economic assessment extends to 92 km (50 nm) off of the nearest land mass, consistent with the available data on wind characteristics. The study is restricted to those locations that meet the depth criteria for Hywind technology—defined as water depths between 100 m to 1,000 m—and only considered sites with net capacity factors that exceed 30%.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

DE-NE0000724 - Research Performance Final Report - Investigation of Thermal Aging Effects on the Evolution of Microstructure and Mechanical Properties of Cast Duplex Stainless Steels

This report details the research activities carried out under DOE-NEUP award number DE-NE0000724 concerning the evolution of structural and mechanical properties during thermal aging of CF–3 and CF–8 cast duplex stainless steels (CDSS). The overall objective of this project was to use state-of-the-art characterization techniques to elucidate trends and phenomena in the mechanical and structural evolution of cast duplex stainless steels (CDSS) during thermal aging. These steels are commonly used as structural materials in commercial light water nuclear power plants, undergoing aging for decades in operation as cooling water pipes, pump casings, valve bodies, etc. During extended exposure to these conditions, CDSS are known to undergo a change in mechanical properties resulting in a loss of ductility, i.e. embrittlement. While it is generally accepted that structural changes within the ferrite phase, such as decomposition into iron (Fe)-rich and chromium (Cr)-rich domains, lead to the bulk embrittlement of the steels, many questions remain as to the mechanisms of embrittlement at multiple length scales. This work is intended to shed insight into the atomic level composition changes, associated kinetic mechanisms, and effects of changing phase structure on micro- and nano-scale deformation that lead to loss of impact toughness and tensile ductility in these steels. In general, this project provides a route to answer some of these major questions using techniques such as 3-dimensional (3-D) atom probe tomography (APT) and real-microstructure finite element method (FEM) modeling, which were not readily available when these steels were originally selected for service in light water reactors. Mechanical properties evaluated by Charpy V-notch impact testing (CVN), tensile testing, and microhardness and nanohardness measurements were obtained for each condition and compared with the initial baseline properties to view trends in deformation behavior during aging. Concurrent analysis of the microstructure and nanostructure by atom probe tomography (APT) and transmission electron microscopy (TEM) provide mechanistic insight into the kinetic and mechanical behavior occurring on the nano-scale. The presence and morphology of the ferrite, austenite, and carbide phases have been characterized, and formation of new phases during aging, including spinodal decomposition products (α- and α'-ferrite) and G-phase, have been observed. The mechanical and structural characterization have been used to create accurate FEM models based on the real micro- and nano-structures of the systems. These models provide new insight into the local deformation behavior of these steels and the effects of each individual phase (including ferrite, austenite, carbides, and spinodal decomposition products) on the evolving bulk mechanical behavior of the system. The project was divided into three major tasks: 1. Initial Microstructure and Mechanical Property Survey and Initiate Heat Treatment; 2. Microstructural Characterization and Mechanical Property Testing During Aging; and 3. Microstructure-based Finite Element Modeling. Each of these tasks was successfully executed, resulting in reliable data and analysis that add to the overall body of work on the CDSS materials. Baseline properties and aging trends in mechanical data confirm prior observations and add new insights into the mechanical behavior of the steels. Structural characterization on multiple length scales provides new information on phase changes occurring during aging and sheds light on the kinetic processes occurring at the atomic scale. Furthermore, a combination of mechanical testing and microstructural characterization techniques was utilized to design FEM models of local deformation behavior of the ferrite and austenite phases, providing valuable new information regarding the effects of each of the microstructural components on the hardening and embrittlement processes. The data and analysis presented in this report and the publication associated with this project (§V) increase the understanding of aging and deformation in CF–3 and CF–8 steels. These results provide valuable information that can be utilized to aid in making informed decisions regarding the ongoing use of these steels in commercial nuclear infrastructure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Quantitative near-field water–air spray measurements at elevated pressures by neutron radiography imaging

Extensive experimental research on high-pressure spray has been conducted for decades to deepen our understanding and optimize its use in transportation, aviation, and propulsion applications; however, the near-field and in-nozzle flow characteristics are not fully understood. Dense near-field spray is among the most challenging diagnostic tasks since light is severely scattered and diffused by the liquid droplets and columns. In this work, the near-field spray and in-nozzle flow characteristics of an aeration nozzle at elevated pressures were characterized by neutron radiography imaging at the Oak Ridge National Laboratory High Flux Isotope Reactor. Neutron imaging benefits via strong penetration depths for some metals (i.e., aluminum, lead, and steel) and is sufficiently sensitive to detection of light elements, especially for hydrogen-based molecules, due to the large incoherent scattering cross section of neutrons. Both two-dimensional snapshots of the near-field spray and a three-dimensional tomographic scan of the nozzle geometry and in-nozzle water were obtained. This work provides new quantitative characterization of practical metal nozzle geometry for accurate boundary conditions, internal flow patterns inside the nozzle, and high-pressure spray flows. In conclusion, the findings may be used to improve performance and operating conditions of transportation vehicles and propulsion systems.

42 ENGINEERING↗
DOE OSTI2013

Empirical Correction of Crosstalk in a Low-Background Germanium γ–γ Analysis System

ABSTRACT The Pacific Northwest National Laboratory is currently developing a custom software suite capable of automating many of the tasks required to accurately analyze coincident signals within gamma spectrometer arrays. During the course of this work, significant crosstalk was identified in the energy determination for spectra collected with a new low-background intrinsic germanium (HPGe) array at PNNL. The HPGe array is designed for high detection efficiency, ultra-low-background performance, and sensitive gamma gamma coincidence detection. The first half of the array, a single cryostat containing 7 HPGe crystals, was recently installed into a new shallow underground laboratory facility. This update will present a brief review of the germanium array, describe the observed crosstalk, and present a straight-forward empirical correction that significantly reduces the impact of this crosstalk on the spectroscopic performance of the system.

coincidence↗