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At least 37 records · Page 2

Business Case Analysis for Artificial Intelligence-Large Language Model Technology Integration

AI-assisted processes are expected to enhance operational efficiency and improve decision-making, supporting the long-term economic viability of nuclear power plants. However, detailed business analyses of AI-generated cost savings are rarely performed. Given the recent industry interest in Large Language Model (LLM), the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program has conducted a comprehensive business case analysis of LLM Artificial Intelligence (AI) implementation in nuclear plant engineering workflows. The research employed three complementary business case approaches to evaluate impact of an LLM, using three representative engineering processes as use-cases: Boric Acid Corrosion (BAC) Evaluations, Maintenance Rule Evaluations, and 10 CFR 50.59 Screenings. Through detailed workload analyses and structured interviews, the study quantified significant efficiency improvements ranging from 11% to 59% across these processes. The research further considers how these efficiency gains could translate into tangible reliability improvements through enhanced engineering capacity. Analysis of historical plant trip data indicates that enabling engineers to focus on proactive reliability activities could provide substantial financial benefits through avoided outages, potentially generating greater value than the direct efficiency improvements alone. By documenting successful applications, implementation challenges, and strategic opportunities, this research provides nuclear utilities with a practical framework for evaluating the value of AI technology to support long-term operations through advanced digital technologies.

97 MATHEMATICS AND COMPUTING↗

NREL Fleet Analysis Support Through Technology Integration Collaboration

This study leveraged the partnership between the United States Department of Energy's (DOE) Clean Cities Coalition Network and the Association for the Work Truck Industry (NTEA) to launch a vehicle and fleet analysis project that assisted fleets in identifying opportunities to save energy, improve efficiency, reduce costs, and meet environmental goals via short term data logging and analysis. The National Renewable Energy Laboratory (NREL) sought to establish a process that included initial data acquisition, provided data storage, and developed analytic methods to inform fleets of areas of opportunity based on approximately 30 days of in use vehicle performance data. However, long-term the project will require ongoing funding to fully develop and maintain the data sharing platform and to produce more complex analysis.

33 ADVANCED PROPULSION SYSTEMS↗

Adaptable Technology Integration for Enhanced Worker Safety and Efficiency within the SPD Gloveboxes [Slides]

Surplus Plutonium Disposition (SPD) Overview: (1) Application Background – Location: Savannah River Site, Aiken, South Carolina – High backlog of plutonium material to process – Parallel lines of gloveboxes – Highly manual operations requiring full PPE and reader/worker steps; (2) Development Scope – Development of automated processes and opportunities to provide robust engineering design alternatives for baseline design that would meet process improvement goals.

61 RADIATION PROTECTION AND DOSIMETRY↗

Integrating 5G Technology for Improved Process Monitoring and Network Slicing in ICS

Industrial Control Systems (ICS) are crucial for monitoring physical processes that support essential cyber-enabled services like power generation. The use of proprietary communication and lack of effective intrusion detection mechanisms pose constraints for efficient operation. Therefore, there is a need to modernize these systems with decentralized technologies like Edge Computing and 5G. However, integrating 5G and Edge Computing into large-scale ICS networks presents implementation and performance challenges. To address these challenges, this paper proposes an integrated ICS architecture that combines 5G and Edge Computing technologies with traditional ICS protocols. The objective is to minimize implementation and operational difficulties while improving the monitoring of physical processes and enabling robust intrusion detection. The proposed architecture outlines the necessary components, services, and communication protocols required for the integration of 5G and Edge Computing.

Aguayo, Jared M.↗

System-on-chip integrated circuit technology applications on the DIII-D tokamak for multi-field measurements

Several mm-wave diagnostics on the DIII-D tokamak provide multi-scale and multi-dimensional measurements of plasma profile evolution and turbulence fluctuations. Mm-wave fusion plasma diagnostics that adopt system-on-chip integrated circuit technology can provide better space utilization, flexible installation, and improved sensitivity. In order to further extend this technology for additional fusion facilities with a higher toroidal magnetic field, V-band (55–75 GHz) and F-band (90–140 GHz) chips for Microwave Imaging Reflectometer (MIR) and Electron Cyclotron Emission Imaging (ECEI) instruments are developed and tested in the Davis Millimeter Wave Research Center (DMRC). Current measurement data show that correlation between these SoC-based diagnostic instruments with other state-of-the-art diagnostics enables co-located multi-field turbulence fluctuation measurement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Hanford Tank Waste Technology Development Integration and Innovation Synergy

The Chief Technology Office (CTO) within Hanford Tank Waste Operations & Closure (H2C) identifies technology development needs and develops solutions for tank waste treatment. One key element of the technology development (TD) program is the annual Technology Development Integrated Coordination (TDIC) meeting series. The main goal of these meetings is to inform the National Laboratories and other entities of the needs identified by the end users of the technology. In turn, the meetings provide an opportunity for National Laboratories and others to provide insight into potential solutions. This dynamic facilitates dialogues that frequently identify not only new, innovative approaches, but also enhancements to ongoing technology development projects.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Real Time-Optimal Power Flow-Based Distributed Energy Resource Management System (DERMS)

This project aims to promote lab-proven clean energy technology to commercially scalable versions of the technology, integrate the technology with broader systems, provide extended performance data, and validate the manufacturability and reliability of the technology. The lab-proven technology, RT-OPF DERMS, was developed and validated through previous U.S. Department of Energy-funded efforts, including Advanced Research Projects Agency-Energy funding under the Network Optimized Distributed Energy Systems program and Holy-Cross Energy High Impact Project. In the Advanced Research Projects Agency-Energy Network Optimized Distributed Energy Systems project, the RT-OPF DERMS was developed and implemented in multiple hardware platforms, demonstrating its performance and capabilities in the lab and field environments. The technology was also evaluated and matured via a participation in the U.S. Department of Energy I-Corps program, whose goal is to pair teams of researchers with industry mentors for an intensive 2-month training in which the researchers define technology value propositions, conduct customer discovery interviews, and develop viable market pathways for their technologies. These activities indicate the high technology maturity and Technology Readiness Level of the RT-OPF DERMS.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Evaluation of Heat Exchanger Technology for Integrated Energy System: Methodology and Preliminary Application

This report proposes a novel heat exchanger evaluation method, based on integrated QFD-AHP technique, to support strategic optimal selection of heat exchanger (HX) technology for integrated energy systems. The term “optimal selection” is defined as selecting a product (i.e., HX) that best meets various aspects of end user demand, including both technical and economic requirements. Compared to previous HX evaluation methods, the proposed approach allows decision makers to explicitly take into account the practical demand of customers (i.e., HX end users) which may vary depending on the HX application target. In addition, the proposed evaluation method can be used not only for high-level decisions to select HX type, but also for low-level decisions such as the selection of the key components including HX material or heat transfer fluid. The focus of this study is to describe the new HX evaluation method and to illustrate the overall HX evaluation and selection processes using the three nuclear heat application cases that represent the thermal integration between advanced nuclear reactors and industrial processes. As a preliminary study, three different types of HX, i.e., shell-and-tube heat exchanger, printed circuit heat exchanger, and heat pipe heat exchanger, were compared.

42 ENGINEERING↗

Microfabricated Devices and Ion Trapping Capabilities

Next generation ion traps will likely need to support tens if not hundreds of ions in order to achieve several logical qubits. As we scale to those sizes, the same problems we face now – rf dissipation, control I/O, and optical access – will only grow and become more complicated. While many of these challenges can potentially be solved with technology integration, independently researching the feasibility of that integration and other solutions may help reduce the time and risk in scaling up to larger traps, by testing on smaller less complex devices. We should also consider other fabrication techniques that may help scale to larger devices, such as: through-substrate-vias (TSVs), different metal coatings, exotic rf routing, on chip laser sources, or even a secondary macroscopic trap to reload ions from. To have these technologies ready for full scale integration when we need them, ion traps with some of these capabilities need to be produced now. Developing the rigorous fabrication methods for producing reliable traps takes time and experimentation. We propose developing larger ion traps and reliable integrated technology in conjunction to make both available faster.

36 MATERIALS SCIENCE↗

Development of an Assessment Methodology That Enables the Nuclear Industry to Evaluate Adoption of Advanced Automation

Nuclear power has a crucial role in providing safe, reliable, and economical carbon-free electricity for today and the future. For continued operation, many of the existing United States nuclear power plants will begin the subsequent license renewal process for extending their operating license periods. As plants extend their expected operating lifetimes, there is a significant opportunity to modernize. These plants have a much stronger business case with these extended mission periods to modernize and significantly enhance their economic viability in current and future energy markets by implementing digital technologies that support innovation, efficiency gains, and business-model transformation. Ensuring continued safety and reliability is crucial. Transformative digital technologies—including automation—that fundamentally change the concept of operation for the nuclear power plant operating model requires a critical focus on the human and technology integration element. Further, the nuclear industry has historically been reluctant to modernize due to having a risk adverse culture and lack of clarity for a transformative new state vision (Joe & Remer, 2019; Thomas et al., 2020). Common barriers include (1) the perceived value and return on investment (ROI) of digital technology, (2) the perceived risk associated with licensing, regulatory, and cybersecurity, and (3) insufficient guidance for performing digital modifications to power generation systems. This work presents a methodology to address these barriers and support the industry in adopting advanced automation and digital technology through developing a transformative vision and implementation strategy that will address the human and technology integration element. This research leverages previous LWRS Program and industry results. It draws specifically on previous LWRS Program research in the areas of advanced alarm systems, computer-based procedures, model informed decision support, and advanced human-system interface displays (e.g., overviews and task-based). The modernization methodology can be used to guide transformative thinking when integrating a set of vendor-specific capabilities to support a new concept of operations and a utility’s end-state vision. The results of this research are organized into six major sections: - Section 1 introduces the need for supporting large-scale digital modifications that will renew the technology base for extended operating life beyond 60 years - Section 2 describes the challenges that the nuclear industry is enduring with modernizing. - Section 3 summarizes the primary standards and guidance. - Section 4 presents earlier work from the LWRS Program regarding the development of a transformative conceptual design for an advanced control room of a hybrid plants. - Section 5 presents a methodology that is designed at addressing the challenges in the industry today in achieving a transformative new state vision and concept of operations. - Conclusions and next steps of this research are provided in Section 6.

99 GENERAL AND MISCELLANEOUS↗

Technology, technology, technology: An integrated assessment of deep decarbonization pathways for the Canadian oil sands

As a party to the Paris Agreement, Canada has an ambitious climate target of net-zero emissions by 2050. The country also holds the world's third largest oil reserves in the Alberta oil sands. Given increasing emissions from the oil sands sector, achieving Canada's net-zero target requires significant oil sands decarbonization. If, while phasing out fossil fuels, there is still a demand for Canadian oil sands, then the decarbonization of the resource production process becomes crucial. In this study, we use an enhanced version of the Global Change Analysis Model (GCAM) with a detailed unconventional oil sector for Canada, including mining and in situ resources. We ask, what is the future of the oil sands sector in deeply decarbonized global and Canadian economies? We address this question under four mitigation scenarios with varying global net-zero GHG emissions constraints, three additional representative lower carbon extraction technologies available for the oil sands sector, as well as global direct air capture (DAC) deployment. We find that lower carbon technology deployment allows a 20%–44% increase in oil sands production by 2050 for scenarios with net-zero GHG emissions in 2100 or 2075. DAC helps maintain oil sands production in the most ambitious global decarbonization scenario (net-zero GHG by 2050), without which low international oil demand makes Canadian oil sands production uncompetitive. Canadian oil sands production thus depends highly on the availability of lower carbon extraction technologies and international oil demand, which to a certain extent relies on the availability and global deployment of negative emissions technologies.

04 OIL SHALES AND TAR SANDS↗

Advanced Systems Level Technology Development, Integration, and Demonstration for Efficient Class 8 Trucks (SuperTruck II)

The Cummins SuperTruck II program has completed the planned technical work on the project. This work includes Demonstrating 50% BTE on the engine-only, 55% BTE for an engine with waste heat recovery, and 125% improvement in vehicle freight efficiency. The engine system included a high efficiency diesel engine integrated with a state-of-the-art waste heat recovery (WHR) system and an advanced aftertreatment system capable of meeting the current emissions standards.

33 ADVANCED PROPULSION SYSTEMS↗