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At least 127 records · Page 7

Spokane Eco-District Campus Performance Under Alternative Electricity Rates: Benefits for virtual power plant participants and suppliers

Here, the respective benefits for virtual power plant participants and suppliers are revealed and compared under alternative electricity rate structures, including conventional large commercial electricity rates, large commercial electricity rates with special rates for demand-side generation, and dynamic hourly transactive prices. These three scenarios were explored using the capabilities of the Eco-District campus, a virtual power plant in Spokane, Washington, that is supplied electricity by Avista Utilities. The Eco-District Campus was modeled to host solar power generation, battery energy storage, and thermal energy resources that must be coordinated with building heating and cooling needs. First, the electricity supplier’s costs for energy, infrastructure, and energy losses were modeled. Then, the virtual power plant’s performance was modeled while presuming that its manager would minimize its costs under its electricity rate structure. The demand charges of conventional commercial electricity rates managed monthly peak, as would be expected, but hourly dynamic transactive pricing resulted in a striking alignment between the costs incurred by the supplier and the virtual power plant’s energy costs.

Electricity rates↗

Performance Evaluation of Augmented Teleoperation of Contact Manipulation Tasks

At Argonne National Laboratory, an enhanced telerobotic concept has been suggested by providing augmented virtual fixtures for precise and dexterous manipulation. The proposed technology incorporated a human-robot interface that can assist personnel on the processes of Deactivation and Decommissioning in sites of high radiation. It has been implemented on a dual-arm robot system, known as Baxter, by integrating the Robotic Operating System (ROS) with 3D sensors and visual-haptic operator interface. However, what remained before its practical utilization is the capability for precisely placing the virtual fixtures. To this end, the objectives involved camera calibration, which required hardware fabrication and setup, as well as modification and implementation of ROS. The goal of this Research and Development is to develop an augmented-reality- based operator interface for human-inclusive, intelligent, and autonomous robotic system for the Deactivation and Decommissioning (D and D) of radioactive sites. The objectives are to develop: Collaborative Robot; Multi-modal Mixed-Reality Human-Robot Interface; Intelligent and Autonomous Behaviors. In order to achieve this, Baxter's Head-Kinect camera and Left-Hand camera need to be calibrated to overlap the real environment with the simulated environment. Camera calibration, which is crucial for precisely placing the virtual fixtures, was successful after running the simulations. The real and simulated environments overlapped, permitting the utilization of augmented teleoperation and the dexterous manipulation of Baxter for D and D applications in nuclear sites. Future steps: Performance evaluation of augmented teleoperation of contact manipulation tasks: Multiple-Camera 3D Reconstruction and Automation. Oculus Interface: Augmented reality and machine learning for enhanced telerobotic operation (Augmented Tele-autonomy): Machine-learning techniques for complex and flexible autonomous robotic behaviors. Interactive remote operation of robotic systems. Mesh cutting with simulation and real robot.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

2026 Annual Molten Salt Reactor Campaign Review

This report documents the 2026 Annual Molten Salt Reactor (MSR) Campaign Review held in Albuquerque, New Mexico, from April 21–24, 2026. The review was organized by Dr. Patricia Paviet, National Technical Director of the Advanced Reactor Technology (ART) MSR program for the U.S. Department of Energy Office of Nuclear Energy (DOE-NE), and included participation from principal investigators, federal managers, developers, regulators, and members of the broader MSR community. The 2026 review expanded beyond the ART-MSR campaign to include related DOE-NE programs supporting molten salt reactor advancement, including the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the Advanced Materials and Manufacturing Technologies (AMMT) program, Advanced Reactor Safeguards and Security (ARSS), Material Protection, Accounting and Control Technologies (MPACT), and relevant advanced fuels activities. Three days were dedicated to technical presentations and panel discussions covering thermal properties, off-gas management, modeling and simulation, safety and licensing, safeguards and security, materials and corrosion, and irradiation activities. A fourth day was dedicated to technical tours of Sandia National Laboratories and Kairos Power facilities. Attendance was strong and comparable to the prior annual review, with approximately 75 in-person participants per day, 75–80 virtual attendees per day, and approximately 30 participants in the tour day. The review fostered significant technical exchange across national laboratories, universities, industry, regulators, and international participants. This report summarizes the review structure, technical themes, participation, tours, feedback, and conclusions relevant to future planning for the MSR campaign.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Workshop Report for Next-Gen AI for Proliferation Detection: Accelerating the Development and Use of Explainability Methods to Design AI Systems Suitable for Nonproliferation Mission Applications

Artificial intelligence (AI) promises powerful new capabilities in an expansive array of applications. One area is proliferation detection, where AI can provide transformative tools to achieve objectives currently inaccessible using conventional methods. In particular, AI affords the opportunity to use new indicators and process massive amounts of heterogeneous data that can increase sensitivity to proliferant activities and push proliferation detection to the earliest possible stages. However, existing AI tools are not ready to achieve such potential, falling short in regard to some important considerations involved in proliferation detection. One crucial aspect that requires improvement is the explainability of the most powerful AI algorithms (i.e., understanding how the algorithms actually arrive at their conclusions)-the lack of which prevents widespread adoption in national security missions. The Data Science and AI portfolio within the National Nuclear Security Administration's Office of Defense Nuclear Nonproliferation Research and Development is driving the development of next-generation AI for proliferation detection through the expertise and work of the national laboratories and partners in academia. The "Next-Gen AI for Proliferation Detection: Accelerating the Development and Use of Explainability Methods to Design AI Systems Suitable for Nonproliferation Mission Applications" workshop aimed to further this objective. The meeting was held virtually on Sept. 15-16, 2020 and included more than 170 participants, primarily from the national laboratories with additional contributions from university researchers and mission partners. Each day included a keynote presentation, four technical presentations about cutting-edge research in explainability, and a panel to explore considerations in applying explainability and developing AI systems that can accelerate the transition of emerging AI technologies among partners and end users to solve critical mission questions. This report summarizes the Next-Gen AI for Proliferation Detection workshop's content and findings.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

The Surface-Topography Challenge: A Multi-Laboratory Benchmark Study to Advance the Characterization of Topography

Surface performance is critically influenced by topography in virtually all real-world applications. The current standard practice is to describe topography using one of a few industry-standard parameters. The most commonly reported number is Ra, the average absolute deviation of the height from the mean line (at some, not necessarily known or specified, lateral length scale). However, other parameters, particularly those that are scale-dependent, influence surface and interfacial properties; for example the local surface slope is critical for visual appearance, friction, and wear. The present Surface-Topography Challenge was launched to raise awareness for the need of a multi-scale description, but also to assess the reliability of different metrology techniques. In the resulting international collaborative effort, 153 scientists and engineers from 64 research groups and companies across 20 countries characterized statistically equivalent samples from two different surfaces: a “rough” and a “smooth” surface. The results of the 2088 measurements constitute the most comprehensive surface description ever compiled. We find wide disagreement across measurements and techniques when the lateral scale of the measurement is ignored. Consensus is established through scale-dependent parameters while removing data that violates an established resolution criterion and deviates from the majority measurements at each length scale. Our findings suggest best practices for characterizing and specifying topography. The public release of the accumulated data and presented analyses enables global reuse for further scientific investigation and benchmarking.

42 ENGINEERING↗

Laboratory Analysis for Radiological Events

Presentation for an International Atomic Energy Agency sponsored workshop on Consequence Management (virtual). Presentation sponsored by DOE NA-81

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Editorial for the Virtual Special Issue of Journal of Power Sources “Low temperature fuel cells and electrolysers” - Science and engineering: Let's play this game hand in hand!

Electrochemistry is already and will increasingly be amongst the major drivers of our energetic mix decarbonization, so to fight anthropogenic global warming. The hydrogen economy vector (ideally produced in water electrolysers using renewable electricity and transformed back into electricity in fuel cells), in parallel with the conversion of carbon dioxide and nitrogen gas into value-added products are seen as pillars of the so-called green and sustainable Energy Revolution. The hydrogen technologies presently attract increasing interest, their momentum growing irremediably in Europe, Asia and Americas. Here, this Virtual Special Issue (VSI) gathers the latest scientific results of major research laboratories worldwide, all addressing various aspects of electrochemical energy and material conversion processes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Hydrokinetic Power Conversion Using Vortex-Induced Oscillation with Cubic Restoring Force

A cubic-spring restoring function with high-deformation stiffening is introduced to passively improve the harnessed marine hydrokinetic power by using flow-induced oscillations/vibrations (FIO/V) of a cylinder. In these FIO/V experiments, a smooth, rigid, single-cylinder on elastic end-supports is tested at Reynolds numbers ranging from 24,000 < Re < 120,000. The parameters of the tested current energy converter (CEC) are cubic stiffness and linear damping. Using the second generation of digital virtual spring-damping (Vck) controller developed by the Marine Renewable Energy Laboratory (MRELab), the cubic modeling of the oscillator stiffness is tested. Experimental results show the influence of the parameter variation on the amplitude, frequency, energy conversion, energy efficiency, and power of the converter. All experiments are conducted in the low turbulence-free surface water (LTFSW) channel of the MRELab of the University of Michigan. The main conclusions are: (1) The nonlinearity in the cubic oscillator is an effective way to extend the vortex-induced vibration (VIV) upper branch, which results in higher harnessing power and efficiency compared to the linear stiffness cylinder converter. (2) Compared to the linear converter, the overall power increase is substantial. The nonlinear power optimum, occurring at the end of the VIV upper branch, is 63% higher than its linear counterpart. (3) The cubic stiffness converter with low harnessing damping achieves consistently good performance in all the VIV regions because of the hardening restoring force, especially at higher flow velocity.

13 HYDRO ENERGY↗

PR100: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy [Slides]

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050. The PR100: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy study, led by the National Renewable Energy Laboratory (NREL), will leverage world-class expertise, cross-sector modeling capabilities, and community engagement to generate feasible pathways to affordable and reliable electricity across the archipelago. PR100 is being funded by the Federal Emergency Management Agency through an interagency agreement with DOE's Office of Electricity to support recovery efforts in the island's energy sector leveraging the expertise and capabilities of the National Laboratories including Argonne, Lawrence Berkeley, NREL, Oak Ridge, Pacific Northwest, and Sandia. The public is invited to this virtual launch event to learn more about the scope and benefits of the study and opportunities for engagement. Welcoming remarks will be provided by Jennifer M. Granholm, Secretary of the U.S. Department of Energy; Martin Keller, Director of the National Renewable Energy Laboratory; and Deanne Criswell, Administrator of the Federal Emergency Management Agency.

100% renewable energy↗

The 2020 Nonlinear Mechanics and Dynamics Research Institute

The 2020 Nonlinear Mechanics and Dynamics (NOMAD) Research Institute was successfully held from June 15 to July 30, 2020. NOMAD brings together participants with diverse technical backgrounds to work in small teams to cultivate new ideas and approaches in engineering mechanics and dynamics research. NOMAD provides an opportunity for researchers – especially early career researchers - to develop lasting collaborations that go beyond what can be established from the limited interactions at their institutions or at annual conferences. A total of 11 students participated in the seven-week long program held virtually due to the COVID-19 health pandemic. The students collaborated on one of four research projects that were developed by various mentors from Sandia National Laboratories, the University of New Mexico, and other academic and research institutions. In addition to the research activities, the students attended weekly technical seminars, various virtual tours, and socialized at virtual gatherings. At the end of the summer, the students gave a final technical presentation on their research findings. Many of the research discoveries made at NOMAD 2020 are published as proceedings at technical conferences and have direct alignment with the critical mission work performed at Sandia.

42 ENGINEERING↗

Operating a commercial building HVAC load as a virtual battery through airflow control

Virtual battery (VB) is an innovative method to model flexibility of building loads and effectively coordinate them with other resources at a system level. Unlike a real battery with a dedicated power conversion system for charging control, methods are required for operating building loads to deviate from the baseline to respond to grid signals. This paper presents a VB control for a commercial heating, ventilation, and air conditioning (HVAC) system to follow the desired power consumption in real-time by adjusting zonal airflow rates. The proposed method consists of two parts. At the system level, a mixed feedforward and feedback control is used to estimate the desired total airflow rate. At the zone level, two priority-based algorithms are then proposed to distribute the total airflow rate to individual zones. In particular, a zonal airflow limit estimation method is proposed using machine-learning techniques, in contrast to physics-based thermal models in existing studies, to more accurately capture zonal thermal dynamics and improve temperature control performance. An office building on the Pacific Northwest National Laboratory campus is implemented in EnergyPlus, and used to illustrate and validate the proposed control.

Wang, Jiyu↗

Near-field acoustical holography and acoustic power analysis of a simulated, highly heated supersonic jet

Although near-field acoustical holography (NAH) and acoustic intensity analysis have previously been used to investigate the apparent jet noise sources produced by military aircraft, explicit connections to supersonic jet characteristics cannot be made due to a lack of information about the exhaust plume. Here, to begin to bridge this gap and better understand the source information yielded by NAH, the current study instead applies NAH to a virtual measurement of the near-field pressures of a highly heated laboratory-scale supersonic jet generated by large-eddy simulation (LES). The holographic reconstructions of the pressure, particle velocity, and acoustic intensity are found to match the LES-generated acoustic field well and are used to calculate the acoustic power of the jet. The jet's calculated overall acoustic power is compared to the free-stream mechanical power, resulting in an acoustic efficiency of 1.5%. Ray-tracing of the acoustic intensity to the jet centerline generates an axial distribution of the acoustic power origin, showing that almost all the power originates from the supersonic portion of the flow and with the distribution peak upstream of the potential core tip. Holographic reconstruction of the pressures along the nozzle lipline captures the general spectral shape of the LES-generated pressures, though it underestimates the amplitude.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Examining United States Nuclear Weapon Educational Initiatives_A Quantitative Research Study on the Satisfaction of Participants Within the Nuclear Weapons Community

This study focused on a few United States nuclear weapons educational initiatives exploring six classroom environment factors that may or may not influence Satisfaction in a virtual or live classroom environment within the nuclear weapons community. The research explored Personalization, Involvement, Student Cohesiveness, Task Orientation, Innovation, and Individualization. The United States nuclear weapons community needed to attract new and talented individuals to the nuclear weapons profession. This study added to the nuclear weapons community by researching factors that may aid academic instructors, and curriculum developers create new and inventive ways of incorporating these factors into existing or new nuclear weapons educational courses. Convenience sampling was the data collection method used to gather quantitative research data. One hundred and seven voluntary participants utilized the College and University Classroom Environment Inventory with the Los Alamos National Laboratory's consent. There is not much concurrent research on Satisfaction within the live and virtual classroom environment. This research was vital for future research into how to increase participant satisfaction. The study provided the nuclear weapons community with grounded analysis to help create and guide new classes and course creation, possibly increasing Satisfaction in a live and virtual classroom environment. According to binary logistic regression, there was a statistically significant relationship among the dependent variable, Satisfaction, and two independent variables, Involvement, and Task Orientation in the classroom environment within the nuclear weapons community. Future nuclear educational programs may increase Satisfaction in the classroom environment by increasing participant Involvement and Task Orientation within a class using the CUCEI as a reference.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Optimized V1G and V2G Electric Vehicle Fleet Management and Grid Transaction at Marine Corps Air Station Miramar in San Diego, CA

The overall technical goal of the project was to demonstrate an all-electric bi-directional non-tactical fleet at Marine Corps Air Station (MCAS) Miramar that was integrated and controlled with other distributed energy resources (DERs) (i.e., PV, stationary battery, and building loads) to provide resilience to critical electric loads in the event of grid outages, to minimize charging costs, and to provide economic energy resources to electricity markets. In this project, the specific, technical objectives were: 1. Demonstrate that bi-directional electric vehicles can provide critical complementary services to fixed storage batteries in microgrid applications while performing function as non-tactical vehicles. 2. Demonstrate participation of bi-directional (V2G) and unidirectional (V1G) PEVs for demand management and minimization of charging costs. 3. Demonstrate integration of multiple DERs for grid service participation. US Marine Corps Air Station (MCAS) Miramar in San Diego was the site of this electric vehicle-to-microgrid-utility grid test and demonstration project. Existing microgrid assets in this study included (1) a public works building; (2) a 30-kW rooftop photovoltaic (PV) system and (3) a separate 250 kW carport PV system. In this project, six bi-directional V2G vans were located at the MCAS Miramar’s showcase building-scale microgrid to develop and test technical capabilities that V2G can provide in microgrid applications (e.g., cost reduction and resiliency). These resources provided aggregated demand management and simulated participation in current retail DR programs. The vehicles used in this demonstration were selected because they provided functionality that MCAS Miramar needed, 15 passenger transport and facilities work cargo carrying capacity, and bi-directional charging capability that the research project required. All vehicles in this study were manufactured and distributed by VIA Motors, Inc. There were six vehicles total and each was VIA’s VTRUX eREV V2G model, a modified General Motors Chevrolet 2500 2WD van. Three of the vans were configured as passenger vans and the other three were configured as cargo vans. Each van had an on-board bi-direcrtional inverter/charger, Bel Power Solutions model 350INVCHGT150-120-240-8G nominally rated at +/-15 kW. The VIA van’s charging connector follows the J1772 charging protocol. The bi-directional EVSEs demonstrated in this study were manufactured by Coritech, Inc. Each VGI-80-AC charging station enabled enhanced V2G charging capability to a Clipper Creek CS-100 charging module. The enhanced capabilities included ethernet communication following the SEP2.0 protocol with a distributed energy resource function set and an operator screen displaying real-time SOC, voltage, and current. The VGI-80-AC charging stations are classified as level 2 with a maximum current output of 80 A or effectively 19 kW. The VIA van’s onboard charger limited the charging and discharging power to 15 kW in each direction. A control computer was installed in the EWOC and connected to an existing monitor. The V2G control communication network was a completely stand-alone closed system that did not have any connection to any other networks on the base. A cybersecure remote communication connection was created with a cellular modem, firewall hardware, and a virtual private network configuration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Fast-Tracking Technology Solutions to Boost Cybersecurity in Virtual Power Plant and Aggregator Operations

This presentation was presented at the Aggregation and Grid Security Workshop - held on June 17-18, 2025, at NREL in Golden, Colorado. The goal of the two-day workshop was to address the critical cybersecurity challenges for the future electric grid. This presentation overviews NREL's work in evaluating cybersecurity technology solutions for virtual power plant and aggregator operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Physics-Informed Recurrent Neural Networks to Predict Reactor Operations of the AGN-201 Nuclear Reactor

4 page paper submitted to ANS Student conference. Summary of paper similar to the following abstract: The ability to predict how a reactor will operate, understand when anomalous conditions arise, and ensure a reactor is being operated as expected is crucial for deploying new nuclear facilities. Digital twins serve as a unique solution to recognizing reactor behavior; however, they require data to be useful. For next-generation reactors, this data may not currently be available. To explore how synthetic physics-informed reactor data can be used to predict reactor operations, a recurrent neural network was implemented for the Idaho State University AGN-201 digital twin. The goal of this work is to determine how synthetic data can be used to train a recurrent neural network model for predicting the reactor power of the AGN-201. The recurrent neural network was validated using both synthetic and real operational data. We envision this approach will help bridge the gap between the virtual and physical sides of a digital twin, where reactor physics models based on as-built data can be corrected for actual operating parameters to ensure the virtual model mirrors reality.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗