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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Energy Transitions Initiative Partnership Project: Alaska Longline Fishermen’s Association Alternative Fuels Review

This report provides information about additional options in electrifying the Alaska Longline Fishermen’s Association (ALFA) fishing fleet. Currently, the Energy Transitions Initiative Partnership Project is prioritizing electric hybrid and battery electric options for retrofit of select fishing vessels in the fleet. However, there are other options for reducing carbon emissions among the fleet, namely hydrogen, ammonia, and biofuels. The use of these alternative fuels may be an option for the fleet in the future as ALFA addresses its vulnerabilities. A literature review of available resources on these fuels was conducted to provide information on several topics associated with implementation of these technologies, including current applications, commercially available power modules, necessary components, infrastructure, and safety codes and standards. An additional aspect that this report investigates is general sizing and refueling schedule based on operating records of multiple ships in the fleet.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Scaling Optimal Allocation of Cloud Resources Using Lagrange Relaxation

The rapid growth of Cloud Computing (CC) has increased the variety of computing resources, storage, and communication services that pose significant new challenges for the efficient use of cloud resources. The cost-efficient allocation of cloud resources has become a decisive premise for the adoption of CC services. The cost-efficient selection and scheduling of these resources to meet the demands of a scientific workflow is a challenging problem that is exacerbated by the inclusion of multiple CC providers. In this paper, we present a novel strategy for the cost-efficient selection of CC resources using Lagrange relaxation. Our approach is based on preselection of resources and demand decomposition to create a series of smaller sub-problems, which allow the estimation of the best cost-structures and selection of CC service providers for a subset of the time period of the planning horizon. Decomposition of the demand is achieved through the boundary analysis of a continuous relaxation of the problem. Using the metrics defined in terms of the cost and time of completion, we demonstrate excellent performance in relation to optimal solutions. Our method reduced the computational time from hours to seconds for a representative 36-month problem and provided high-quality solutions (< 0.05% relative error). Given the importance of selecting resources and scheduling complex scientific workflows, we believe that this novel strategy will be beneficial for many researchers and users of cloud computing resources.

De La Torre, Luis↗
DOE OSTI2019

Contributing to Long-term Wind Resource Characterization through Buoy-based Observations of Meteorological and Oceanographic Conditions

The U.S. Department of Energy (DOE) supports development of renewable power generation within the U.S. with increasing emphasis on offshore wind energy. This development is currently impeded by a lack of long-term wind observations above the ocean surface at wind turbine rotor plane heights. Pacific Northwest National Laboratory (PNNL) procured two AXYS WindSentinelTM buoys on behalf of DOE to support offshore wind resource assessment. The buoys are available for loan to qualified users according to agency priorities. The Lidar Buoy Loan Program represents an opportunity for organizations with an interest in offshore wind energy to work together with DOE to provide valuable meteorological and oceanographic data to the offshore community that is needed for offshore wind resource characterization. The buoys have already begun to fill observational gaps in offshore winds during long-term deployments off the coasts of Virginia and New Jersey and are scheduled for deployment off the coast of California in 2020. This paper provides an overview of the Lidar Buoy Loan Program, along with highlights of previous deployments, a summary of the upgrades to the lidar systems, and a discussion of the planned activities related to the buoys and the Lidar Buoy Loan Program.

floating lidar, offshore wind energy, wind resourc↗
DOE OSTI2023

Federal Aviation Administration Vertiport Electrical Infrastructure Study

In this detailed analysis, the authors assess the charging infrastructure needed for the deployment of advanced air mobility involving electrified vertical take-off and landing technologies. The report covers four research areas: (1) Identifying charging infrastructure requirements for existing facilities based on flight operational parameters, potential use cases, charging strategy, and other constraints. (2) Assessing sites on power availability to meet charging demand, the impact on grid infrastructure, potential hazards, and cybersecurity needs, and using technoeconomic analysis to identify opportunities for onsite distributed energy resources, primarily solar photovoltaics and battery energy storage systems. (3) Calculating greenhouse gas emission based on total energy consumption attributable to each site. (4) Analyzing the job and economic development impact for sites adopting new infrastructure.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Route Optimization for Energy Efficient Airport Shuttle Operations - A Case Study from Dallas Fort Worth International Airport

Air travel and requisite surface traffic supporting passenger arrival/departure constitutes a significant portion of travel and emissions in cities with large airports. An airport trip can segment into three parts namely: i) travel from a location in the city to the airport; ii) travel from a parking lot or rental car center to the terminal (i.e., within the airport premises), and iii) travel inside the terminal. Depending on the airport access mode all or a part of these legs comprise a traveler’s journey to the airport. The priority of airport ground transport management teams is to provide passengers with a seamless travel experience within the airport, so it is understandable that within airport shuttle routes might not be optimized for minimizing energy consumption. Solutions that meet the dual objective of reducing energy consumption from airport shuttle operations without compromising on passenger travel experience are key to improving system efficiency. There is currently a dearth of research and tools that can inform airports in making such decisions. Addressing this need, this research effort puts forth an optimization model that generates optimal shuttle routes for a given set of constraints, and a discrete-event simulator that evaluates the optimal solutions in a stochastic environment to understand the tradeoffs between passenger wait times, and within airport shuttle energy consumption. The proposed set of tools are tested in the context of optimizing airport shuttles routes within the Dallas Fort Worth International Airport (DFW). In addition to shuttle spatial positioning, and passenger demand information, high-fidelity vehicle data was collected using data loggers installed on DFW shuttles. Results show that 20% energy reduction in shuttle operations is possible with a modest two-minute increase in average passenger wait times. The tools developed in this research effort are designed to be generalizable and can help optimize shuttle operations planning at any major airport.

air travel↗
DOE OSTI2022

2021 Annual Report: Atmospheric Radiation Measurement

In fiscal year 2021 (FY2021), the COVID-19 pandemic continued to have an impact on activities within the Atmospheric Radiation Measurement (ARM) user facility. Travel was limited, which affected field activities and forced the continuation of virtual meetings. However, the ability to travel expanded significantly through the year, bringing some return to normalcy, and throughout the year, there was a great deal of activity dedicated to advancing the facility. Because of COVID, ARM twice delayed the TRacking Aerosol Convection interactions ExpeRiment (TRACER) in the Houston, Texas, area. Originally planned to launch in the spring, TRACER started October 1, 2021, one month after the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign began near Crested Butte, Colorado. ARM teams worked onsite and remotely to make sure both campaigns could launch on this new schedule that was set early in the year. Data from SAIL and TRACER will be critical to improving earth system models, each contributing to different sets of issues. SAIL measurements will provide insights into how precipitation forms and water travels through the Upper Colorado River Basin. TRACER scientists want to know whether tiny atmospheric particles can influence the severity of thunderstorms. In October 2020, the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition ended after 13 months. MOSAiC data from ARM and other organizations are already helping scientists better understand how ice, atmosphere, and ocean systems are connected in the central Arctic. This report discusses some early investigations from MOSAiC, along with other ARM campaigns and activities generating prolific research. In this report, you will also learn how research activities moved forward during the pandemic at ARM’s fixed-location atmospheric observatories. There were important science applications from measurements across the facility. ARM spent a significant amount of FY2021 looking back—and ahead. In November 2020, ARM had its Triennial Review. This review is held every three years to evaluate ARM’s effectiveness in science, operations, and management. Overall, the reviewers had positive feedback regarding the breadth and impact of science activities using ARM data and the way ARM strives to meet changing user needs. The reviewers also provided some recommendations for strengthening ARM going forward. Incorporating feedback from the review, we finalized an updated Decadal Vision document that will help guide ARM priorities in the coming years. This report describes the four themes driving ARM’s Decadal Vision.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Leverage modern artificial intelligence (AI) enabled systems for waste reduction

Manufacturing industries continue to face challenges in reducing waste, as upstream strategies such as source reduction and product redesign require a deeper understanding of processes compared to conventional recycling methods. Recent advancements in artificial intelligence (AI) and machine learning (ML) have opened new opportunities to integrate modern computational techniques with traditional waste minimization strategies. This paper explores AI-enabled approaches for product redesign, source reduction, and recycling that can significantly reduce waste generation while improving efficiency and sustainability. AI-driven material substitution and lightweighting in product design enable discovery of novel materials with optimized properties, reducing waste without compromising performance. Reinforcement learning models optimize process parameters, raw material specifications, and machine sequencing to minimize production losses, while Industrial Internet of Things (IIoT) systems paired with AI analytics enhance real-time waste tracking, predictive maintenance, and quality inspection. Furthermore, AI-based demand forecasting and production planning reduce overproduction and excess inventory, as demonstrated in industrial applications. In recycling, ML-powered pattern recognition and robotic sorting technologies achieve higher accuracy in waste segregation, directly improving recycling efficiency. Complementary solutions such as smart bins and AI-enabled waste pickup scheduling optimize collection logistics, reducing both costs and emissions. Although implementation requires upfront investment in infrastructure and training, the long-term benefits include higher material efficiency, reduced waste, improved product quality, and stronger sustainability outcomes across the supply chain. By leveraging AI-enabled systems, manufacturers can align waste minimization efforts with circular economy principles, creating scalable solutions for both industry and society.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Day-Ahead Forecasting with Federated LSTM to Plan Energy Sharing in a Community Microgrid

Energy balancing in microgrids is a key enabler of resilience. Community microgrids located close to each other have the added benefit of networking and sharing surplus energy, if available. Such complex decision-making runs on optimization that requires reliable short-term (up to very-short-term) forecasts of energy generation and consumption for scheduling or trading. Each microgrid may also opt to not expose their sensitive data such as consumption patterns of individual businesses or residences. This paper investigates a federated approach to dayahead forecasting that trains naive long short-term memory (LSTM) at each business in a microgrid and aggregates weights at the microgrid controller using proximal regularization. This approach ensures that the controller has access only to energy surplus/deficit and not the actual generation or consumption values, avoiding unwanted exposure of sensitive data. A community microgrid in Adjuntas, Puerto Rico with 3 businesses is selected as a case study with a laboratory-scale computing setup. A central LSTM forecaster, where sensitive data from businesses are aggregated at the controller, is implemented as a baseline for qualifying the results. This work serves as a proof-of-concept for scaling the approach to networked and nested microgrids with more complex control options.

Sundararajan, Aditya [ORNL] (ORCID:000000033577854↗
DOE OSTI2026

Commissioning of the IOTA Proton Injector

The IOTA Proton Injector (IPI) at the Fermilab Accelerator Science and Technology facility (FAST) is a machine capable of delivering up to 14 mA pulses of protons at 2.5 MeV to the Integrable Optics Test Accelerator (IOTA) ring. Its construction was completed in the fall of 2025, followed by a successful commissioning run scheduled to conclude at the end of May 2026. It operates alongside the existing electron injector beamline to facilitate further beam physics research and continued development of novel accelerator technologies at the IOTA ring. This report details the current operational profile, known challenges, and future plans for the proton program development at FAST.

Romanov, A. [Fermilab] (ORCID:0000000287065709)↗
DOE OSTI2025

ORNL Infrastructure: Status Update on BEA Research Reactor Cask Planning Activities Completed During FY 2025

This report documents Oak Ridge National Laboratory’s (ORNL’s) FY 2025 progress toward establishing readiness to use the Battelle Energy Alliance (BEA) Research Reactor (BRR) shipping cask in support of the Nuclear Science User Facilities (NSUF). The BRR cask will provide a new shared infrastructure capability for transporting irradiated fuels and materials between ORNL and Idaho National Laboratory (INL), thereby supporting NSUF’s mission of enabling user access to advanced nuclear research facilities. In FY 2025, ORNL advanced the regulatory, contractual, safety review, and planning activities necessary to qualify its facilities and staff for BRR cask handling. Although loaded shipments were delayed due to fabrication lead times for Orano Federal Services LLC’s internal basket hardware, the program progressed to the point where an empty cask dry run is scheduled for October 2025. This dry run represents a critical step in demonstrating ORNL’s ability to receive, handle, and return the BRR cask.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Update on the United States Advanced Ultra-Supercritical Program with Full Scale Component Fabrication to Develop Utility Scale Power Plants with 760°C Steam Temperature

Following the successful completion of a 15-year effort to develop and test materials that would allow coal-fired power plants to be operated at advanced ultra-supercritical (A-USC) steam conditions, a United States-based consortium is presently engaged in Phase 2 of a project which includes an advanced manufacturing effort to complete US-based supply chain development for full commercial scale (800-850 MWe) A-USC components made of nickel-based alloys, components operating at up to 760°C. The project, funded under U.S. Department of Energy Award No. DE-FE0025064, falls under the US DOE overall goal to Develop cost-effective, reliable technologies to improve the efficiency of new and existing coal-fired power plants. A-USC steam cycles have the potential to improve cycle efficiency, reduce fuel costs, and reduce greenhouse gas emissions. Current development and demonstration efforts are focused on enabling the construction of A-USC plants, operating with steam temperatures as high as 1400°F (760°C) and steam pressures up to 5000 psi (35 MPa), which can potentially increase cycle efficiencies to 47% HHV (higher heating value), or approximately 50% LHV (lower heating value), and reduce CO 2 emissions by roughly 25%, compared to today’s U.S. fleet. A-USC technology provides a lower-cost method to reduce CO 2 emissions, compared to CO 2 capture technologies, while retaining a viable coal option for owners of coal generation assets. Among the specific goals of Phase 2 of the ComTest Project are to: validate that components made from advanced nickel-based alloys can operate and perform under A-USC conditions accelerate the development of a U.S.-based supply chain for the full complement of A-USC components close the remaining gaps and reduce the risks for manufacturing components from advanced materials for commercial demonstration fabricate full-scale versions of selected key components made of nickel-based alloys validate a qualified U.S. supply chain, to provide greater cost certainty for components obtain American Society of Mechanical Engineers (ASME) code approval for new materials, components and processes Additional benefit: Manufacturing technology will be applicable to other advanced fossil energy high temperature cycles, and can support increased flexibility of existing power plants The ComTest project is managed by Energy Industries of Ohio, and technically directed by the Electric Power Research Institute, Inc., with General Electric designing the A-USC components. As stated earlier, the current phase of the effort is primarily funded by the U.S. Department of Energy, through the National Energy Technology Laboratory. This presentation outlines the motivation for the project, explains the project’s structure and schedule, and provides some of the technical details on the design of the ComTest components.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

EVs@Scale Next-Gen Profiles - Fleet Utilization 2023

As U.S. fleet operators begin transitioning to electric vehicles (EVs), critical questions arise regarding how to manage this shift without disrupting fleet operations or placing undue stress on the electric grid. A major challenge for fleets is maintaining effective operational schedules while accommodating charging requirements, particularly with high-power charging (HPC) infrastructure, which presents grid stability concerns for utilities. Proposed solutions such as charging substations, megawatt charging systems (MCS), and smart charge management systems (SCMS) offer potential pathways forward, but their effectiveness depends on alignment with real-world fleet behavior and operational constraints. This report investigates the charging and utilization behavior of EV and EVSE fleets actively employing HPC technologies by conducting detailed case study analyses based on telematics data. A suite of predefined metrics—covering charging, routing, and other operational behaviors—is developed to evaluate the impact of fleet activities on grid infrastructure and identify opportunities for optimization. Results highlight variations in charging behavior across fleets, such as weekday versus weekend usage, diurnal charging trends, and the role of operational predictability in enabling SCMS effectiveness. While SCMS can help lower costs and improve energy efficiency for fleets with stable schedules, they may be insufficient for fleets with highly variable or long-haul operations, which may require more robust solutions like MCS. Visualization of aggregated hourly energy metrics reveals that while fleet behaviors are diverse, there are common temporal patterns that could inform infrastructure planning and energy management. These insights emphasize the need for fleet-specific charging strategies that minimize grid impact while supporting reliable fleet operations. Additionally, the report underscores the broader economic stakes of electrification, particularly in high-value markets such as freight, where misaligned transitions could stall EV adoption. By examining current EV and EVSE fleet deployments using predetermined standardized metrics, this study offers a foundation for developing technologies and operational frameworks that support scalable, grid-compatible electrification across a variety of fleet types while establishing a baseline understanding of operational behaviors. In doing so, we aim to ensure that future charging solutions reflect actual fleet needs and grid constraints—an essential step toward maintaining operational continuity and achieving a successful transition to electric fleet operations.

Charging↗
DOE OSTI2020

Advanced Retrieval and Disposition Techniques for Remote Handled Mixed Low-Level Waste - 20319

Legacy waste generated by the sodium-cooled fast reactor, EBR-II, program at the Idaho National Laboratory (INL) (owned by the U.S. Department of Energy and managed and operated by Battelle Energy Alliance, LLC) is challenging to treat and disposition using conventional methods. As a result, Veolia Nuclear Solutions is under contract with the Idaho National Laboratory to demonstrate an integrated retrieval and disposition solution for Remote-Handled Mixed Low-Level Waste currently stored in underground liners at INL. Delivery of the integrated solution builds on the expertise and successes of Veolia Nuclear Solutions under its Problematic Waste Treatment Initiative with INL. This initiative focuses solely on the treatment of problematic (reactive metal containing) waste streams using the Veolia Nuclear Solutions GeoMelt{sup R} In-Container Vitrification (ICV{sup TM}) technology. Under the contract, Veolia Nuclear Solutions will provide a fully commissioned prototype remote retrieval system to semi-remotely retrieve and size-reduce problematic waste liners into a safe and consolidated package for transport. The consolidated package will be shipped to Richland, Washington for demonstration treatment using the robust GeoMelt Richland system at Perma-Fix Northwest. The treated waste will ultimately be disposed of as a vitrified Low-Level Waste glass monolith. Veolia Nuclear Solutions has delivered countless remotely operated systems globally to solve some of the industry's most challenging problems. To ensure risk is mitigated in the best possible manner, a methodical phased approach is being utilized to validate the integrated solution. This contract focuses on the delivery and deployment of the prototype retrieval system onsite and the treatment of a single liner. Following successful demonstration treatment using GeoMelt ICV, the project is planning to make prototype enhancements before retrieving and treating another liner. Establishing a new integrated approach for retrieval and disposition of waste offers many benefits to INL and the U.S. Department of Energy. It is anticipated that the integrated solution will provide significant cost and schedule savings by increasing the number of liners dispositioned per year. In addition, the complexity of the overall waste disposition process will be reduced. Remotely retrieving and size-reducing waste in the field will provide additional safety to operational personnel and allow critical resources, such as hot cells, to focus on the primary missions at hand. Vitrification (using the GeoMelt ICV technology) allows for the direct processing of metal clad waste thereby significantly reducing pretreatment steps while providing a robust waste form for long-term disposal. The results from this ongoing contract are presented in this paper. (authors)

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

Hydrodynamic Test Requirements Process Improvements

Hydrodynamic testing at Los Alamos National Laboratory would benefit from a process improvement for the requirements process. Cameo was used as a digital solution for requirements management to allow Lead Engineers to track requirements more effectively. This was identified as a process improvement throughout this Capstone project. This report includes a project proposal, business case, literature review, methodology, project plan, data analysis, decision-making report, financial analysis report, discussion, and conclusion. Initially, this project focused on figuring out a solution for the hydrotest requirement process improvements. The scope narrowed to focus on the use of Cameo for requirement capture and management. During this Capstone, four tests had digital models produced for requirements management in Cameo. The initial model was the baseline, with core requirements used across the tests. Commonalities in tests were used and the core requirements allowed for process efficiencies. In the data analysis, it was seen that overall, the implementation of using Cameo for requirements resulted in a decreasing trend for both schedule and normalized cost. Tests have different complexity levels which is also a factor in how long the requirements process will take. Additional data is needed to continue analyzing process improvements. Through decisionmaking and financial analysis, the recommendation was to use Cameo for requirements process improvement. Multiple experts provided feedback for requirements that were then captured within models. Numerous tangible and intangible benefits were identified with this process improvement. For return on investment, the metric of success was schedule reduction, which was overall seen. Four tests were analyzed, so future analysis will be needed. There is also not a great financial risk because the main cost would be purchasing more licenses. Individuals must generate requirements whether using this software or not. Overall, training is needed to help improve the skillsets of Lead Engineers but is already being supported on a regular frequency. A desktop guide was started associated with explaining the process, however, it is a work in progress. The team plans on adding additional information in the digital models to help status when requirements are met using verification methods and artifacts. From working on this project an improved understanding of Cameo and requirements was the result. There are future opportunities to extend the usage for requirements management and progress will continue after this project.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Unlocking Autonomous Telescopes through Reinforcement Learning: An Offline Framework and Insights from a Case Study

Optimizing observational astronomy campaigns is becoming a complex and expensive task for next-generation telescopes, where manual planning of observations may tend to reach suboptimal results in terms of optimization.Reinforcement Learning (RL) has been well-demonstrated as a valuable approach for training autonomous systems, and it may provide the basis for self-driving telescopes capable of scanning the sky and optimizing the scheduling for astronomy campaigns.We have developed a framework for the optimization of telescope scheduling using RL techniques, based on a dataset containing data on a discrete set of sky locations that the telescope should visit, and a reward metric. We compared several RL algorithms applied to an offline simulation dataset based at the Stone Edge Observatory, considering a discrete set of sky locations to visit and using “t-effective” as a reward metric, a measure of the quality of the data.Deep Q-Networks (DQNs), belonging to the class of value-based methods, have shown remarkable success in the optimization of astronomical observations in our dataset. In the full environment, the average reward value in each state was found to be 92%±5% of the maximum possible reward, while on the test set it resulted in 87%±9% of the maximum possible reward.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

IRSN Work in Support of NCSP: FY2021 and Plan for Future [Slides]

IRSN and NCSP collaboration has been very fruitful. Despite challenges presented by COVID-19, work has been performed regularly and successfully by video conference. This includes monthly basis meeting with LLNL and LANL and specifics meetings with ORNL and SNL when needed. After two years without any IRSN participation to experiments, ISRN is looking forward to fully participating in the three proposed integral experiments scheduled in 2022. IRSN is working on several new projects including TEX-MOX and TEX-low temperatures.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A hybrid architecture for volt-var control in active distribution grids

Modern active distribution grids are characterized by the increasing penetration of distributed energy resources (DERs). The proper coordination and scheduling of a large numbers of these small-scale and spatially distributed DERs is necessary, and warrants the use of novel distributed approaches. In this paper, we propose a hybrid volt-var control architecture for the distribution grid, which leverages existing centralized and local approaches to planning, decision making, and control, and augments it with distributed optimization and distributed control for DER management. First, we propose a convex model to describe the power physics of distribution grids of meshed topology and unbalanced structure, based on current injection and McCormick Envelopes. Second, we employ the distributed proximal atomic coordination (PAC) algorithm to coordinate DERs to provide voltage support. We implement volt-var optimization by optimally coordinating DERs including PV smart inverters and demand response. We present results using the IEEE-34 bus network, using real data from a distribution feeder in Hawaii, to model load and PV generation. Different levels of DER penetration and objective functions are simulated. Finally, our results show the need for the coordination of DERs to improve voltage profiles, even in networks with existing voltage control devices. Further, we show the need for flexible reactive power capabilities to achieve desired grid performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Testing Capabilities for Superconducting Magnets at Fermilab

This presentation will focus on the current testing capabilities for superconducting magnets at Fermilab, highlighting existing systems, recent upgrades, and future plans. The Vertical Magnet Test Facility (VMTF) remains a cornerstone for testing superconducting magnets in R&D applications, maintaining its established capabilities. Stand 4 continues to support the Hi-Lumi AUP production line of magnets in cryostats and has achieved significant improvements through a redesign of lead connections, resolving issues with liquid helium levels and resistance, culminating in a successful endurance test without interruption. Similarly, Stand 7 underwent commissioning and a lead redesign to reduce heat load, while its core testing capabilities remain unchanged. Looking forward, Stand 3 is undergoing a redesign, with plans to restart and begin commissioning by the end of 2025, introducing new features such as background magnetic field testing and upgraded power supplies. Fermilab is also advancing the High Field Vertical Magnet Test Facility (HFVMTF), designed to support the fusion and magnet R&D program, with commissioning scheduled for 2025 and critical components, including the cryostat and power supplies, being delivered. Enhancing all operations, the newly commissioned IB1 cryoplant now offers automated overnight helium production and efficient transfer to a 10,000-liter dewar, streamlining support across all test stands. This talk will provide a comprehensive overview of testing capabilities, and showcasing how Fermilab is advancing its capabilities to meet the evolving demands of superconducting magnet testing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗