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At least 703 records · Page 39

Wind Supply Chain Security: Hardware Enumeration and Analysis

This project, undertaken by Idaho National Laboratory (INL) for the Department of Energy (DOE) Wind Energy Technologies Office (WETO), focused on the enumeration and analysis of six key devices important to wind technologies. The devices analyzed included Beckhoff Bus Terminal Controllers (BK1120 and BC9000), a Beckhoff Economy Built-in Panel PC (CP6231), an N-Tron Managed Industrial Ethernet Switch (711FX3), a Bachmann M1 Gateway, and a Bachmann Smart Power Plant Controller. Device selection was driven by availability and budget constraints, with several components sourced from existing wind farms and others procured through a co-agreement with another WETO-funded project. The project's primary objective was to create a hardware bill of materials (HBOM) for each device, identifying and documenting all components to assess potential security and supply chain risks. A detailed analysis revealed over 750 unique components across the six devices, with 80% successfully identified and accompanied by datasheets. Notably, Texas Instruments emerged as the leading supplier, providing over 16% of the components, followed by ON Semiconductor at 11.3%, Analog Devices at 5.3%, and Renesas Electronics Corp at 4.1%. Other notable vendors included Toshiba Corporation, iC-Haus Corporation, Atmel, Vishay, and STMicroelectronics. The enumeration process involved thorough documentation of each component, including its designation, quantity, identifiers, pin package, description, vendor, model, and country of origin. This process provided valuable insights into the complexity and diversity of the electronic systems within these wind devices. It also highlighted the distinct separation of components between vendors, suggesting a trend of vendor-specific component usage. Key findings from the project emphasized the importance of broadening the scope of vendor analysis in future research to gain a comprehensive understanding of component distribution and commonality. The identification of vendor-specific component usage patterns offers new avenues for research and underscores the significance of continued investigation in this field. Overall, this project provides critical insights into the component composition of wind devices, aiding in the development of improved supply chain management and component sourcing strategies. The results contribute valuable knowledge to the wind technology sector, laying the groundwork for enhanced security and resilience in wind energy systems.

17 - WIND ENERGY↗

How Today's Hydropower Impacts Tomorrow's Grid: Counterfactual Scenarios Showing Grid Impacts if Hydropower Goes Away

Amidst ongoing discussions about hydropower removals, retirements, and reduced availability due to drought and other environmental considerations, it is important to understand the long-term effects of reduced hydropower resources on the U.S. electric grid. This analysis uses the Regional Energy Deployment System (ReEDS™) grid planning model to compare several representative scenarios of retiring hydropower and pumped storage hydropower (PSH) capacity over time and explore the overall implications on the U.S. grid from present day through 2050. Reduced hydropower capacity and generation is replaced by a mix of both fossil and non-fossil resources, including natural gas, wind, solar, and battery technologies. Additional natural gas usage leads to an increase in cumulative national electric sector carbon dioxide and criteria pollutant operating emissions of less than 1% in many scenarios but up to 4-5.3% in some cases. Total electric sector costs also increase by <1% in many scenarios but up to 3.6% in the most extreme scenarios where nearly all the hydropower and PSH fleet retires, equating to $\$$340 billion in undiscounted costs. National results indicate that absent additional interventions, retiring hydropower and PSH capacity could increase electric sector emissions and direct capital and operating costs. However, more focused analysis is required to evaluate specific asset-level, local, and regional implications, and a broader scope is necessary to weigh these electric sector impacts alongside economic, ecological, water management, and other cross-sectoral effects that could be either negative or positive.

14 SOLAR ENERGY↗

Sitka Energy Inventory

The City and Borough of Sitka was chosen for an Energy Technology Innovation Partner Project award starting in Fall 2023, the third cohort of the program. The scope of the following work was driven by the city, as well as the city-appointed Sustainability Commission. The community asked for a method to track their reliance on outside fuel sources, as well as the emissions associated with those fuels and other processes in Sitka. The Pacific Northwest National Laboratory (PNNL) provided research and methodology in line with this community driven ask. This project is a community wide inventory, requiring methods to estimate the fuel usage and emissions from various industries. For each estimate, PNNL presents methodologies that can be repeated by the community in future years to understand how the city is changing.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Toward scalable quantum computations of atomic nuclei

We solve the nuclear two-body and three-body bound states via quantum simulations of pionless effective field theory on a lattice in position space. While the employed lattice remains small, the usage of local Hamiltonians including two- and three-body forces ensures that the number of Pauli terms scales linearly with increasing numbers of lattice sites. We use an adaptive ansatz grown from unitary coupled cluster theory to parametrize the ground states of the deuteron and 3 He, compute their corresponding energies, and analyze the scaling of the required computational resources. Our quantum simulations reproduce exact benchmarks for 2 H and 3 He within 100 keV, requiring at most 30 layers in the ansatz and thus resulting in modest circuit depths. Additionally, we find the number of shots required to reach a given precision scales linearly in the lattice size and more mildly in the system size. Furthermore, based on the agreement with exact benchmarks and mild scaling, we conclude that this can be an efficient, scalable approach for quantum computations of nuclear ground states, particularly to prepare initial states for quantum phase estimation or other filtering algorithms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Split HPWHs as an Efficient Solution for Multifamily Buildings with In-Unit Water Heaters

A quarter of all housing units in the United States are found in multifamily buildings, but few efficiency innovations have been made to improve electric water heating systems in this building type. Domestic hot water in multifamily buildings can either be provided by a large central water heater or smaller in-unit water heaters. Integrated heat pump water heaters that are installed in single-family homes are often a poor fit for individual multifamily units because the water heaters are often located in small internal closets. This confined space can limit the airflow to the heat pump, and the cold exhaust air can cause discomfort and reduced efficiency. Split CO2 HPWHs separate the tank from the heat pump, which allows for installation location flexibility. Further, CO2 heat pumps can operate under colder ambient conditions, making them a better fit for multifamily units across a wide range of climate regions. As part of a larger project to characterize split HPWH performance, we evaluated the feasibility of installing an additional, parallel tank that could provide hot water to a second housing unit using a single CO2 heat pump. This approach would reduce the first costs of these more expensive units. Based on the high draw volume that we imposed on both tanks, the same heat pump may be able to support more tanks, depending on hot water usage. This paper will describe the split CO2 HPWH technology, how the two-tank system was controlled, and results from our laboratory evaluation.

CO2 HPWH↗

Usage of Multi-Mission Radioisotope Thermoelectric Generators (MMRTGs) for Future Potential Missions

The goal of NASAs Radioisotope Power Systems (RPS) Program is to make RPS ready and available to support the exploration of the solar system in environments where the use of conventional solar or chemical power generation is impractical or impossible to meet the needs of the missions. To meet this goal, the RPS Program, working closely with the Department of Energy, performs mission and system studies (such as the recently released Nuclear Power Assessment Study), evaluates the readiness of promising technologies to infuse in future generators, assesses the sustainment of key RPS capabilities and knowledge, forecasts and tracks the Programs budgetary needs, and disseminates current information about RPS to the community of potential users. This presentation focuses on the needs of the mission community and provides users a better understanding of how to integrate the MMRTG (Multi-Mission Radioisotope Thermoelectric Generator).

Radioisotope↗

Human Factors and Technologies Design to Improve User Acceptance of Pooled Rideshare for Increasing Transportation System Energy Efficiency

This multi-year project delivered a comprehensive, human-factors-driven framework to understand, model, and improve pooled rideshare (PR) adoption in the United States. Through three large-scale national survey studies involving more than 16,000 participants across multiple cities and demographic groups, the research established one of the most extensive datasets to date on user perceptions, behavioral barriers, and service expectations related to pooled rideshare. These data revealed key human factors barriers of user acceptance of PR and suggested potential actionable experience optimizations that could lead to increased PR usage. This foundational knowledge guided the development of novel human-factors models and behavioral choice models that quantify how psychological, demographic, and trip-level factors influence willingness to pool. Building on these empirical insights, the project developed advanced behavioral modeling tools, including mixed logit and integrated choice and latent variable models, to capture both observable and latent influences on PR adoption. These models significantly improved the ability to predict riders’ acceptance of pooled trips, explaining choice heterogeneity through latent constructs such as safety, service experience, privacy concerns, time sensitivity, and environmental attitudes. Together, these models provide a robust analytical foundation for designing PR systems that more effectively meet user needs. The project translated human-factors insights and behavioral models into actionable technology innovations by extending POLARIS—an agent-based, activity-based travel simulation platform—into a fully functional pooled rideshare simulation environment. New PR modules, acceptance models, and regional scenarios were implemented for Greenville, SC and Austin, TX, enabling high-fidelity validation of algorithmic strategies under realistic demand and traffic conditions. The simulation platform supported the development and evaluation of adaptive discount-based assignment algorithms, enhanced willingness-to-pay formulations, demographic-aware incentive mechanisms, and a proactive joint assignment and repositioning strategy. Simulation results demonstrated substantial gains in pooling uptake, average vehicle occupancy, energy efficiency, and fleet profitability. In Greenville, pooling adoption more than doubled, while reductions in vehicle-miles traveled and energy consumption were significant. In Austin, pooling improvements were achieved with minimal service-quality trade-offs, and profitability increased across all fleet sizes. Through this research, we developed a comprehensive understanding of the human factors barriers that limit user acceptance of pooled rideshare services. These insights enabled the design of human-factors-aware pooled rideshare technologies that more effectively address user concerns and improve adoption rates. By integrating these models into an advanced agent-based simulation framework, we demonstrated that higher adoption of pooled rideshare can lead to measurable improvements in energy efficiency and system performance. Together, these contributions establish a validated pathway from human-centered analysis to technology development and energy-saving outcomes, supporting national goals for more sustainable and efficient mobility systems.

Jia, Yunyi↗

Recent Advances in the Use of Ionic Liquids and Deep Eutectic Solvents for Lignocellulosic Biorefineries and Biobased Chemical and Material Production

Biorefineries, which process biomass feedstocks into valuable (bio)products, aim to replace fossil fuel-based refineries to produce energy and chemicals, reducing environmental and health hazards, including climate change, and supporting a sustainable economy. In particular, lignocellulose-based biorefineries, utilizing the most abundant renewable feedstock on Earth, have significant potential to supply sustainable energy, chemicals and materials. Ionic liquids (ILs, organic salts with low melting temperatures) and deep eutectic solvents (DESs, mixtures with eutectic points lower than the ideal mixture) are capable of dissolving some of the key lignocellulose polymers, and even the whole biomass. Furthermore, they have intrinsic advantages over molecular solvents, including safer usage profiles and high tunability, which allow tailored physicochemical properties. Such properties provide unique opportunities for the development of new processes that could unlock the full potential of future biorefineries. Here, we review the current state of lignocellulosic biomass processing with ILs and DESs, with a specific focus on the pretreatment chemistry, process flow and products from each component; followed by discussions on sustainability assessments and technological challenges. We aim to inform the research community about the opportunities, challenges and perspectives in developing truly sustainable lignocellulose-based biorefineries.

09 BIOMASS FUELS↗

Using the ATLAS experiment software on heterogeneous resources

With the large dataset expected from 2030 onwards by the HL-LHC at CERN, the ATLAS experiment is reaching the limits of the current data processing model in terms of traditional CPU resources based on x86_64 architectures and an extensive program for software upgrades towards the HL-LHC has been set up. The ARM CPU architecture is becoming a competitive and energy efficient alternative. Accelerators like GPUs are available in any recent HPC. In the past years ATLAS has successfully ported its full data processing and simulation software framework Athena to ARM and has invested significant effort in porting parts of the reconstruction and simulation algorithms to GPUs. We report on the successful usage of the ATLAS experiment offline and online software framework Athena on ARM and GPUs through the PanDA workflow management system at various WLCG sites. Furthermore we report on performance optimizations of the builds for ARM CPUs and the GPU integration efforts. We will discuss performance comparisons of different ARM and x86_64 architectures on WLCG resources and Cloud compute providers like GCP and AWS using ATLAS productions workflows as used in the Hep-Score23 benchmark suite.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Research and Test Reactor Fuels

PRO-RR is the research reactor focused program element of the broader Proliferation Resistance Optimization program (PRO-X) under the National Nuclear Safety Administration (NNSA) in the U.S. Department of Energy (DOE). PRO-X provides a framework for integrating proliferation resistance in nuclear system designs to minimize weapons usable nuclear materials (WUNM) production and diversion pathways while optimizing systems performance for peaceful use missions. PRO-RR applies the PRO-X mission objectives to research reactor system design. This document serves as one of the foundational documents for the PRO-RR-Fuel System Design technical team by documenting current research reactor fuels usage. The PRO-RR-Fuel System Design technical team consists of subject matter experts from Argonne National Laboratory (Argonne) and Savannah River National Laboratory (SRNL). In order to determine the preferred fuel of use in upcoming research and test reactors to optimize proliferation resistance, performance, and safety, it is useful to assess the fuels that have been used in the past, or are currently in use. This report reviews the historical and current fuels used in research and test reactors to inform future fuel selection. Chapter 2 discusses the low-enriched uranium (LEU) fuels currently in use in terms of thermal power level and utilization of the reactor. Chapter 3 summarizes the fabrication processes for common fuel types. Chapter 4 discusses in detail the fuel types in use in research and test reactors. A review of the cladding types in use is presented in Chapter 5, and a historical review of research and test reactor fuel fabricators is presented in Chapter 6. The data collection strategy used the International Atomic Energy Agency (IAEA) research reactor database [1] as a starting point. Information on the fuel used was gathered on research reactors (other than critical assemblies) that were listed as operational, planned, or in temporary shutdown in the IAEA database. Data on the fuel type, geometry, enrichment, uranium loading, cladding type, and fabricator were collected for each of the reactors available in the public domain. Sources of data included conference papers, journal articles, and facility and fabricator websites. Data on research reactors operating on LEU fuels are presented in Appendix A, while Appendix B presents data collected on all reactors at the time of publication of this report. Appendix C presents data collected on reactors that were part of the M3 research and test reactor conversion program.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Decarbonization of heat pump dual fuel systems using a practical model predictive control: Field demonstration in a small commercial building

In the transition from fossil fuel to electrified heating, a concerning trend is emerging in certain regions of the US. Owners of buildings with gas-based systems leave them in place after adding heat pumps (HPs). Existing control solutions for these hybrid (dual fuel) systems are rudimentary and fall short of realizing the full carbon reduction potential of these systems. Model predictive control (MPC) is often regarded as the benchmark for achieving optimal control in integrated systems. However, in the case of small-medium commercial buildings (SMCBs), the control and communication infrastructure required to facilitate the implementation of such advanced controls is often lacking. This paper presents a field implementation of easy-to-deploy MPC for a dual fuel heating system consisting of HPs and a gas-fired furnace (GF) for SMCBs. The control system is deployed on an open-source middleware platform and utilizes low-cost sensor devices to be used for real SMCBs without major retrofits. Here, we demonstrated this MPC in a real office building with 5 HPs and 1 GF for 2 months. The test results showed that MPC reduced 27% of cost while completely eliminating GF usage by shifting 23% of the thermal load from occupied-peak time to non-occupied-non-peak times.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Fire Protection Engineering Technical Report for Electric Vehicles and Lithium-Ion Batteries

This fire protection engineering technical report discusses and presents the properties, data, and safety of select lithium-ion batteries. Lithium-ion batteries have increased in usage and a fire scenario analysis must be created for each situation where they may be introduced in buildings to determine the risk associated if a battery failure were to occur.

25 ENERGY STORAGE↗

Approximate Dynamic Programming With Enhanced Off-Policy Learning for Coordinating Distributed Energy Resources

Herein this paper proposes an innovative approximate dynamic programming (ADP) method for distributed energy resource coordination with the loss of life of battery energy storage system (BESS) explicitly modeled. The dispatch policy is designed to account for both calendrical and cyclical aging effects on BESS, explicitly modeling the impacts of ambient temperature on BESS lifespan. The proposed ADP employs an adaptive critic method and enhanced off-policy deterministic policy gradient (DPG) strategy, addressing the limitations of the on-policy gradient-based ADP approaches, including inadequate exploration, low data usage, and computational complexity. In particular, a customized policy is proposed to guide the algorithm to explore some promising decisions and thereby improve exploration capability and learning efficiency compared to conventional DPG-based learning approaches, which may struggle to find a global optimum due to random noisy action-based exploration or require expert demonstration with extra effort. The proposed method is illustrated using the IEEE 123-node system and compared with the existing ADP methods to prove solution accuracy and demonstrate the effects of incorporating degradation models into control design. Case studies showed that the proposed ADP effectively coordinates DERs with a 10 times smaller optimization gap compared to existing methods, and the incorporation of the BESS life loss model ensures the expected lifespan and results in significant cost savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Ground and excited state gradients with end-to-end differentiable semiempirical quantum chemistry

Accurate and efficient gradients of molecular energy with respect to nuclear degrees of freedom are essential for geometry optimization and molecular dynamics, including simulations that go beyond the Born–Oppenheimer regime. A common approach involves deriving analytical formulas for new electronic structure methods, which is often conceptually difficult and requires tedious coding. Here, we implement analytical, semi-numerical, and automatic differentiation (AD)-based gradient pathways for semiempirical Hamiltonian models in the PYSEQM software package, leveraging both graphics processing unit (GPU) and central processing unit (CPU) architectures. We further extend these capabilities to excited states calculated using the configuration interaction singles and time-dependent Hartree–Fock ansätze. We benchmark wall time, peak memory usage, and accuracy across three molecular families of varying chemical complexity, including systems of up to a thousand atoms. For ground-state simulations, analytical and AD gradients achieve near-identical GPU runtimes, while semi-numerical gradients are slower on GPU but remain competitive on CPU. For excited states, both analytical and custom AD approaches using implicit differentiation show similar performance and low memory requirements, whereas gradients with full AD are memory-limited. AD gradients match analytical ones in accuracy across all tested systems, aided by a quaternion-based diatomic frame rotation for two-center quantities that ensures smooth energy surfaces. Overall, automatic differentiation emerges as a practical alternative to analytical gradients in semiempirical quantum chemistry, offering high accuracy while allowing seamless integration in AI-driven workflows and popular packages, such as PyTorch and JAX. Our results provide actionable guidance for selecting optimal gradient strategies in large-scale ground- and excited-state molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Configuration design studies and wind tunnel tests of an energy efficient transport with a high-aspect-ratio supercritical wing

The results of design studies and wind tunnel tests of high aspect ratio supercritical wings suitable for a medium range, narrow body transport aircraft flying near M=0.80 were presented. The basic characteristics of the wing design were derived from system studies of advanced transport aircraft where detailed structural and aerodynamic tradeoffs were used to determine the most optimum design from the standpoint of fuel usage and direct operating cost. These basic characteristics included wing area, aspect ratio, average thickness, and sweep. The detailed wing design was accomplished through application of previous test results and advanced computational transonic flow procedures. In addition to the basic wing/body development, considerable attention was directed to nacelle/plyon location effects, horizontal tail effects, and boundary layer transition effects. Results of these tests showed that the basic cruise performance objectives were met or exceeded.

Henne, P. A.↗

Passively Cooled Superconductors Final Report

A highly reflective spray-on coating and tile material has been under development at Kennedy Space Center (KSC) that scatters away most of the Sun’s energy, thereby allowing coated objects to remain cool in space. The best performing tile material has achieved 1% solar absorptivity while the best performing spray-on coating has achieved around 4%. Both versions passively maintain cryogenic temperatures below 120 K at 1 astronomical unit (AU) from the Sun, but the tile material consistently sustains temperatures below 90 K, which is low enough to preserve oxygen and methane in a liquid state. Besides keeping propellants cold, this “solar white” material has the potential to passively maintain high-temperature superconductors (HTS) in a superconducting state without the support of liquid nitrogen cooling. If superconductors can be operated without the added infrastructure of liquid nitrogen cooling, it may enable them to be used in space for applications like magnetic radiation shielding and efficient energy management. Long duration exposure to both galactic cosmic radiation and coronal mass ejections can pose health risks for the astronauts and increase the potential for damage to electronics. This makes shielding essential to accomplish long duration missions, particularly when astronauts are onboard. The objective of this project was to determine the extent we could keep a high-temperature superconducting (HTS) material passively chilled to maintain its superconducting state. Both the tile and spray-on versions of solar white were investigated. We focused on finding a version that could support passive cooling at 1 AU from the Sun and determined the closest operating distances for samples that were unable to perform at 1 AU. Early in the project, we selected bismuth strontium calcium copper oxide (BSCCO) as the HTS to test based on its reputable usage in superconducting wires. The version we selected was Bi-2223, which has a critical temperature of about 108 K. Sample bars with contacts for a four-point probe were obtained from Quantum Levitation: https://quantumlevitation.com/product/superconductor-bar-for-4-point-tc-experiment/.

superconductors↗

Low‐PGM and PGM‐Free Catalysts for Proton Exchange Membrane Fuel Cells: Stability Challenges and Material Solutions

Abstract Fuel cells as an attractive clean energy technology have recently regained popularity in academia, government, and industry. In a mainstream proton exchange membrane (PEM) fuel cell, platinum‐group‐metal (PGM)‐based catalysts account for ≈50% of the projected total cost for large‐scale production. To lower the cost, two materials‐based strategies have been pursued: 1) to decrease PGM catalyst usage (so‐called low‐PGM catalysts), and 2) to develop alternative PGM‐free catalysts. Grand stability challenges exist when PGM catalyst loading is decreased in a membrane electrode assembly (MEA)—the power generation unit of a PEM fuel cell—or when PGM‐free catalysts are integrated into an MEA. More importantly, there is a significant knowledge gap between materials innovation and device integration. For example, high‐performance electrocatalysts usually demonstrate undesired quick degradation in MEAs. This issue significantly limits the development of PEM fuel cells. Herein, recent progress in understanding the degradation of low‐PGM and PGM‐free catalysts in fuel cell MEAs and materials‐based solutions to address these issues are reviewed. The key factors that degrade the MEA performance are highlighted. Innovative, emerging material concepts and development of low‐PGM and PGM‐free catalysts are discussed.

Du, Lei↗

Shape-Memory-Alloy-Based Deicing System Developed

Ice buildup on aircraft leading edge surfaces has historically been a problem. Most conventional deicing systems rely either on surface heating to melt the accreted ice or pneumatic surface inflation to mechanically debond the ice. Deicers that rely solely on surface heating require large amounts of power. Pneumatic deicers usually cannot remove thin layers of ice and lack durability. Thus, there is a need for an advanced, low-power ice protection system. As part of the NASA Small Business and Innovation Research (SBIR) program, Innovative Dynamics, Inc., developed an aircraft deicing system that utilizes the properties of Shape Memory Alloys (SMA). The SMA-based system has achieved promising improvements in energy efficiency and durability over more conventional deicers. When they are thermally activated, SMA materials change shape; this is analogous to a conventional thermal expansion. The thermal input is currently applied via conventional technology, but there are plans to implement a passive thermal input that is supplied from the energy transfer due to the formation of the ice itself. The actively powered deicer was tested in the NASA Lewis Icing Research Tunnel on a powered rotating rig in early 1995. The system showed promise, deicing both rime and glaze ice shapes as thin as 1/8 in. The first prototype SMA deicer reduced power usage by 45 percent over existing electrothermal systems. This prototype system was targeted for rotorcraft system development. However, there are current plans underway to develop a fixed-wing version of the deicer.

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