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NREL Marine Energy Desalination R&D Portfolio

The National Renewable Energy Laboratory (NREL), in collaboration with the U.S. Department of Energy's (DOE's) Water Power Technologies Office (WPTO), has developed a unique R&D approach to advance marine energy desalination. Desalination is a foundational investment within WPTO's Powering the Blue EconomyTM portfolio [1], and was the first investment within this portfolio. NREL's marine energy desalination spans techno-economic feasibility studies, numerical modeling, and laboratory testing at the component and subsystem level, as well as development of the Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC). This multilayered approach enables an innovative feedback loop where the data and lessons learned from laboratory and field experiments are used to refine modeling tools and analysis techniques, prioritize out-year activities, and refine strategic directions within NREL and across the WPTO portfolio. The primary objective of the NREL-led research is to identify key barriers associated with the commercialization of wave-powered desalination and develop solutions that can be adopted by the marine energy industry. It should be noted, while WPTO's marine energy portfolio includes wave, tidal, ocean current, thermal gradients, and pressure gradients the bulk of the marine energy desalination work has been focused on wave powered desalination. In parallel, these R&D activities can help inform technical assistance and support of industry and academic technologies. These two tracks help build a common solver community approach, while also identifying key stakeholders, government agencies, and other organizations outside of the marine sector that will be necessary for developing a robust industry.

desalination↗

Laboratory Directed Research and Development Program Activities (LDRD 2021 Annual Report)

Each year, Brookhaven National Laboratory (BNL) is required to provide a report of its completed Laboratory Directed Research and Development Program (LDRD) projects to the Department of Energy (DOE) Office of Scientific and Technical Information in accordance with DOE Order 413.2C Chg1 (MinChg) dated August 2, 2018. This report provides a detailed look at the scientific and technical activities for each of the LDRD projects funded by BNL in FY 2021, in fulfillment of that requirement. In FY 2021, the BNL LDRD Program funded 68 projects, 24 of which were new starts, at a total cost of $17.1M. The investments that BNL makes in its LDRD program support the Laboratory’s strategic goals. BNL has identified six scientific initiatives that define the Laboratory’s scientific future and that will enable it to realize its overall vision. This requires simultaneous excellence in all aspects of BNL’s work – from science and operations, to external partnerships with the local, state, and national communities, and beyond. This is enabled by safe, efficient, and secure operations; by an unwavering commitment to a diverse, equitable, and inclusive environment, including workforce development, both with staff and reaching out to the community; and by a strong focus on renewed infrastructure. The six scientific initiatives are: (1) Nuclear Physics: The Electron Ion Collider, (2) Clean Energy and Climate, (3) Quantum Information Science and Technology, (4) Discovery Science Driven by the Human-AI-Facility Integration, (5) High Energy Physics: Building for Discovery, and (6) Accelerating Isotope Production: Ensuring the Nation’s Supply is Secure. The funded projects support BNL’s six scientific initiatives and priority programs as well as new areas of research and competencies at the Laboratory that are consistent with the Laboratory’s vision and mission. In total, these LDRD investments supported 80 postdoctoral researchers and graduate students in whole or in part and resulted in 136 publications and 3 awards. This Program Activities Report represents the future of BNL science; it is an impressive body of exploratory work that investigates many scientific and technical directions in support of the DOE and BNL missions.

07 ISOTOPE AND RADIATION SOURCES↗

UAVSAR: A New NASA Airborne SAR System for Science and Technology Research

NASA's Jet Propulsion Laboratory is currently building a reconfigurable, polarimetric L-band synthetic aperture radar (SAR), specifically designed to acquire airborne repeat track SAR data for differential interferometric measurements. Differentian interferometry can provide key deformation measurements, important for studies of earthquakes, volcanoes and other dynamically changing phenomena. Using precision real-time GPS and a sensor controlled flight management system, the system will be able to fly predefined paths with great precision. The expected performance of the flight control system will constrain the flight path to be within a 10 m diameter tube about the desired flight track. The radar will be designed to be operable on a UAV (Unpiloted Aria1 Vehicle) but will initially be demonstrated on a NASA Gulfstream III. The radar will be fully polarimetric, with a range bandwidth of 80 MHz (2 m range resolution), and will support a 16 km range swath. The antenna will be electronically steered along track to assure that the antenna beam can be directed independently, regardless of the wind direction and speed. Other features supported by the antenna include elevation monopulse and pulse-to-pulse re-steering capabilities that will enable some novel modes of operation. The system will nominally operate at 45,000 ft (13800 m). The program began as an Instrument Incubator Project (IIP) funded by NASA Earth Science and Technology Office (ESTO).

synthetic aperture radar (SAR)↗

Application of an Embedded Fracture and Borehole Modeling Approach to the Understanding of EGS Collab Experiment 1

EGS Collab is a series of meso-scale experiments and associated numerical simulation activities being funded by the United States Department of Energy, Geothermal Technologies Office (GTO) to investigate enhanced geothermal system processes under in-situ stress and slightly elevated temperature conditions. This project is designed to provide scientists and engineers with immediate access to impermeable rock at scales larger than possible in the laboratory, but generally smaller than those for commercial production. Immediate access to rock is provided via the existing drifts of the former Homestake Gold Mine, now operated as the Sanford Underground Research Facility in Lead, South Dakota. The objectives of the EGS Collab project are to develop well controlled fracture networks between injector and producer boreholes using normal and shear stimulation for permeability enhancement. The first experimental site was located off the West Access drift on the 4850 Level (4850 feet below ground surface) in phyllite of the Precambrian Poorman formation, and involved the creation of a fracture network comprising a combination of hydraulic and natural fractures. A second experimental site is now being considered near the battery alcove on the 4100 Level in amphibolite and rhyolite of the Yates Unit. Data generated during these experiments will be compared against predictions of a suite of computer codes specifically designed to solve problems involving coupled thermal, hydrological, geomechanical, and geochemical processes. Comparisons between experimental and numerical simulation results will provide code developers with direction for improvements and verification of process models, build confidence in the suite of available numerical tools, and ultimately identify critical future development needs for the geothermal modeling community. Moreover, conducting thorough comparisons of models, modelling approaches, measurement approaches and measured data, via the EGS Collab project, will serve to identify techniques that are most likely to succeed at the Frontier Observatory for Research in Geothermal Energy (FORGE), the GTO’s flagship EGS research effort. Experiment 1 has comprised a series of successful tests, including a long-term chilled-water circulation test, but the testbed has two atypical EGS elements. Active ventilation in the adjacent drift over a 50-year period cooled the testbed rock mass and hydraulic fracturing intersected monitoring boreholes making them conduits for fluid flow. Numerical simulations executed in support of the design of the EGS Collab Experiment 1, computed a radial temperature distribution and stress gradient orthogonal to the drift axis, resulting in the forecast of an oblong hydraulic fracture geometry, extended in the direction of the drift from the stimulation borehole. This paper describes the numerical simulation of long-term chilled-water circulation test with an embedded fracture and borehole modeling approach. The principal objective of the simulation work is show agreement between experimental observations in terms of production fluid temperatures, monitoring borehole temperatures, injection and production pressures, and tracer recoveries using a single conceptual model for the fracture network, using characterization and monitoring data generally available for EGS. A secondary objective is to improve the numerical simulation result comparisons with additional data available from the broader monitoring equipment within the testbed versus deeper, hotter, and more remote EGS. One complicating factor for comparisons between the numerical simulation results and experimental observations, is the Joule-Thomson heating associated with large pressure drops across the fracture network.

numerical simulation, embedded fractures and boreh↗

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗

The NASA Space Radiation Laboratory

The Space Radiation Element (SRE) of the Human Research Program (HRP) aims to establish a robust biospecimen and tissue sharing collection (BTSC) to improve sample collection, tracking, access, distribution, and usability to maximize scientific return with intention. Future missions to the Moon, Mars, and beyond will require the appropriate characterization and mitigation of the many of the health risks associated with cosmic radiation exposure. An ongoing partnership between the National Aeronautics and Space Agency (NASA) and the Office of Science for the U.S. Department of Energy (DOE) has established the NASA Space Radiation Laboratory (NSRL) at the DOE Brookhaven National Laboratory (BNL) to create a space radiation ground-analog. NSRL provides the capability to use simulated space radiation with high energy ion beams for assessment of biological outcomes relevant space radiation risks as well as electronics testing for avionics safety. Current NSRL irradiation capabilities include a variety of exposure variables available for experimental needs: - Up to approximately 10 Gy/min dose-rates with a 20 × 20 cm 2 beam area. - Down to several hundred particles within a 60 × 60 cm 2 beam area. - Dose fractionation across multiple days is also possible. - For most radiobiology experiments the exposure structure, referred to as “spills”, has a 4 second repetition time where ions are extracted uniformly during a 0.3-0.4 second spill, followed by a ~3.6 second recovery time when the beam is off. - Both single or mixed-beam field irradiations are possible including a full 33-beam GCRSim and 6-beam SimGCRSim. Biological experiment capabilities: Two labs for Cell/tissue culture procedures can be conducted in two lab spaces with a separate lab available for sample processing that contains two chemical fume hoods. Sixteen fully equipped cell culture laboratories are available in the NSRL’s Long Term Support area in the Medical Building. The current vivarium configuration can support approximately 8,000 rodents/year for animal-based experiments. The NSRL area animal husbandry system includes five caging racks with 48 spaces in each coupled to a ventilation/filtration system in largest room, and two smaller rooms with conventional caging systems. Schedule: The NSRL is nominally open for experiment scheduling during three runs per year; Spring (March – May), Summer (May - June), and Fall (Sept – Nov). NASA funding is not required for biological and electronic testing experiments at the NSRL.

Jason M Weeks↗

Uncertainty and Sensitivity Analysis Methods and Applications in the GDSA Framework (FY2021)

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Fuel Cycle Technology (FCT) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). Two high priorities for SFWST disposal R&D are design concept development and disposal system modeling. These priorities are directly addressed in the SFWST Geologic Disposal Safety Assessment (GDSA) control account, which is charged with developing a geologic repository system modeling and analysis capability, and the associated software, GDSA Framework, for evaluating disposal system performance for nuclear waste in geologic media. GDSA Framework is supported by SFWST Campaign and its predecessor the Used Fuel Disposition (UFD) campaign. This report fulfills the GDSA Uncertainty and Sensitivity Analysis Methods work package (SF-21SN01030404) level 3 milestone, Uncertainty and Sensitivity Analysis Methods and Applications in GDSA Framework (FY2021) (M3SF-21SN010304042). It presents high level objectives and strategy for development of uncertainty and sensitivity analysis tools, demonstrates uncertainty quantification (UQ) and sensitivity analysis (SA) tools in GDSA Framework in FY21, and describes additional UQ/SA tools whose future implementation would enhance the UQ/SA capability of GDSA Framework. This work was closely coordinated with the other Sandia National Laboratory GDSA work packages: the GDSA Framework Development work package (SF-21SN01030405), the GDSA Repository Systems Analysis work package (SF-21SN01030406), and the GDSA PFLOTRAN Development work package (SF-21SN01030407). This report builds on developments reported in previous GDSA Framework milestones, particularly M3SF 20SN010304032.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Highly Accelerated UV Stress Testing for Transparent Flexible Frontsheets

There are many photovoltaic (PV) applications where lighter weight and/or bendable PV power would be beneficial. This includes the curved surfaces of buildings, buildings with weight limitations, boats, automobiles, or other portable applications. In many of these cases, the bending will be only a single occurrence at installation or the amount of bending, even if repeated, is not dramatic. This allows for crystalline silicon modules to be used. For flexible applications, the dominant material for the frontsheet is polyethylene tetrafluoroethylene (PETFE). As a fluoropolymer it resists soiling, is UV stable, and PETFE is a more mechanically durable fluoropolymer. However, in the interests of keeping costs down, less expensive alternative polymers are desirable. In this study, highly accelerated ultraviolet light and heat stresses are applied to candidate materials and the degradation kinetics are determined to provide information to evaluate their suitability for use in a PV application.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Advances in Uncertainty and Sensitivity Analysis Methods and Applications in GDSA Framework.

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Fuel Cycle Technology (FCT) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). Two high priorities for SFWST disposal R&D are design concept development and disposal system modeling. These priorities are directly addressed in the SFWST ''Geologic Disposal Safety Assessment'' (GDSA) control account, which is charged with developing a geologic repository system modeling and analysis capability, and the associated software, ''GDSA Framework'', for evaluating disposal system performance for nuclear waste in geologic media. ''GDSA Framework'' is supported by SFWST Campaign and its predecessor the Used Fuel Disposition (UFD) campaign. This report fulfills the GDSA Uncertainty and Sensitivity Analysis Methods work package (SF-20SN01030403) level 3 milestone — ''Advances in Uncertainty and Sensitivity Analysis Methods and Applications in GDSA Framework'' (M3SF-20SN010304032). It presents high level objectives and strategy for development of uncertainty and sensitivity analysis tools, demonstrates uncertainty quantification (UQ) and sensitivity analysis (SA) tools in GDSA Framework in FY20, and describes additional UQ/SA tools whose future implementation would enhance the UQ/SA capability of ''GDSA Framework''. This work was closely coordinated with the other Sandia National Laboratory GDSA work packages: the GDSA Framework Development work package (SF- 2051\101030404), the GDSA Repository Systems Analysis work package (SF-2051\101030405), and the GDSA PFLOTRAN Development work package (SF-20SN01030406). This report builds on developments reported in previous ''GDSA Framework'' milestones, particularly M2SF- 19SNO1030403.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Restoration Hydro: A Watershed Approach to Standard Modular New Hydropower

The objectives of FOA DE- FOA-0001836- “Standard Modular Hydropower” included designing a standardized, modular, and environmentally compatible hydropower schematic for implementation in greenfield sites that generate up to 10 MW of capacity. Utilizing funds competitively awarded under DOE’s Water Power Technologies Office, the Natel Energy team developed a concept for modular new stream reach (NSR) hydropower that incorporates multi species upstream and downstream fish passage, improved river channel connectivity, and recreational modules. The in-stream design of the collective modules minimized site specific design and maximized the opportunities for modularity. Financial data was also presented using actual costs from regional suppliers, with figures provided in 2022 dollars. While the project team did not address potential permitting process improvements, the site selection criteria did consider established barriers to hydropower development such as tribal and preserved lands, interconnection proximity, and endangered species to exclude or deprioritize. The project’s design schematic met the objectives of the FOA, and presented a unique solution that targets alluvial pockets as natural features for sustainable development. Natel’s concept also incorporated the company's fish-safe Restoration Hydro Turbine for safe downstream passage, while featuring a rock arch that integrates fish passage, water, recreation, and grade control modules (including sediment). Alignment with the Department of Energy Office of Energy Efficiency and Renewable Energy (EERE) “Innovative Design Concepts for Standard Modular Hydropower and Pumped-Storage Hydropower” Program: According to the Hydropower Vision (DOE, 2016), approximately 16 GW of hydropower growth is possible with the development of technology solutions that balance efficiency, economics, and environmental sustainability. The desired outcome of the SMH program is transformational innovation specifically in the site identification, conceptual, and detailed design phases of technology development lifecycles (DOE, 2018). In developing the SMH design schematic, the team aimed to address the opportunities outlined in the Vision through an inverted design philosophy; rather than singularly prioritizing efficiency and power production, the team focused on integrating hydropower with restoration of degraded streams to optimal ecosystem function and provision of exceptional recreation value as design criteria. To achieve this, Restoration Hydro incorporates the principles of nature-based engineering (WWAP, 2018) and biomimicry (Biomimicry NL.) to strategically deploy complementary combinations of permanent, semi-permanent, and ephemeral low-head structures - such as natural and engineered log jams - that harness geomorphological and hydrological processes at the landscape-scale. Primary applications of Restoration Hydro include: 1) restoration of degraded watersheds’ natural ecological function and enhancement of hydrological connectivity; and 2) creation of associated co-benefits to hydro production, including increased groundwater recharge, improved sediment transport and management, improved water security and water quality. Restoration Hydro projects build upon proven watershed restoration engineering techniques by integrating hydropower turbines into low-head structures using innovative and evolving civil works concepts that facilitate fish and sediment passage, and in some cases create additional revenue-generating recreational opportunities. Powering low-head structures creates a directly monetizable layer of economic value in the form of flexible, reliable, renewable energy on top of the already high-value water, environmental and recreational benefits of watershed and river restoration. The approach aims to create a virtuous, self-reinforcing cycle whereby Restoration Hydro projects support the scaling of ecosystem restoration activities, creating a water-energy-carbon multiplier effect that, through the principles of adaptive change management: 1) improves the resilience of landscapes and downstream population centers for changing hydrological cycles; 2) creates a reliable energy resource that facilitates the integration of intermittent renewable power sources into grids; and 3) supports climate change mitigation through grid decarbonization and enhanced ecosystem carbon capture and retention.

13 HYDRO ENERGY↗

EV Charging Infrastructure Energization: An Overview of Approaches for Simplifying Processes and Accelerating Timelines to Processing EV Charging Load Service Requests

The United States has seen significant growth in electric vehicle (EV) adoption, leading to increased demand for EV charging infrastructure and electricity. Growth in electricity demand from EV charging, coupled with growth in other sectors like data centers and electrification of other sectors, is impacting electricity infrastructure and load service request processes after two decades of relatively flat electricity demand. While most electric vehicle charging occurs at home, enroute and depot charging for medium and heavy-duty vehicles, both using high-powered EV charging, are critical to meet electric vehicle operational needs. Over the past decade, EV charging infrastructure site developers, site hosts, and electric distribution utilities have navigated the process to integrate chargers onto the electric grid. Site developers and site hosts have expressed distress that the integration process for high-powered EV charging projects does not meet the needs of the EV market for timeliness or cost. High-powered charging stations typically require a load service request or an agreement with the local utility to connect to the grid. The process of energizing a new high-powered charging site can be complex and time consuming, often taking up to 2 years. This timeline is the result of current utility energization processes having been designed for construction projects that take longer to build (i.e., buildings). The specific challenges stem from various factors, including compartmentalization in application processes, the integration of EV charging process approvals with other distributed energy resources (DERs), and the need to ensure grid reliability. The energization process needs to evolve to meet the growing demand for high-powered EV charging. This white paper compiles information gathered through various conversations with key stakeholders, including utilities, utility regulators, EV charging operators, site developers, and authorities having jurisdiction (AHJ) as well as through an extensive literature review. This document identifies the challenges and provides potential solutions to streamline the process of connecting EV charging infrastructure to the power grid in the United States, serving as a starting point for future conversations around these solutions.

33 ADVANCED PROPULSION SYSTEMS↗

FY24 Integrated Results for High-Temperature Mechanical Testing of LPBF 316H Stainless Steel

This report provides the mechanical test data of laser powder bed fusion (LPBF) 316H stainless steel (SS) collected during Fiscal Year 2024 (FY 24) under the US Department of Energy, Office of Nuclear Energy’s Advanced Materials and Manufacturing Technologies program, along with the current state of microstructural-based understandings of the behaviors. Materials with variabilities in manufacturing site, machine, laser parameters, powder chemistry, porosity, specimen geometry and heat treatment were tested in high-temperature tension, creep, fatigue and creep-fatigue. Electron microscopy and optical microscopy were performed on selected materials before and after the tests to provide microstructural-based understandings to the mechanical behavior. It was discovered that the as-built (AB) and stress-relieved (SR) materials exhibit similar behaviors in tension and creep, as do the solution-annealed (SA) and hot-isostatic pressed (HIP) materials. The AB and SR materials are softer but more ductile than the SA and HIP materials in tension. In creep, the LPBF materials have comparable rupture times but lower rupture strains compared to the wrought materials. The AB and SR materials have low creep rupture strains (<10%) when tested at 720°C and 800°C, while the SA and HIP materials are much more ductile. The LPBF materials exhibit large scatter in fatigue and creep-fatigue lives. The cyclic lives of creep-fatigue tests are lower than those of fatigue tests. In fatigue and creep-fatigue, SR materials outperform SA materials. A common observation from the cyclic tests is that, given the same post-build heat treatment, a lower initial peak stress generally results in a longer cyclic life regardless of hold time. It was also discovered that the batch variation can be more impactful than heat treatment, as demonstrated by the overall better performance of one batch of material than another, regardless of the heat treatment. The results provided insights into how different factors impact the behaviors of LPBF 316H SS. An outlook to FY 25 work scope is provided.

36 MATERIALS SCIENCE↗

Artificial Intelligence and Machine Learning for Bioenergy Research: Opportunities and Challenges

The integration of artificial intelligence and machine learning (AI/ML) with automated experimentation, genomics, biosystems design, and bioprocessing technologies is poised to revolutionize scientific investigation and, particularly, bioenergy research. To identify the opportunities and challenges in this emerging research area, the U.S. Department of Energy’s (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23–25, 2022. These interests have since been amplified in a September 2022 Executive Order, “Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure U.S. Bioeconomy,” to promote a whole-of government approach to biotechnology development (White House 2022). Approximately 50 scientists with various backgrounds and expertise from academia, industry, and DOE national laboratories met to discuss the opportunities and challenges of AI/ML for bioenergy research. Workshop participants were tasked with assessing the potential for AI/ML and laboratory automation to advance biological understanding and engineering in general. They particularly examined how integrating AI/ML tools with laboratory automation could accelerate biosystems design and optimize biomanufacturing. Discussions included the data and computational infrastructure needed to augment biosystems design applications and the expertise and workforce development efforts urgently required to shift integrated systems toward bioenergy research more broadly. Participants discussed many existing and future applications of AI/ML for biosystems design ranging from enzymes to plants and microbes, microbiomes, and bioprocess development. They also identified three key categories of scientific and technical opportunities and challenges: high-quality data, AI/ML algorithms, and laboratory automation. Several main takeaways emerged from the workshop: 1. Numerous AI/ML and automated experimentation applications exist for a variety of DOE mission needs in energy and the environment; 2. Exemplary research grand challenges for which AI/ML could provide solutions include: building microbes and microbial communities to specifications, developing closed-loop autonomous design and control for biosystems design, and advancing scale-up and automation; 3. Lack of sufficient high-quality, annotated data hinders the development of AI/ML applications; 4. New and improved AI/ML tools are needed, particularly those meeting the specific needs of the BER and BETO research communities; 5. Trade-offs in performance, cost, and reliability exist between deploying commercially available versus building custom-developed instrumentation and software for automated or autonomous experimentation; translation of manual to automated or autonomous methods is often a nontrivial endeavor; 6. Training a new generation of young scientists who can develop and apply AI/ML tools is needed to solve long-standing scientific challenges in bioenergy research. The integration of AI/ML tools and automated experimentation represents a new data-driven research paradigm complementary to the traditional hypothesis-driven research paradigm. This paradigm accelerates design and optimization of biological systems and processes for a variety of DOE mission needs in energy and the environment. The AMBER workshop broadly explored the potential of this new paradigm for bioenergy research, of particular interest to BER and BETO, and identified key challenges and opportunities that DOE can address in the coming years by leveraging its unique capabilities and resources.

59 BASIC BIOLOGICAL SCIENCES↗

Information Technology Support in the 8000 Directorate

My summer internship was spent supporting various projects within the Environmental Management Office and Glenn Safety Office. Mentored by Eli Abumeri, I was trained in areas of Information Technology such as: Servers, printers, scanners, CAD systems, Web, Programming, and Database Management, ODIN (networking, computers, and phones). I worked closely with the Chemical Sampling and Analysis Team (CSAT) to redesign a database to more efficiently manage and maintain data collected for the Drinking Water Program. This Program has been established for over fifteen years here at the Glenn Research Center. It involves the continued testing and retesting of all drinking water dispensers. The quality of the drinking water is of great importance and is determined by comparing the concentration of contaminants in the water with specifications set forth by the Environmental Protection Agency (EPA) in the Safe Drinking Water Act (SDWA) and its 1986 and 1991 amendments. The Drinking Water Program consists of periodic testing of all drinking water fountains and sinks. Each is tested at least once every 2 years for contaminants and naturally occurring species. The EPA's protocol is to collect an initial and a 5 minute draw from each dispenser. The 5 minute draw is what is used for the maximum contaminant level. However, the CS&AT has added a 30 second draw since most individuals do not run the water 5 minutes prior to drinking. This data is then entered into a relational Microsoft Access database. The database allows for the quick retrieval of any test@) done on any dispenser. The data can be queried by building number, date or test type, and test results are documented in an analytical report for employees to read. To aid with the tracking of recycled materials within the lab, my help was enlisted to create a database that could make this process less cumbersome and more efficient. The date of pickup, type of material, weight received, and unit cost per recyclable. This information could then calculate the dollar amount generated by the recycling of certain materials. This database will ultimately prove useful in determining the amounts of materials consumed by the lab and will help serve as an indicator potential overuse.

FROM↗

Final DOE-ASR Report for the Project “Using LASSO to bridge the gap between model and observations and to learn about atmospheric convection”

Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.

54 ENVIRONMENTAL SCIENCES↗

Capsulation Satellite or CapSat: A Low-Cost, Reliable, Rapid-Response Spacecraft Platform

The National Aeronautics and Space Administration (NASA) Goddard's Rideshare Office estimates that between 2013 and 2022, NASA launches of primary satellites will have left unused more than 20,371 kilograms of excess capacity. This equates to hundreds of millions of dollars in launch-vehicle costs going unutilized. To fill this void with a standard CubeSat or SmallSat spacecraft platform, which when required to be more reliable, still will cost in the neighborhood of $1M a kilogram, making it prohibitively expensive. A newly proposed solution, which NASA is pursuing, is called the Capsulation Satellite or CapSat. CapSat is a modularized, pressurized, thermally controlled spacecraft designed to host ruggedized commercially available instrumentation in a terrestrial like environment on orbit. Using a technique that is under review for a patent, CapSat actively manages internal air temperatures in a manner similar to a household thermostat. This gives CapSat high-thermal stability, which, in turn, provides component longevity. CapSat was specifically designed to take advantage of the United States Air Force (USAF) Rideshare Program and the Evolved Expendable Launch Vehicle Secondary Payload Adaptor, or ESPA ring. The ESPA ring comes in two sizes: standard and Grande. CapSat primarily will take advantage of the ESPA Grande to provide a 300-kilogram payload capability per attachment point, with up to four attachment points per ring. This approach combines a high-mass capability with a proven Rideshare mechanical interface and secondary payload management infrastructure. Opportunities for ESPA based co-manifests are continuing to expand. The CapSat program is currently funded to design and build a limited prototype and perform thermal-vacuum testing. CapSat is currently in the concept/study phase for both single missions and constellation of earth- and space-observing missions. One of these studies includes land imaging using state-of-the-art advanced infrared detector technology. This paper will report on the current status of the CapSat hardware design, testing, and results as well as any openly available advanced concept study results. The CapSat solution is intended to be a game-changing paradigm shift. CapSat will repurpose currently available, already-proven technology to reduce spaceflight hardware costs to less than $50,000 per kilogram.

Burt, Joe↗

Lunar Glovebox Balance with Wireless Technology

The most important equipment required for processing lunar samples is a high-quality mass balance for maintaining accurate weight inventory, security, and scientific study. After careful review, a Curation Office memo by Michael Duke in 1978 chose the Mettler PL200 to be used for sample weight measurements inside the gloveboxes (Fig. 3). These commercial off-the-shelf (COTS) balances did not meet the strict accepted material requirements in the Lunar lab. As a result, each balance housing, weighing pan, and wiring was custom retrofitted to meet Lunar Operating Procedure (LOP) 54 requirements [for material construction restrictions]. The original design drawings for the custom housings, readout support stands, and wiring were done by the JSC engineering directorate. The 1977- 1978 schematics, drawings, and files are now housed in the curation Data Center. Per the design specifications, the housing was fabricated from aluminum grade 6061 T6, seamless welds, and anodized per MIL-A-8625 type I, class I. The balance feet were TFE Teflon and any required joints were sealed with Viton A gaskets. The readout display and support stands outside the glovebox were fabricated from 300 series stainless steel with #4 finish and mounted to the glovebox with welded bolts. Wire harnesses that linked the balance with the outside display and power were encapsulated with TFE Teflon and transported through custom Deutsch wire bulk head pass-through systems from inside to outside the glovebox. These Deutsch connectors were custom fabricated with 316L stainless steel bodies, Viton A O-rings, aluminum 6061 with electroless nickel plating, Teflon (replacing the silicone), and gold crimp connectors (no soldering). Many of the Deutsch connectors may have been used in the Apollo program high vacuum complex in building 37 and date to about 1968 to 1970.

Zeigler, Ryan A.↗