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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Parametric studies of stream instability-induced higher harmonics in plasma ionization breakdown near an emissive dielectric surface

Here, in this work, we comprehensively investigate the generation of higher harmonic (HH) electric fields normal to the applied rf electric field in multipactor-coexisting plasma breakdown by fully kinetic particle-in-cell (PIC) simulations and a theoretical model. Firstly, a base case at driving frequency 1 GHz, transverse rf electric field amplitude 3 MV m –1 , and background gas pressure 0.2 Torr, is studied in detail. The enhanced harmonic frequency observed is around ten times the fundamental rf frequency, significantly lower than the Langmuir frequency. A theoretical model reveals that the fundamental mechanism of HHs generation is stream–plasma instability, which originates from stream-like secondary electron emission interacting with plasma. The resulting HH frequency and the growth rate of its oscillating amplitude from the theoretical model, agree well with the PIC simulations. With increasing pressure, the HH oscillations are found to be significantly reduced. This is because at higher pressure the gas ionization rate is higher, which causes a more rapidly increasing plasma density, leaving less time for the growth of instability. Furthermore, the parameter space in terms of background gas pressure and rf field amplitude within which the HHs appear is revealed. Finally, the effect of the driving rf frequency on HHs is also investigated, and it is found that the instability-induced oscillating HHs field remains when the driving frequency is increased to 2 GHz, however, it is highly reduced at higher driving frequency of 5 GHz, as oscillations at the fundamental frequency start playing a more important role.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Environmental Flow Requirements from FERC Licenses Across the US

Environmental flow requirements included in Federal Energy Regulatory Commission (FERC) hydropower licenses are important for balancing natural properties and benefits of river ecosystems (e.g., healthy species, recreation, water supply, flood control) supporting hydropower production. In some cases, environmental flow requirements may limit operational flexibility given current operational schemes and make a hydropower plant less able to provide power to the electric grid on demand. Hydropower plants may gain some flexibility as hydropower scheduling time periods are made to be more responsive to the short-term needs of an energy grid increasingly reliant on intermittent renewables. However, many flow requirements focus on the daily, monthly, or seasonal flow fluctuations which matches the time scale of most paradigms linking flow alterations to the health of river ecosystems. This dataset seeks to provide a greater understanding of how flexibility in environmental requirements can be leveraged to create positive outcomes for both the power system and the environment. It contains information on environmental flow requirements from the Protection, Mitigation, and Enhancement section of 50 randomly selected FERC licenses: 25 issued from 1998-2013 that were also included in the ORNL Mitigation Database (Schramm et al. 2015) and 25 issued from 2014-present. The information on environmental flow requirements was extracted from the PM&E section of 50 randomly selected FERC licenses: 25 issued from 1998-2013 that were also included in the ORNL Mitigation Database (Schramm et al. 2015) and 25 issued from 2014-present. The flow requirements were then categorized into flow augmentation categories based on whether the license stated a specific water management purpose for the given requirement called augmentation categories (i.e., fisheries or habitat, recreation or boating, industry, and general or unspecified; Table B). Requirements were also grouped into flow type categories (e.g., minimum flow rate, maximum flow rate, ramping rate). Additional information related to flow requirements such as the augmentation time-period and whether the flow rate was continuous (i.e., condition must be present at all-times) or instantaneous (i.e., condition present at a point in time) was also extracted from the licenses. Some licenses had specific flow requirements based on whether the project was in a wet, dry, or normal water year. If that information was presented in the license, it was also included in the data set. The location within the project was noted, hereafter, zone, in the dataset for flow requirements relating to specific areas of hydropower projects (Dam, Powerhouse, Bypass Reach). Maximum discharge capacities of hydropower facilities were also extracted from both the Existing Hydropower Assets (EHA) data set and the National Inventory of Dams (NID) databases. Each facility was coded with project identification codes from the EHA dataset to facilitate cross-referencing between datasets.

13 HYDRO ENERGY↗
DOE OSTI2024

Characterization of Nitrate, Nitrite, Ammonia, and Tritium in D0220 Cores

This report describes characterization of nitrogen species (nitrate, nitrite, ammonia) in aqueous and solid phases in cores taken in borehole D0220 (well 299-E25-245) under crib 216-A-37-1 at the Hanford Site in 2022 to evaluate (a) the types of nitrogen species currently in the vadose zone and (b) the migration of nitrogen species in the vadose zone. Ammonia and tritium from PUREX decladding condensate were sporadically discharged to the crib from 1977 to 1989. During discharge operations, the estimated travel time through the vadose zone to groundwater was 2.5 to 9 months. By 2003, a characterization borehole (C4106) showed residual pore water with elevated tritium and nitrate in the first 100 ft of the vadose zone, which is likely from the crib. However, there was significantly more nitrate present at the shallowest depth (15 to 22 ft), which may indicate a different source for nitrate, such as adsorbed ammonia slowly being oxidized or nitrogen species precipitates slowly dissolving. In this study, more extensive nitrogen species characterization was done on D0220 cores (drilled in 2022) at 40- and 262-ft depths, which included (a) aqueous nitrate, nitrite, and tritium; (b) adsorbed ammonia; (c) nitrogen in carbonates (or other minerals dissolved in acidic acid); (d) nitrogen in iron oxides (or other minerals dissolved in oxalic acid); and (e) nitrogen in hard-to-extract minerals (minerals dissolved in nitric acid). High pore water nitrate (226 to 331 mg/L) at 40-ft depth measured in D0220 (2022) compared to 60 mg/L at 40-ft depth in C4106 (2003) may indicate nitrate is migrating deeper. Tritium concentrations (pore water 132,000 to 148,000 pCi/L) measured in D0220 at 40-ft depth in 2022 were considerably higher than in C4106 at 40-ft depth (160 pCi/L). Additional nitrogen species mass was present in adsorbed and precipitated phases in D0220 cores. Low adsorbed ammonia was measured at 40.1- and 261.7-ft depths. Low concentrations of carbonate associated nitrogen and iron oxide-associated nitrogen were present at 40.1 and 40.6 ft depths. Nitrogen species in solid phase extractions indicate nitrogen precipitates or aqueous nitrate or ammonia trapped in sediment microfractures that are coated by precipitates. Overall, the nitrogen species and tritium characterization at two depths in D0220 showed that additional nitrogen species were present in the vadose zone. In addition, elevated pore water nitrate in D0220 at 40 ft depth from 2022 may indicate vertical migration compared to C4106 nitrate profile from 2003. Analysis of additional depths in D0220 and spatial variability of the nitrate plume along the length of the crib (from surface electrical resistivity) would be extremely useful for this comparison.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Dual Purpose – Heating & Cooling – Thermal Battery for Flexible and Energy-Efficient Heat Pump Systems

The integration of heat pumps with thermal energy storage (HP-TES) systems is gaining attention as a viable solution for managing peak building demand driven by immense cooling and heating loads. With growing reliance on renewable energy sources, thermal energy storage offers an excellent opportunity to mitigate mismatches in thermal load between energy supply and demand. The use of phase-change material (PCM) TES is especially promising, as PCMs offer significant latent energy storage capacity with smaller temperature glides in smaller volumes compared to other TES technologies. However, challenges arise because current HP-TES architectures can load-shift only cooling or heating, not both, requiring two systems and thus doubling cost, weight, and footprint. Furthermore, current research efforts lack specific tools and techniques to advance integrated systems from concept design to end-user application, focusing on only discharge performance. To address these challenges, this research proposes a dual-mode (heating and cooling) integrated HP-TES system that uses room-temperature PCM-TES as a high-temperature heat source in heating mode and a low-temperature heat sink in cooling mode, thereby reducing temperature lifts and compressor power. Design criteria for PCM-TES heat exchangers were developed, balancing thermal-hydraulic performance with practical constraints such as available building space and weight requirements along with PCM selection considerations such as shipping conditions, moisture exposure, and number of available cycles. A detailed transient model for HP-TES systems was developed to enable rapid annual performance assessments in any US climate zone.

42 ENGINEERING↗
DOE OSTI2020

TRANSENSOR: Transformer Real-time Assessment INtelligent System with Embedded Network of Sensors and Optical Readout. Final Report

Utilities across the world are wrestling with evolving market dynamics, population growth and climate change. Distributed Energy Resources (DERs) such as solar photovoltaics, distributed generators and energy storage systems are becoming important parts of the U.S. energy mix. These factors are driving an increasing need for low-cost grid asset monitoring. Aside from being costly, traditional utility monitoring systems are not sufficiently robust and do not provide real-time visibility into the condition of grid assets such as transformers. Lack of accurate real-time measurements on performance has resulted in the use of lagging indicators, such as oil sample analysis. To address this need, an innovative embedded optical sensing technology, Transformer Real-time Assessment Intelligent System (TRANSENSOR) was developed, validated and demonstrated in this project. To date, TRANSENSOR has focused on transformers but is extendable to other grid assets. In addition to the technology being embedded into new transformers during manufacturing, a retrofit configuration that can be installed on existing transformers in the field was also developed. It is anticipated that the ability to retrofit existing transformers will help accelerate adoption of the underlying TRANSENSOR technology. Phase 1 of the project focused on laboratory development and qualification of the technology. Following iterations and exploration of relevant optical sensing modalities and multiplexed configurations of interest for the transformer environment, an effective candidate configuration was agreed upon, down-selected and custom-designed for embedding into General Electric (GE) network transformers. Two new GE 500 kilovolt ampere (kVA), 27 kilovolt (kV) distribution network transformers were built with embedded fiber-optic (FO) sensors and successfully qualified per industry standards at GE’s Shreveport, Louisiana facility during Phase 1 of the project. Following the successful completion of Phase 1, the team proceeded to Phase 2, which focused on a field demonstration of the technology. Over Phase 2, the first new GE transformer built with embedded fiber-optic sensors was installed in an above-ground cage and connected to the grid at Con Edison’s Astoria facility. A second transformer equipped with TRANSENSOR was installed in an underground vault. Additionally, an older (1982 year model) GE transformer in an above-ground cage was retrofitted with fiber- optic sensors and reconnected to the grid at ConEd’s facility. Analysis of data acquired from the sensors showed interesting correlations with transformer loading. Additionally, key events such as transformer low-voltage network connection, primary-side energizing, and a pressure loss event from an oil sampling were detected by the TRANSENSOR system. Online data processing/feature extraction algorithms for the second transformer in the underground vault detected key features and event alerts that were transmitted through a wireless 4G connection. The remote deployment concept showed promising results with data collection running for a total of 8 months across the three (3) GE transformers instrumented for the Phase 2 field demonstration. This sets the stage well for further development and commercialization.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Considerations for Thermal Annealing of Zr-Alloy Cladding During Dry Storage

In January 2025, the U.S. Department of Energy (DOE) sponsored a technical workshop with fuel vendors that provided a forum for increased collaboration on backend fuel cycle research. The workshop reviewed observations of thermal annealing of irradiated zirconium alloys in simulated dry storage conditions and discussed implications to the industry’s interest in reducing wet storage to optimize operational flexibility and the expected trend of increasing discharge burnup (and decay heats), which could lead to an increase in dry storage temperatures. One approach to accommodate increased decay heats in dry storage is to increase the regulatory temperature limit during dry storage, which is now 400°C. However, this could lead to thermal annealing of the cladding, which will tend to increase creep rates, creep strains, and ductility while decreasing yield strength. These considerations are compounded by bonding between the pellet and cladding at high burnup, which results in the pellet carrying more load during fuel rod deformations, especially in bending, which is the dominant deformation phenomenon in canister drop analyses. Because the U.S. Nuclear Regulatory Commission (NRC) recommends yield strength as a primary failure criterion for accident analyses in storage and transportation, particularly for canister drop scenarios, the purpose of the workshop was to develop options for alternative failure criterion that could replace yield strength in canister drop analyses. Topics discussed were (1) the regulatory framework, (2) the effect of thermal annealing on microhardness and tensile properties of cladding materials, (3) the effect of thermal annealing on fuel rod failure during bending, bending fatigue, and pinch loading, and (4) an alternative failure criterion for canister drop analyses. This paper provides a summary of the key discussions and outcomes of the workshop

Cantonwine, Paul [ORNL] (ORCID:0009000522247033)↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2025

CERF: IM3 Projected Western US Power Plant Locations

Overview The Capacity Expansion Regional Feasibility (CERF) model is an open-source geospatial python package that provides new power plant locations at a 1km resolution. The model ingests U.S. state or regional-scale electricity system capacity expansion plans, such as those produced by the Global Change Analysis Model (GCAM-USA), and identifies feasible, site-specific locations for individual new power plants (renewable and non-renewable). CERF combines high-resolution geospatial suitability analyses with an economic algorithm that selects individual plant siting locations based on grid interconnection costs and the locational marginal value of new generation. The model incorporates a wide range of dynamic constraints and opportunities, such as protected lands, population density, existing infrastructure, and water availability. This dataset provides CERF power plant siting results for IM3 Phase 2 simulations across eight different scenarios for the Western US through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 CERF siting results in this dataset correspond to capacity expansion plans in the GCAM-USA IM3 Phase 2 simulation data and are available for each of the above scenarios. Data Details Temporal Range: 2015-2055 in 5-year timesteps. Note that 2015 is the experiment base year and 2020 and beyond represent model simulation years. Spatial Range: Plant locations are provided for the eleven states in the Western US including Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, and Wyoming. Spatial Resolution: 1 km-squared, provided in x and y coordinates Geospatial Projection: Albers Equal Area Conic (ESRI:102003) File Type: csv The dataset contains subdirectories for each of the eight scenarios described in the overview. Each scenario folder contains two subfolders with the following information: 1. Power Plant Data This directory contains a single .csv file of power plant locations for both pre-existing (non-CERF sited plants in operation in 2015) and new (CERF-sited) power plants across the temporal range along with additional CERF model output parameters for CERF-sited plants. Plant with a siting year earlier than 2020 correspond to facilities that are operational leading into the first timestep CERF simulation. For a more detailed description of CERF model output parameters, see the CERF model documentation. Note that the cerf_plant_id parameter is unique within each scenario file but not across scenario files. Parameter Descriptions scenario - Name of scenario cerf_plant_id - Unique siting identifier cerf_sited - If True, indicates that plant was sited by CERF model. If False, indicates pre-existing facility region_name - Name of region (state) tech_id - Technology ID tech_name - Full generation technology name inclusive of cooling type (if applicable) and additional characteristics tech_simple - Simplified generation technology type unit_size_mw - Power plant unit size (MW) xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) index - Index position in the flattend 2D array buffer_in_km - Exclusion buffer around site (km) sited_year - Year of siting retirement_year - Year of retirement lmp_zone - Locational marginal price (LMP) zone ID locational_marginal_price_usd_per_mwh - Locational marginal price ($/MWh) generation_mwh_per_year - Generation output (MWh/yr) operating_cost_usd_per_year - Cost of plant operations ($/yr) net_operational_value - Net operational value based on LMP and and operating costs ($/yr) interconnection_cost - Cost of interconnection for transmission & gas pipeline (if applicable) net_locational_cost -- Difference of interconnection cost and operating value ($/yr) capacity_factor_fraction - Capacity factor (fraction) carbon_capture_rate_fraction - Carbon capture rate (fraction) fuel_co2_content_tons_per_btu - Fuel CO2 content (tons/Btu) fuel_price_usd_per_mmbtu - Fuel price ($/MMBtu) fuel_price_esc_rate_fraction - Fuel price escalation rate (fraction) heat_rate_btu_per_kWh - Heat rate (Btu/kWh) lifetime_yrs - Technology lifetime for annuity (years) operational_life_yrs - Operational lifetime for retirement (years) variable_om_usd_per_mwh - Variable operation and maintenance costs of yearly capacity use ($/MWh) variable_om_esc_rate_fraction - Variable operation and maintenance costs escalation rate (fraction) carbon_tax_usd_per_ton - Carbon tax ($/ton) carbon_tax_esc_rate_fraction - Carbon tax escalation rate (fraction) 2. Storage Data This directory contains information on new and pre-existing energy storage facilities operational in each timestep along with various storage operational parameters. The 2015 timestep provides pre-existing energy storage data and corresponds with facilities that are operational leading into the first model simulation timestep. Note that coordinates in the storage files correspond to the interconnection point on the grid (substation location), not individual energy storage locations. Energy storage is added in a cumulative process at each given interconnection point. That is, each individual file provides the total operational storage capacity interconnected to the specified substation for the given timestep, inclusive of previously installed storage at that location and new storage installed in that timestep at that location. Parameters scenario - Name of scenario timestep - Simulation timestep name - Unique storage identifier s_typ - Type of energy storage technology (battery or pumped storage hydro) s_node - Node ID of interconnecting substation xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) charge_rate - Maximum charge rate (power capacity) of storage system (MW) discharge_rate - Maximum discharge rate (power capacity) of storage system (MW) duration - Duration of storage system (hours) max_SoC - Allowed maximum state of charge (energy capacity) of storage system (MWh) min_SoC -Allowed minimum state of charge (energy capacity) of storage system (MWh) charge_eff - Efficiency of charge (fraction between 0 and 1) discharge_eff - Efficiency of discharge (fraction between 0 and 1) 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.

CERF↗