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DOE OSTI2026

FAD-Toolset (Floating Array Design Toolset) [SWR-26-056]

The Floating Array Design (FAD) Toolset is a collection of tools for modeling and designing arrays of floating offshore structures. It was originally designed for floating wind systems but has applicability for many offshore applications. A core part of the FAD Toolset is the floating array model, which serves as a high-level library for efficiently modeling a floating array, such as a floating wind array. It combines site condition information and a description of the floating array design, and contains functions for evaluating the array's behavior considering the site conditions. For example, it combines information about site soil conditions, mooring line loads, and an array's anchor characteristics to estimate the holding capacity of each anchor. The library works in conjunction with the tools RAFT, MoorPy, and FLORIS to model floating platforms, wind turbines, mooring systems, power cables, and array wakes respectively. Layered on top of the floating array model is a set of design tools that can be used for algorithmically adjusting or optimizing parts of the a floating array. Specific tools existing for mooring lines, shared mooring systems, dynamic power cables, static power cable routing, and overall array layout. These capabilities work with the design representation and evaluation functions in the floating array model, and they can be applied by users in various combinations to suit different purposes. In addition to standalone uses of the FAD Toolset, a coupling has been made with Ard, (https://github.com/NLRWindSystems/Ard) a sophisticated and flexible wind farm optimization tool. This coupling allows Ard to use certain mooring system capabilities from FAD to perform layout optimization of floating wind farms with Ard's more advanced layout optimization capabilities. The FAD Toolset works with the IEA Wind Task 49 Ontology (https://github.com/IEAWindTask49/Ontology), which provides a standardized format for describing floating wind farm sites and designs. See example use cases in our examples folder (https://github.com/NLRWindSystems/FAD-Toolset/blob/main/examples/README.md) For working with the library, it is important to understand the floating array model structure, which is described more here: https://github.com/NLRWindSystems/FAD-Toolset/blob/main/fad/README.md.

Sirkis, Leah [National Laboratory of the Rockies (↗

DOE OSTI2024

AmeriFlux FLUXNET-1F US-Ro3 Rosemount- G19

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Ro3 Rosemount- G19. This is the FLUXNET version of the carbon flux data for the site US-Ro3 Rosemount- G19 produced by applying the standard ONEFlux (1F) software. Site Description - This tower is located in a farm field farmed in accordance with the cominant farming practice in the region: a corn/soybean rotation with chisel plow tillage in the fall following corn harvest and in the spring following soybeans.

Baker, John↗

DOE OSTI2024

AmeriFlux FLUXNET-1F US-UC1 LTAR UCB (Upper Chesapeake Bay) EC1

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UC1 LTAR UCB (Upper Chesapeake Bay) EC1. This is the FLUXNET version of the carbon flux data for the site US-UC1 LTAR UCB (Upper Chesapeake Bay) EC1 produced by applying the standard ONEFlux (1F) software. Site Description - Upper Chesapeake Bay farm is privately owned. The farming that took place was performed by the Farm Owner. The ground is rolling terrain, next to wooded areas, private resdiences and other large fields maintained by private land owners. At the time of this collection period, the site housed another Eddy Covariance System and a two Phenocams. Crop has been continuous corn with plans to rotate to alfalfa grass mixture.

Goslee, Sarah↗

DOE OSTI2024

AmeriFlux FLUXNET-1F US-UC2 LTAR UCB (Upper Chesapeake Bay) EC2

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UC2 LTAR UCB (Upper Chesapeake Bay) EC2. This is the FLUXNET version of the carbon flux data for the site US-UC2 LTAR UCB (Upper Chesapeake Bay) EC2 produced by applying the standard ONEFlux (1F) software. Site Description - Upper Chesapeake Bay farm is privately owned. The farming that took place was performed by the Farm Owner. The ground is rolling terrain, next to wooded areas, private resdiences and other large fields maintained by private land owners. At the time of this collection period, the site housed another Eddy Covariance System and a two Phenocams. Crop has been continuous corn with plans to rotate to alfalfa grass mixture.

Goslee, Sarah↗

DOE OSTI2025

Field Test Report Neutron Scintillator Array Dry Storage Cask Scanner FY2024

During two weeks of Field Testing at the Idaho National Laboratory INTEC Cask Farm in July and August 2024, the LLNL Dry Storage Cask Scanner Array was lifted on top of an MC-10 dry storage fuel cask and operated to acquire neutron and gamma-ray data from the 24 fuel bundle positions. Neutron and gamma-ray data acquisition scans across the top of the cask of varying dwell times were performed July 15-18, 2024 and August 19-22, 2024 to evaluate the ability of the scanner data to reveal asymmetries in the fuel positions that reflect asymmetries in the MC-10 cask fuel bundle loading. The MC-10 cask 24 position fuel bundle loading at the INTEC Cask Farm is well documented, including the locations of six empty fuel bundle positions. This loading presents an opportunity to test the ability of the scanner system to detect diversion of spent fuel bundles as well as to validate the MC-10 cask MCNP modeling. The cask scanner array consists of six Stilbene crystal scintillator detectors and a linear actuator frame that moves the six detectors across the MC-10 dry storage cask to obtain data above each of the 24 fuel bundle positions. The detectors are connected to a pulse-shape discrimination data acquisition system capable of generating separate neutron and gamma-ray spectra for each detector and for each scan position. From the prior single detector Field Test in 2021 and iteration with MCNP modeling, the neutron and gamma-ray data were analyzed in multiple energy regions to identify an analysis method that would provide the strongest and most consistent signature of the asymmetric MC-10 cask fuel loading1 . From both the 2021 Field Test and the current Field Test results, the neutron capture gamma-ray count rate around 2.2 MeV provides the strongest signature of the asymmetric MC-10 cask fuel loading and has qualitative agreement with MCNP calculations. Counting all gamma-rays produces a similar signature. Neutrons emerging from the cask top are moderated and captured by the hydrogen in the polyethylene moderator and scintillator detector, producing a 2.2 MeV gamma ray which is seen in the scintillator gamma-ray spectrum. The count rate in the 2.2 MeV gamma-ray region is ~50 c/s, which is ~1000x higher than the ~0.05 n/s rate in the > 4MeV neutron region, and ~50x greater than the ~1 n/s rate in the neutrons > 500 keV region. Analysis of the 2.2 MeV neutron-capture Compton-scattered gamma-rays produces a statistically significant signature of the INTEC Cask Farm MC-10 asymmetric fuel loading. MCNP simulations indicate that the average neutron energy spectrum offers the potential to detect a large asymmetry from several missing bundles as well as individual missing fuel bundles. Testing this feature will require measurements on a cask with single missing elements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Wind Plant Flow Physics and Power Performance in Complex Environments: Cooperative Research and Development (Final Report)

Cornell University will partner with NLR on the topic of wind farm wake effects to improve understanding of interactions between complex atmospheric flows, terrain, and wind turbine wakes and plant efficiency. Wind plant flow simulation tools will also be validated. The work performed will help improve wind farm modeling by analyzing data, applying models, designing and performing experiments to acquire additional wind farm data, and develop better models.

17 WIND ENERGY↗

DOE OSTI2026

Impact of atmospheric turbulence on performance and loads of wind turbines: knowledge gaps and research challenges

Wind energy harvesting from the atmosphere takes place in the atmospheric boundary layer. The boundary layer shear and buoyancy create three-dimensional turbulent eddies spanning a range of scales that form a continuous forward cascade of kinetic energy to the smallest scales of motion where energy is dissipated. Large-scale atmospheric circulations modulate the boundary layer turbulence, characterized by coherence and intermittency. As wind turbines grow in size and the integrated control of both turbines and wind farms spans greater distances, the relationship between the scales of atmospheric turbulence and the design and operation of wind energy facilities has entered new territory. The boundary layer turbulence impacts both wind turbine power production and turbine loads. Optimizing wind turbine and wind farm performance requires an understanding of how turbulence affects both wind turbine efficiency and reliability. While the characteristics of atmospheric boundary layer turbulence have been observed and studied in detail over the last few decades, there are still significant gaps in our understanding of the impact of turbulence on wind power resources and wind farm operations. This paper outlines the current state of turbulence research relevant to wind energy applications and points to gaps in our knowledge that need to be addressed to effectively utilize wind resources.

Kosović, Branko [Johns Hopkins Univ., Baltimore, M↗

NASA NTRS2002

Practical Remote Sensing Application for Agriculture

Aerial surveys of plant health in row crops are converted into crucial farm management information plots for each field. These plots are delivered overnight to subscribing farmers. After review, the plots are converted to machinery control discs and installed on farm equipment to manage the appropriate applications of seed, chemicals and water when and where needed. The process is repeated throughout the crop planting, growing and harvesting season. This entire operation has been installed and tested on four Mississippi Delta farms. Its use demonstrated operational cost savings of more than fifty dollars per acre and increased cotton production by ten percent on average.

Source record↗

NASA NTRS2004

Method and apparatus for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data

Remotely sensed spectral image data are used to develop a Vegetation Index file which represents spatial variations of actual crop vigor throughout a field that is under cultivation. The latter information is processed to place it in a format that can be used by farm personnel to correlate and calibrate it with actually observed crop conditions existing at control points within the field. Based on the results, farm personnel formulate a prescription request, which is forwarded via email or FTP to a central processing site, where the prescription is prepared. The latter is returned via email or FTP to on-side farm personnel, who can load it into a controller on a spray rig that directly applies inputs to the field at a spatially variable rate.

Hood, Kenneth Brown↗

NASA NTRS2007

Method and system for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data

Hood, Kenneth Brown↗

NASA NTRS2017

GC13I-0857: Designing a Frost Forecasting Service for Small Scale Tea Farmers in East Africa

Kenya is the third largest tea exporter in the world, producing 10% of the world's black tea. Sixty percent of this production occurs largely by small scale tea holders, with an average farm size of 1.04 acres, and an annual net income of $1,075. According to a recent evaluation, a typical frost event in the tea growing region causes about $200 dollars in losses which can be catastrophic for a small holder farm. A 72-hour frost forecast would provide these small-scale tea farmers with enough notice to reduce losses by approximately 80 USD annually. With this knowledge, SERVIR, a joint NASA-USAID initiative that brings Earth observations for improved decision making in developing countries, sought to design a frost monitoring and forecasting service that would provide farmers with enough lead time to react to and protect against a forecasted frost occurrence on their farm. SERVIR Eastern and Southern Africa, through its implementing partner, the Regional Centre for Mapping of Resources for Development (RCMRD), designed a service that included multiple stakeholder engagement events whereby stakeholders from the tea industry value chain were invited to share their experiences so that the exact needs and flow of information could be identified. This unique event allowed enabled the design of a service that fit the specifications of the stakeholders. The monitoring service component uses the MODIS Land Surface Temperature product to identify frost occurrences in near-real time. The prediction component, currently under testing, uses the 2-m air temperature, relative humidity, and 10-m wind speed from a series of high-resolution Weather Research and Forecasting (WRF) numerical weather prediction model runs over eastern Kenya as inputs into a frost prediction algorithm. Accuracy and sensitivity of the algorithm is being assessed with observations collected from the farmers using a smart phone app developed specifically to report frost occurrences, and from data shared through our partner network developed at the stakeholder engagement meeting. This presentation will illustrate the efficacy of our frost forecasting algorithm, and a way forward for incorporating these forecasts in a meaningful way to the key decision makers - the small-scale farmers of East Africa.

frost↗

DOE OSTI2024

Waste Retrieval Enhancements to Achieve Preliminary Cease Waste Removal in Savannah River Site Liquid Waste Tanks 9H and 10H – 25348

The Liquid Waste (LW) contractor at the Savannah River Site (SRS) is Savannah River Mission Completion (SRMC). The LW Mission is tasked with processing legacy nuclear waste stored in underground waste tanks for final disposition. The Concentration, Storage, and Transfer Facilities (CSTF) contain 43 active waste tanks and 8 closed waste tanks between the two tank farms, F-Area Tank Farm (FTF) and H-Area Tank Farm (HTF). The first steps in the Waste Retrieval and Tank Closure (WRTC) process are the waste removal campaigns, consisting of either salt dissolution or sludge mobilization. Two tanks that are rapidly approaching the final closure determination and have demonstrated considerable success with salt dissolution are Tanks 9 and 10. The closure of these tanks is a high priority for the LW Mission due to the greater environmental risk they pose since both tanks reside within the water table and contain active leak sites from the primary tank to the annulus space. Tanks 9 and 10 have each recently completed their respective salt dissolution campaigns and achieved the Preliminary Cease Waste Removal (PCWR) milestone.

Stetson, Jacqueline G.↗

DOE OSTI2026

Tank 11H Low Temperature Aluminum Dissolution and Inhalation Dose Potential Analyses at Savannah River Site – 26018

Currently, there is approximately 34 million gallons of high-level radioactive tank waste in the Tank Farm at the Savannah River Site (SRS). The ultimate goal of operations at the Tank Farm is to remove the high level waste (HLW) from the tanks followed by stabilization of the waste through vitrification of the HLW into glass or grouting the decontaminated waste into saltstone. After bulk removal of the HLW consisting of sludge, saltcake, and supernatant, further efforts are made to reduce the residual waste present in the tank in order to declare preliminary cease waste removal (PCWR) signifying completion of HLW removal. These reduction efforts can include tank washing to remove soluble salts and radioisotopes and dissolution of solids including aluminum. Aluminum in the form of gibbsite and boehmite is relatively insoluble in water. Through addition of aqueous sodium hydroxide, the aluminum can be dissolved at mild temperatures. In order for the waste tank to meet closure mode requirements of the Concentration, Storage, and Transfer Facilities (CSTF), which includes the Tank Farm, Documented Safety Analysis (DSA), a component of the safety basis, the inhalation dose potential (IDP) and the radiolytic hydrogen generation rate of the stored waste must be demonstrated to be lower than their respective designated limits. These parameters are calculated from measured radiochemical analyses of isotopes that emit a high amount of radioactivity including Cs-137, Sr-90, Pu-238, Pu-239, Pu-240, Pu-241, Am-241, and Cm-244. Following the low temperature aluminum dissolution (LTAD) process, Tank 11H slurry samples were pulled from the tank and sent to Savannah River National Laboratory (SRNL) to measure the extent of aluminum dissolution, hydroxide concentration, densities of slurry and supernatant, weight percent solids analyses, and radionuclide activities. The analyses of the composite sample found that approximately 90% of the total aluminum in the slurry was dissolved, indicating successful reduction of the insoluble aluminum in the waste tank. Additionally, the weight percent insoluble solids (slurry basis) measurement of the composite sample was found to be approximately 1%, demonstrating that minimal solids still remain in the tank. Finally, the radiochemical analyses of the composite sample determined that the waste contents of the tank met the IDP and radiolytic hydrogen generation rate requirements of the CSTF DSA. These measurements have shown that the LTAD process in Tank 11H was successful in waste reduction efforts and a positive step towards declaring PCWR and tank closure at SRS.

Dekarske, John [Savannah River National Laboratory↗

DOE OSTI2024

Agrivoltaic Decision Tools for Perennial and Field Crop Farmers

This article describes a series of spreadsheet-based tools to help farmers estimate costs, revenues, and yields from agricultural production under different configurations of agrivoltaic installations for field and perennial crops. Crop-specific log books allow farmers to project changes in activity-level costs from the field due to agrivoltaic installations. The whole-farm tool helps farmers aggregate activity-level net returns up to the farm level to calculate projections of trade-offs between crop production with or without agrivoltaic installations. We present tools for lettuce and cranberries, but the tools are comprehensive and inclusive and so can be modified for other perennial and field crops.

14 SOLAR ENERGY↗

DOE OSTI2025

Rethinking agrivoltaic incentive programs: A science-based approach to encourage practical design solutions

Agrivoltaic systems are promising solutions to address global food and energy challenges by combining agriculture and solar photovoltaics. However, the lack of appropriate regulations to define and guide their implementation constrains the growth of agrivoltaic systems in the U.S. This study uses a shading and radiation tool to evaluate an existing agrivoltaic incentive program that defines agrivoltaic designs based on shading reduction limits and panel height requirements. Our analysis indicates that structuring policy requirements around shading, and not light availability, may lead to an underestimation of crop suitability by neglecting diffuse radiation. Furthermore, we show that agrivoltaic systems can avoid increasing panel height if policy acknowledges use-case scenarios where farming only occurs between rows. In light of these insights, this study proposes two key policy recommendations: (1) benchmark crop suitability based on daily light integral (DLI) requirements for a shade-intolerant crop selected to represent a prevalent crop in the region, and (2) include an incentive scenario where agriculture is only required between rows. Furthermore, these two recommendations can potentially incentivize designs that are practical and closer in cost to conventional solar farms, thereby accelerating the adoption of cost-effective agrivoltaic systems.

14 SOLAR ENERGY↗

DOE OSTI2024

Software-Defined Virtual Synchronous Condenser

Synchronous condensers (SCs) play important roles in integrating wind energy into relatively weak power grids. However, the design of SCs usually depends on specific application requirements and may not be adaptive enough to the frequently-changing grid conditions caused by the transition from conventional to renewable power generation. This paper devises a software-defined virtual synchronous condenser (SDViSC) method to address the challenges. Our contributions are fourfold: 1) design of a virtual synchronous condenser (ViSC) to enable full converter wind turbines to provide built-in SC functionalities; 2) engineering SDViSCs to transfer hardware-based ViSC controllers into software services, where a Tustin transformation-based software-defined control algorithm guarantees accurate tracking of fast dynamics under limited communication bandwidth; 3) a software-defined networking-enhanced SDViSC communication scheme to allow enhanced communication reliability and reduced communication bandwidth occupation; and 4) Prototype of SDViSC on our real-time, cyber-in-the-loop digital twin of large-wind-farm in an RTDS environment. Furthermore, extensive test results validate the excellent performance of SDViSC to support reliable and resilient operations of wind farms under various physical and cyber conditions.

17 WIND ENERGY↗

DOE OSTI2024

The IEA Wind Task 49 Reference Floating Wind Array Design Basis

International Energy Agency Wind Technology Collaboration Programme (IEA Wind) Task 49 on Integrated Design of Floating Wind Arrays is an international collaboration aiming to advance the development of large-scale floating wind farms by providing open-access resources to the research and development and planning communities. The work of Task 49 focuses on array-level challenges related to the colocation of many floating wind turbines; their layouts, mooring systems, and cabling systems; failure risks; logistical considerations; marine spatial planning needs; and future research needs and innovation directions. This report provides a general design basis for the development of reference floating wind farm designs. These reference array designs will extend the scope of existing reference floating wind turbine designs to facilitate research on array-level floating wind technology challenges and innovations. The design basis promotes coordination and consistency in developing the reference array designs.

17 WIND ENERGY↗

DOE OSTI2026

Benchmarking of three DWM-based wake models at below-rated wind speeds

Wind turbine wake models are essential tools for predicting power losses and structural loads in wind farms. Among these, the dynamic wake meandering (DWM) model, included as a recommended approach in the International Electrotechnical Commission design standard, is a widely used engineering-fidelity method that balances accuracy and computational cost. This study compares the performance of three DWM-based wake model implementations (from the Technical University of Denmark, the National Renewable Energy Laboratory, and the Institute for Energy Technology) under below-rated wind speed conditions. Model predictions of wake flow, power output, and structural loads for a four-turbine row are evaluated across different ambient turbulence levels and wind-direction misalignments and compared against high-fidelity large-eddy simulation results. All three models captured the overall wake evolution and mean turbine performance with reasonable accuracy; their predicted time-averaged thrust and power were typically within 5 %–10 % of the large-eddy simulation benchmark. However, notable differences emerged in wake structure and unsteady load predictions, with discrepancies increasing for turbines further downstream. These differences highlight the importance of modelling choices such as wake summation and turbulence treatment, which strongly influence power-deficit and fatigue-load predictions. Comparison with large-eddy simulations reveals each approach's strengths and weaknesses, indicating where improvements are needed. Overall, the findings point to specific refinements for DWM models to improve their fidelity, ultimately enabling more robust wake predictions for wind farm design and operation.

17 WIND ENERGY↗