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DOE OSTI2023

A use-case-driven approach for demonstrating the added value of digitalisation in wind energy

Digitalisation is one of the key drivers for reducing the costs and risks of wind energy. When considering whether to embark on a digitalisation initiative, two key questions arise. The first is what business or operational opportunities might feasibly be addressed and the second is which of the many potential aspects of digitalisation are relevant to those opportunities. In this work, we show how these questions can be answered with a use-case-driven approach, based around a survey aiming to collect and collate the main "pain points" (or everyday challenges) of people in the wind energy sector. Although the relatively low number of participants of the survey (46) means that the results should only be used indicatively, it is still possible to make some general recommendations for priorities for digitalisation efforts in the wind energy sector. Firstly, digitalisation efforts should focus both on supporting people carrying out cross-lifecycle tasks, in particular sharing data, managing data, undertaking general data analyses and accessing data. Tools to do this should deal with varying data formats and naming conventions, make metadata more accessible, define data and metadata standards, make more data publicly available and improve the quality of data. Secondly, efforts should also focus on supporting people in the wind farm operational phase, in particular with failure detection, fault diagnosis, failure rate modelling and predictive maintenance. Solutions to do this should focus on accessible and validated tools for fault detection, cloud or other data pipeline solutions for SCADA data and tools for exhaustive data documentation. Finally, digitalisation efforts should focus on better communicating and helping people become aware of existing solutions and tools, as well as on helping people to exert a stronger influence on possible solutions.

17 WIND ENERGY↗

DOE OSTI2024

Development and Verification of an Improved Wake-Added Turbulence Model in FAST.Farm

We introduce a generalized wake-added turbulence (WAT) model in the multiphysics, multiturbine simulation tool FAST.Farm. The WAT model introduces additional small-scale turbulence that represents the breakdown of vortical structures and shear layers in the wake. The article describes the development, implementation, calibration, and verification of the model. The novelties of the model include support for wake asymmetry, buildup of WAT across the wind farm, and secondary effects of wake-induced turbulence (e.g., wake meandering) driven by smaller-scale turbulence structures that arise from wake breakdown. Large-eddy simulations were run to support the calibration of the WAT parameters and verification of the model. Previous studies hypothesized that the lack of WAT modeling was the source of underprediction of fatigue loads, in particular for cases at low turbulence intensities and/or stable atmospheric boundary layers. This study confirms that the newly implemented WAT model enhances the loads predictions in these cases.

17 WIND ENERGY↗

DOE OSTI2020

Operation of the ATLAS trigger system in Run 2

The ATLAS experiment at the Large Hadron Collider employs a two-level trigger system to record data at an average rate of 1 kHz from physics collisions, starting from an initial bunch crossing rate of 40 MHz. During the LHC Run 2 (2015–2018), the ATLAS trigger system operated successfully with excellent performance and flexibility by adapting to the various run conditions encountered and has been vital for the ATLAS Run-2 physics programme. For proton-proton running, approximately 1500 individual event selections were included in a trigger menu which specified the physics signatures and selection algorithms used for the data-taking, and the allocated event rate and bandwidth. The trigger menu must reflect the physics goals for a given data collection period, taking into account the instantaneous luminosity of the LHC and limitations from the ATLAS detector readout, online processing farm, and offline storage. This document discusses the operation of the ATLAS trigger system during the nominal proton-proton data collection in Run 2 with examples of special data-taking runs. Aspects of software validation, evolution of the trigger selection algorithms during Run 2, monitoring of the trigger system and data quality as well as trigger configuration are presented.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Machine learning on FPGA for event selection

Real-time data processing is a frontier field in experimental particle physics. The application of FPGAs at the trigger level is used by many current and planned experiments (CMS, LHCb, Belle2, PANDA). Usually they use conventional processing algorithms. LHCb has implemented Machine Learning (ML) elements for real-time data processing with a triggered readout system that runs most of the ML algorithms on a computer farm. The work described in this article aims to test the ML-FPGA algorithms for streaming data acquisition. Herein, there are many experiments working in this area and they have a lot in common, but there are many specific solutions for detector and accelerator parameters that are worth exploring further. This report describes the purpose of the work and progress in evaluating the ML-FPGA application.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Control of Floating Offshore Wind Energy Systems: An Introduction to the Special Issue

As the global demand for renewable energy sources intensifies amid the urgent fight against climate change [1] , offshore wind energy has emerged as a promising and crucial component of the sustainable energy portfolio. Fixed-bottom offshore wind farms have already demonstrated their potential; however, they are limited to relatively shallow waters, typically no deeper than 60 m.

climate change↗

DOE OSTI2024

A Tutorial on the Control of Floating Offshore Wind Turbines: Stability Challenges and Opportunities for Power Capture

Climate change is a serious threat facing humanity. The United States (U.S.) and many other countries are increasing the amount of electrical power generated from renewable energy sources in an effort to combat climate change and ensure energy independence. The U.S. has set goals to achieve a 100% decarbonized electric grid by 2035 and a net-zero emissions economy by no later than 2050. Renewable energy currently accounts for about 20% of the U.S. power grid. According to the U.S. Department of Energy and the National Renewable Energy Laboratory (NREL), in the U.S. in 2021, wind and solar photovoltaic generation supplied 9.1% and 4% of total electricity generation, respectively, and the latest publicly available data show that hydropower represented 6.6% of all electricity generated in the U.S. in 2019. As wind farms have been built in many of the best wind resource areas on land, the U.S. and many other countries are turning to offshore wind for further growth of wind power capacity. Further, the U.S. has committed to deploy 30 GW of offshore wind by 2030, a significant increase from the 0.04 GW of installed offshore wind in the country as of the end of 2023. Many other countries have also established ambitious goals or plans to increase the amount of installed offshore wind power.

17 WIND ENERGY↗

DOE OSTI2026

Closed-Loop Wind Turbine Controllers for Active Wake Mixing Strategies

Wind turbine active wake mixing (AWM) is an exciting new field of research where dynamic actuation, usually on the blade pitch angles, is used to increase wind farm-wide power production. From a controls perspective, the current state-of-the-art AWM strategies are very simple: a dynamic, usually periodic, reference signal is prescribed to actuators in an open-loop (OL) fashion. The actuation is then presumed to have a certain desired effect on the system, i.e., the wind turbine and the flow it affects. However, this system is highly nonlinear and experiences disturbances in the form of wind variations that are not known a priori. As a result, the OL approach might not yield optimal results. In this article, a novel approach is presented, which closes the loop on AWM controllers. A feedback loop is implemented, which uses measurements of the individual blade bending moments that are widely available on modern wind turbines to determine the individual blade pitch angles. A proof of concept of this implementation is presented in this article, and a thorough comparison with the OL method is executed using high-fidelity flow simulations. These simulations show that the novel closed-loop controller does not substantially increase wake mixing but achieves similar performance as the OL controller while reducing fatigue loads on the controlled turbine.

17 WIND ENERGY↗

DOE OSTI2020

Applying Constrained Bayesian Optimization to the Design of Critical Experiments

Often when planning a criticality experiment, many design configurations are iteratively investigated with a Monte Carlo transport code. The goal is that the experiment will be optimal with respect to some variable, like the fraction of fissions occurring at a certain energy range, while simultaneously being critical. Unfortunately, the Monte Carlo transport simulations are expensive, which can ultimately limit the number of configurations that can be explored. In this work, we present how Gaussian processes (GPs) can be used as a reduced-order model in a constrained Bayesian optimization (CBO) algorithm to design a criticality experiment. The GPs replace the Monte Carlo transport simulations that explore the design space. The CBO algorithm efficiently identifies new points in the design space to run the Monte Carlo transport code while respecting the criticality constraint. It does so in a manner that both improves the accuracy of the GP and finds the approximate global optimum. We demonstrate the performance of CBO with the design of a Thermal Epithermal eXperiment (TEX) for the criticality safety validation of nuclear waste models of the Hanford Tank Farm.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Effect of Nuclear Data Covariances on Integral Experiment Design with Sensitivity and Uncertainty Analysis

Washington River Protection Solutions (WRPS) uses MCNP6.2 and the Whisper code for criticality safety analyses of the Hanford Tank Farm. Together the codes derive baseline upper subcritical limits (USLs) for the waste models using experimental benchmarks. Whisper returns higher USLs, i.e. , has less of a conservative penalty, when the neutronic similarity of the experimental benchmarks to the application is high. Unfortunately, few critical benchmarks have high similarity to the Hanford tanks. The waste in the tanks is highly dilute in plutonium and contains large masses of weakly neutron-absorbing elements like iron and manganese. Experimental benchmarks typically have low sensitivity to these absorbers because they are present as structural materials. Lacking similar benchmarks, new Thermal Epithermal eXperiment (TEX) configurations with high Pu content and interstitial iron absorbers have been designed for the criticality safety validation. The features of the design have been iterated upon to maximize the similarity between the experiment and different Hanford waste models. The similarity is quantified with sensitivity analysis and uncertainty quantification using the representativity coefficient, or c k . The representativity calculation requires nuclear data covariances, which may differ between nuclear data libraries and between library versions. Because of these variations, the optimal design may depend on the nuclear data covariances library. A scenario can be envisioned where an experiment is designed, and c k is maximized, with one set of covariance data. However, when the covariance data is changed, say from ENDF/B-VII.1 to ENDF/B-VIII.0, and the benchmark is used in a criticality safety evaluation, the experiment becomes suboptimal with respect to c k . In this paper, we present how the optimal design of the new TEX experiments varied depending on the nuclear data covariances used to calculate c k . We compare ENDF/B-VII.1 and ENDF/B-VIII.0, as if the library had been updated since the design of the experiment. Additionally, we use JEFF3.3 to simulate if the covariance data of a different library had been used. The results show that the covariances do have an important effect on the designs, less so for thermal systems (where the data are more consistent between evaluations) and more so for epithermal systems where more differences exist.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Impact of Permanganate Oxidation of Glycolate on Corrosion of the Defense Waste Processing Facility (DWPF) Recycle Collection Tank (RCT), Transfer-line and Waste Tank Materials of Construction (MoC)

Savannah River Remediation (SRR) is evaluating the use of glycolic acid to replace formic acid as an alternate reductant for the Defense Waste Processing Facility (DWPF) at Savannah River Site (SRS). The replacement is aimed at reducing facility hazards, improving pH stability and rheological control, and lowering off gas production. Glycolate, which is the product that may remain, can also be carried downstream to High-Level Waste and Low-Level Waste facilities. Complete oxidation of glycolate and other organic species from the Sludge Receipt and Adjustment Tank (SRAT) may be necessary to minimize thermolytic hydrogen generation that can cause flammability issues. The glycolate oxidation may be performed in the Recycle Collection Tank (RCT). The RCT heel would be adjusted with sodium hydroxide to maintain the solution caustic and sodium nitrite as corrosion inhibitor prior to the addition of condensate that can be from the contents of the Slurry Mix Evaporator Condensate Tank (SMECT) or Offgas Condensate Tank (OGCT). The RCT tank collects the waste to be transferred via the Low Point Pump Pit – Recycle Pump Tank (LPPP-RPT) through a jacketed transfer-line to the Tank Farm facility. Scoping studies were performed to evaluate an oxidizing agent and sodium permanganate was selected as the best option for glycolate destruction. Testing was recommended to determine the impact on the Materials of Construction (MoC) due to the addition of sodium permanganate. The targeted concentration of sodium permanganate used equated to a 7:1 molar permanganate to glycolate ratio (nominally 0.002 M permanganate). However, to conservatively maximize the permanganate corrosivity, in some cases no glycolate was added.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Satellite-Based Solar Forecasting Including Maintenance of Computer and Storage Equipment at CSU/CIRA (CRADA Final Report)

The Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University (CSU) proposes to continue its research partnership with the NREL in Golden, CO. The partnership resonates with the goals outlined in a Memorandum of Understanding between the Department of Energy and the Department of Commerce (with the National Oceanic and Atmospheric Administration (NOAA)) signed in 2011. This CRADA will sustain the research partnership and provide an avenue and resources for ongoing collaborations, including the maintenance of NREL-furnished computer and storage equipment at CSU/CIRA. There is no formal exchange of funds in this CRADA; support above and beyond the in-kind items outlined in this document will come on a best-effort basis and/or in association with formal sponsored-research enabled collaborations. The research conducted under this CRADA continues to work toward enabling and improving short-term solar energy forecasting as developed under previous CIRA/CSU and NREL collaborations, with specific focus on point-based (e.g., solar farm) forecasting on the 1-3 hour timeframe. Under the best-effort actions during the CRADA period, technical maintenance of CIRA's existing satellite-based solar forecasting algorithm ("CIRACast"; Miller et al., 2017) was continued to maintain operability with evolving datasets. These efforts benefit the public by maintaining national capability for point solar forecasting using geostationary observation platforms, and laying the groundwork for future technical improvements as opportunities arise.

14 SOLAR ENERGY↗

DOE OSTI2022

Blue Rock CropSpanPV - Low Cost Racking for Agricultural Solar Photovoltaics

In this work, a total of four solar panel layouts, applied to Agrivoltaics, are investigated. This study presents two hypotheses: 1. Prefabrication - Lower total cost can be achieved by constructing a pre-assembled, pre-wired solar array in a factory, with automation, then rapidly deploying it in the field. 2. Tension Structures - Using tension structures in a way to suspend an overhead solar array also reduces costs when compared to conventional support methods. Designs are presented for frames to hold the panels. Configurations are advanced to connect the frames into arrays. Supports and foundations to hold the arrays in the desired layout are calculated, selected and presented. Cost models are prepared for the four layouts, which include definition of the business enterprise, the manufacturing operation, and the required facility for production at scale. Cost models include, detail material and task/labor take-offs for both manufacturing and installation. Comparisons with conventional system adapted to Agrivoltaics reveal that the two hypotheses do not hold true. A prefabricated array requires additional material that is not needed in the base system and the cost of this additional material is not outweighed by the cost savings of reduced field installation. The cost of wire rope for a tension structure does result in an economy of material, however, the cost of end connections and tensioning devices adds significantly to the cost of the overall tension structure. Foundation loads with tension structures, especially the large wind uplift seen with a fixed tilt solar array, impose significant constraints and high costs. The following conclusions are recommended for further consideration: 1. Best Case Agrivoltaic Configuration - The best value/lowest cost configuration for agrivoltaics is the installation of solar panels mounted on a single axis tracker in either a 2-in-portrait or 2-in landscape arrangement. This is useful for grazing lands and for staple crops which require high light levels. These applications represent the vast majority of the potential agrivoltaic market. Important elements in this configuration are the specific geometric layout coordinated with the various field operations and a control system linked between the farm equipment and single axis tracker. The control system is to monitor location and orientation, then actively tilt the solar panels or brake the field equipment to provide clearance and avoid collisions. 2. Long Span Applications - The use of tension structures for an overhead fixed tilt array is beneficial where long spans are a necessity, especially where the base support in the project location has consolidated rock near the surface or some other solid structure. One application is spanning wide irrigation canals. Another may be as an installation at the top deck of parking structures. 3. Direct Ground Mount Configuration – Having skids at the base of a pre-fabricated array that extend when the array is deployed, could be a successful design. This could be a useful strategy for dense, flat, ground-mount configurations like that employed by a couple of successful commercial operations (5G Maverick and Erthos). Arrays would be orientated north and south, deployed very low on prepared grade. Arrays would be aligned closely next to each other and anchored with small ground screws or simply with ballast. This same product arrangement could be very useful for rapid deployment and set-up of solar arrays for temporary deployments, disaster response and the military operations

14 SOLAR ENERGY↗

DOE OSTI2022

Characterization of Infrequent Samples from the Concentration, Storage, and Transfer Facility: H-Area Diversion Box 7 (HDB-7) Sump Sample: January 2022 Samples

Savannah River Remediation Engineering (SRR-E) requested that the Savannah River National Laboratory (SRNL) analyze the Concentration, Storage, and Transfer Facility (CSTF) samples from the following Tank Farm areas: the sump encasement, catch tank, drain cell, and waste tank annulus. In general, these CSTF samples will be analyzed on an infrequent basis and analyses will include detection for total beta/gamma, total alpha activities, density, free hydroxide, and pH measurements. This report presents characterization results for the H-Area diversion box 7 sump (HDB-7) 07 January 2022 and 18 January 2022 samples. The samples were clear and colorless and free from any solids. The results are measurements for total gamma, total alpha, total beta, density, free hydroxide, and pH.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Characterization of Infrequent Samples from the Concentration, Storage, and Transfer Facility: H-Area Diversion Box 1 (HDB-1) Sump Sample: January 25, 2022 Sample

Savannah River Remediation Engineering (SRR-E) requested that the Savannah River National Laboratory (SRNL) analyze the Concentration, Storage, and Transfer Facility (CSTF) samples from the following Tank Farm areas: the sump encasement, catch tank, drain cell, and waste tank annulus. In general, these CSTF samples will be analyzed on an infrequent basis and analyses will include detection for total beta/gamma, total alpha activities, density, free hydroxide, and pH measurements. This report presents characterization results for the H-Area diversion box 1 sump (HDB-1) January 2022 sample. The sample was slightly brown with a small amount of suspended fine particulates visually estimated to be less than 1% by volume. The results are measurements for total gamma, total alpha, total beta, density, free hydroxide, and pH.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Characterization of Infrequent Samples from the Concentration, Storage, and Transfer Facility: Leak Detection Box (LDB) Drain Cell Sample: February 09, 2022 Sample

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Characterization of Infrequent Samples from the Concentration, Storage, and Transfer Facility: Leak Detection Box (LDB) Drain Cell Sample: August 04, 2022 Sample

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Characterization of Infrequent Samples from The Concentration, Storage, And Transfer Facility: Leak Detection Box (LDB) Drain Cell Sample: February 26, 2023, Sample

Savannah River Mission Completion Engineering (SRMC-E) requested that the Savannah River National Laboratory (SRNL) analyze the Concentration, Storage, and Transfer Facility (CSTF) samples from the following Tank Farm areas: the sump encasement, catch tank, drain cell, and waste tank annulus. In general, these CSTF samples will be analyzed on an infrequent basis and analyses will include detection for total beta/gamma activities, total alpha activity, free hydroxide, and pH measurements. This report presents characterization results for the leak detection box (LDB) February 26, 2023, drain cell sample. The sample was clear and colorless with no visible particulates. The results are measurements for total gamma, total alpha, total beta, free hydroxide, pH, and density. These analyses were performed in triplicate. A summary of the average analytical results for the LDB sample includes the following. The directly measured pH for the LDB February 26, 2023 "as-received" drain cell sample range was 7.12-7.16, and the free hydroxide concentration was <0.02 M. The density of the "as-received" drain cell sample determined at 25 °C was 1.02±0.00 g/mL. The total alpha activity for the LDB February 26, 2023, sample is reported as a less than value (Upper Limit) because of possible spectral interferences. Thus, the total alpha activity averaged <3.52E+02 dpm/mL. This value is less than 4.83E+03 dpm/mL, which is the procedural limit for non-waste determination. The total beta activity in the LDB February 26, 2023, drain cell sample is above the instrument detection limits and average 9.76E+03±5.94E+02 dpm/mL. The total beta activity in the LDB February 26, 2023, drain cell sample is above he instrument detection limits and averaged 7.76E+03±5.94E+02 dpm/mL. The average measured cesium-137 activity (dominant beta emitter) in the LDB February 26, 2023, drain cell sample is 7.76E+03±2.35E+02 dpm/mL. The corresponding Ba-137m (dominant gamma emitter) activity, calculated as 94.6% of the Cs-137 values, is 7.34E+03±2.23E+02 dpm/mL. The total empirical activity of the beta and gamma emitting (represented by the sum of total beta and Ba-137m activities) averaged 1.71E+04±8.18E+02 dpm/mL. This value is less than 8.69E+05 dpm/mL, which is the procedural limit for non-waste determination.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Characterization of Infrequent Samples from the Concentration, Storage, and Transfer Facility: Leak Detection Box (LDB) Drain Cell Sample: May 15, 2023, Sample

Savannah River Mission Completion Engineering (SRMC-E) requested that the Savannah River National Laboratory (SRNL) analyze the Concentration, Storage, and Transfer Facility (CSTF) samples from the following Tank Farm areas: the sump encasement, catch tank, drain cell, and waste tank annulus. In general, these CSTF samples will be analyzed on an infrequent basis and analyses will include detection for total beta/gamma activities, total alpha activity, free hydroxide, and pH measurement. SRMC-E corresponded with SRNL to obtain the final results through memo SRNL-L3120-2023-00013. This report presents characterization from results for the leak detection box (LDB) May 15, 2023, drain cell sample. The sample was clear and colorless with no visible particulates. The results are measurements for total gamma, total alpha, total beta, free hydroxide, pH, and density. These analyses were performed in triplicate. A summary of the average analytical results for the LDB sample includes the following. The measured pH for the LDB May 15, 2023 "as-received" drain cell sample range was 6.60-6.89, and the free hydroxide concentration as expected, based upon the pH, was <0.02 M. The average measured density of the "as-received" drain cell sample determined at 22 °C was 1.022±0.001 g/mL. the average measured total alpha activity for the LDB May 15, 2023, sample was 3.04E+02±1.13E+01. This value is less than 4.83E+03 dpm/mL, which is the procedural limit for non-waste determination. The total empirical activity of the beta and gamma emitting (represented by by the sum of total beta and B-137 m activities) averaged to 1.83+04±1.07E+03 dpm/mL. This value is less than 8.69E+05 dpm/mL, which is the procedural limit for non-waste determination.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗