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At least 91 records · Page 5

Fire Protection Jacket

NERAC, Inc., Tolland, CT, aided Paul Monroe Engineering, Orange, CA, in the development of their PC1200 Series Fire Protection Jacket that protects the oil conduit system on an offshore drilling platform from the intense hydrocarbon fires that cause buckling and could cause structural failure of the platform. The flame-proof jacketing, which can withstand temperatures of 2000 degrees Fahrenheit for four hours or more, was developed from a combination of ceramic cloth (similar to the ceramic in Space Shuttle tiles), and laminates used in space suits.

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1:70-Scale Model Testing of the Reference OpenSource Controller (ROSCO) on the IEA-Wind 15MW Reference Wind Turbine Including Floating Feedback: Preprint

This paper presents results from the Floating Offshore-wind Controls Advanced Laboratory (FOCAL) Experimental campaign performed at the University of Maine's (UMaine's) Harold Alfond Wind/Wave Ocean Engineering Laboratory (W2). The project involves four Froude-scaled test campaigns considering the International Energy Agency (IEA) Wind 15MW Reference Wind Turbine deployed on the VolturnUS-S semi-submersible platform with tuned-mass damper (TMD) elements in the hull. The turbine employs real-time rotor torque and blade pitch control through the Reference OpenSource Controller (ROSCO), including the additional control strategies of ROSCO's thrust peak shaving and a floating feedback control loop. Results with the floating feedback control are considered in this paper and show a significant reduction in platform pitch motion and loads around the platform pitch natural frequency with minimal negative impact of rotor power quality.

controls↗

On Building Predictive Digital Twin Incorporating Wave Predicting Capabilities: Case Study on UMaine Experimental Campaign - FOCAL

The response of floating wind turbines (FWT) are susceptible to stochastic wave variations. For the optimal operation of FWT, a comprehensive understanding of the phaseresolved wave dynamics and the consequential system response is crucial for real-time monitoring and control. A multi-variate, multi-step, long short term memory (MLSTM), a type of recurrent neural network (RNN) is used to capture complex system dynamics for real-time application. Results indicate that the integration of a wave prediction-reconstruction (WRP) model substantially enhances prediction accuracy by 50% on average relative to the baseline model. The improvement is consistent across various wave extremity and prediction horizons, thereby significantly broadening the scope for timely and precise predictive capabilities.

17 WIND ENERGY↗

A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Final Technical Report)

Collision of birds and bats with wind turbines is a conservation concern for both land-based and offshore wind projects. The fatality rates of birds and bats at land-based turbines are well documented. The measurement strategies on land focus on finding carcasses following collision, estimating the number of carcasses missed through searcher efficiency, carcass persistence trials and carcass fall distributions, and modeling statistically robust fatality rates. Few technologies have been developed to monitor offshore bird and bat collisions, and many that have been developed focused on detecting collisions with large birds. The few studies that have attempted to document collisions at offshore turbines do not account for smaller bodied animals or for collisions that might be missed, which prevents the calculation of statistically robust fatality rates. The overall goal of this report, A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Project), was to develop an effective multi-sensor system for quantifying bird and bat collision rates, specifically for offshore wind facilities. The Project goal and resulting automated collision detection system was achieved through two major technological advancements: 1) refining The Netherlands Organisation for Applied Scientific Research’s (TNO’s) existing WT-Bird® vibration sensing system, that had successfully detected large bird collisions during daytime, to allow for improved detection of smaller birds and bats during both daytime and nighttime hours and 2) improving image processing systems and developing and integrating machine learning algorithms to automatically detect and classify small and large bird and bat collisions with offshore turbines. This final technical report (FTR) summarizes Methods , Results , Conclusions , and Lessons Learned during each of the five Tasks identified for this research and development effort. This FTR includes summaries of the following: Task 1. Initial Engineering Tests to Improve WT-Bird® Task 2. Installation of WT‐Bird® on a Utility-scale Turbine at the National Wind Technology Center – National Renewable Energy Laboratory Task 3. Field Tests and Refinement of the Object Detection System Task 4. Validation of WT-Bird® on a Land-based Turbine Task 5. Preparation for the Implementation of WT-Bird® on an Offshore Turbine. This research and development effort documented successful improvement of the WT Bird® collision detection system to detect small birds and bats, and WT-Bird® is the first collision detection system to validate results compared to land-based post-construction monitoring. The collision trials provide estimates of missed targets that can be used to estimate fatality rates, a significant improvement relative to other offshore collision monitoring systems. Advances were made in developing an edge-processing solution to reduce data storage requirements, which is important if the system is deployed for long periods of time at offshore turbines. The improved WT-Bird® system also provides an important option for wind operators on land or offshore who need to document specific details about when collisions occur, particularly efforts to further research on bat impact minimization, or when standard fatality searches are impractical (e.g. offshore) or inadequate (e.g. challenging locations on land).

17 WIND ENERGY↗

Uncertainty-Guided Prediction Horizon of Phase-Resolved Ocean Wave Forecasting Under Data Sparsity: Experimental and Numerical Evaluation

Accurate short-term wave forecasting is critical for the safe and efficient operation of marine structures that rely on real-time, phase-resolved ocean wave information for control and monitoring purposes (e.g., digital twins). These systems often depend on environmental sensors (e.g., waverider buoys, wave-sensing LIDAR). Challenges arise when upstream sensor data are missing, sparse, or phase-shifted due to drift. This study investigates the performance of two machine learning models, time-series dense encoder (TiDE) and long short-term memory (LSTM), for forecasting phase-resolved ocean surface elevations under varying degrees of data degradation. We introduce the τ-trimming algorithm, which adapts the prediction horizon based on uncertainty thresholds derived from historical forecasts. Numerical wave tank (NWT) and wave basin experiments are used to benchmark model performance under short- and long-term data masking, spatially coarse sensor grids, and upstream phase shifts. Results show under a 50% probability of upstream data loss, the τ-trimmed TiDE model achieves a 46% reduction in error at the most upstream target, compared to 22% for LSTM. Furthermore, phase misalignment in upstream data introduces a near-linear increase in forecast error. Under moderate model settings, a ±3 s misalignment increases the mean absolute error by approximately 0.5 m, while the same error is accumulated at ±4 s using the more conservative approach. These findings inform the design of resilient, uncertainty-aware wave forecasting systems suited for realistic offshore sensing environments.

42 ENGINEERING↗

Centrifuge modeling and numerical analysis on lateral performance of mono-bucket foundation for offshore wind turbines

The lateral loading performance of the mono-bucket foundation for offshore wind turbines is investigated in this study through a series of centrifuge tests and numerical analysis. Six mono-bucket models are considered to assess the influences of aspect ratio under the ultimate condition. The FE model is validated against the centrifuge test results, and the failure mechanism of the foundation is revealed. The parametric study and sensitivity analysis of the soil parameters are performed in the numerical simulations. A modified theoretical calculation method is proposed to estimate the ultimate lateral capacity of the suction bucket foundation by solving the limit equilibrium equations. A correction term is added in the calculation using the “m” method. The position of the rotation center is calculated, demonstrating a better accuracy compared to the previously reported geometric method. The modified calculation method is verified against the field test, the centrifuge test, and the laboratory test. The method is proved to be applicable in estimating the lateral performance of the mono-bucket foundation in a general form. Finally, this study aims to provide well-documented data and design references for practical engineers.

17 WIND ENERGY↗

Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations

Accurately predicting wind farm reliability under complex offshore atmospheric conditions remains a key challenge, particularly during noncanonical meteorological events such as coastal low-level jets (LLJs). LLJs, characterized by strong nonmonotonic vertical shear and directional veer, depart significantly from the simplified inflow assumptions embedded in conventional design standards, low-fidelity engineering models, and microscale large eddy simulations of the atmospheric boundary layer. In this work, we use the virtual wind farm framework—an exascale, graphics processing unit–accelerated large eddy simulation platform coupled with high-fidelity aeroservoelastic turbine models and advanced mesoscale-microscale coupling via the ExaWind software stack—to investigate turbine responses under realistic LLJ forcing. Simulations are performed over the U.S. North Atlantic offshore domain with the use of meteorological inputs from New York State Energy Research and Development Authority buoy data, focusing on a representative LLJ case impacting the International Energy Agency 15 MW reference turbine. Our results show that LLJs can cause up to 50% power deficits in downstream turbine rows and significantly amplify low-speed shaft and tower loads through nonlinear coupling between complex inflow characteristics and turbine structural dynamics. Two primary mechanisms drive these load amplifications: (1) unique LLJ inflow features—including veer and vertical/lateral shear—and (2) the downstream evolution of the flow under stable thermal stratification, which suppresses turbulence mixing and alters wake recovery. These mechanisms produce streamwise variations in turbine loading not captured by standard hub height–based metrics or existing design load case (DLC) definitions. This study highlights the critical role of rotor-scale flow gradients in driving fatigue and system-level aeroelastic responses, challenging current DLC and control strategies. We advocate the integration of full-flow field, environment-aware wind inputs into load modeling and control algorithms. By leveraging exascale computing to resolve mesoscale-microscale coupling, this work lays the groundwork for next-generation offshore wind turbine design and operation in meteorologically complex marine environments.

17 WIND ENERGY↗

Space Derived Waterjets

The American Enterprise, a high speed crewboat and supply vessel for the offshore oil industry, is propelled by three Rocketdyne waterjets. The propulsion units are direct spinoffs from the company's line of turbopumps, which feed propellants to rocket engines on space launch vehicles.

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Parametric Study to Assess Technical Prospect Feasibility for Offshore CO 2 Storage

This report is a white paper on the parametric study to assess technical prospect feasibility for CO 2 storage with and without CO 2 -EOR. The SECARB Offshore GOM team reviewed key parameters that previous modeling experience suggests have the largest impact on CO 2 plume size and CO 2 -EOR performance (SSEB, 2019) These parameters include tectonic impacts (reservoir dip and fault block size), reservoir properties (permeability) and development strategies (well field payout, waterflood, and CO 2 flooding strategies). These parameters are further evaluated in this study in order to identify upper and lower boundary conditions for the parametric values. The boundary conditions are needed to set constraints for key parameters when performing modeling assessments. Understanding the key parametric values for the GOM will facilitate locating successful offshore carbon capture utilization and storage (CCUS) projects in terms of plume size, CO 2 stored and, in the case of EOR, oil recovery. Importantly, this white paper focuses on both technical factors (geologic and engineering), but does not address economic, commercial, or stakeholder considerations. The report is organized into four sections and includes a review of the datasets used to define the parameter ranges, the results of a full-physics reservoir simulation, a summary of a reduced order modeling approach to evaluate the impact of the study parameters, and, finally, a discussion of the work that will occur during the next phase of the project.

02 PETROLEUM↗

FECM/NETL Offshore CO2 Saline Storage Cost Model

The FECM/NETL Offshore CO2 Saline Storage Cost Model (CO2_S_COM_Offshore) estimates costs for a CO2 storage project in an offshore saline formation or reservoir. It is applicable for storage projects located on the Outer Continental Shelf of the Gulf of America. The purpose is to model the costs associated with a project, using simplified geo-engineering equations to calculate reservoir values needed to determine costs (such as CO2 plume area and number of injection wells). To use the model, change any of the inputs, which are always in orange cells, to the values you desire. Although there are numerous values that can be changed, the values expected to be of most interest have input cells on the 'Key_Inputs' sheet. Last update: 5/2/2025; Version 1.1 corrects bug in reservoir thickness calculations.

Carbon storage↗

OC6 Phase III Definition Document

The objective of Phase III of the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) project was to evaluate the accuracy of aerodynamic load predictions by offshore wind modeling tools for a floating offshore wind turbine as it experiences large surge-translational and pitch-rotational motion, as would occur during normal operation. A variety of models were examined in the project, with the goal of performing a three-way validation between engineering-level tools, higher-fidelity tools, and measurement data from two wind tunnel experimental campaigns. This document provides the necessary information to model and simulate the system studied in the OC6 Phase III project. This information is not only useful for project participants, but also future modelers who want to replicate this work for verification and validation purposes.

17 WIND ENERGY↗

Impact of Aerodynamic Modeling Assumptions on Flutter Speeds of Vertical-Axis Wind Turbines

Theodorsen’s unsteady aerodynamic theory has been used extensively in flutter speed prediction of wind turbine blades. In this study, three key assumptions of Theodorsen theory (thin airfoil, flat wake, and small angle of attack) have been revisited, and all three assumptions have been addressed in combination to obtain new lift and moment equations that are subsequently applied in flutter calculations for full-scale vertical-axis wind turbine (VAWT) rotors, not just of an individual airfoil or blade. Furthermore, edgewise aerodynamics terms are added to the lift and moment equations to include their effects on flutter speeds. The newly obtained equations were implemented in the OWENS (Offshore Wind ENergy Simulation) toolkit, which is an FEM (Finite Element Method)-based toolkit for aeroelastic analysis of VAWTs. The effect of modifying each of these assumptions has been studied for the flutter RPM prediction of three primary modes of flutter of VAWTs: propeller, butterfly, and tower modes. For the land-based case, the most change was observed for the flutter RPM of the propeller mode, with a maximum increase of 2.62% for the two-bladed UTD 5 MW VAWT case. For the floating offshore case, the primary flutter modes (tower and platform pitch) were not significantly affected.

Engineering↗

Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads in extreme idling conditions

Abstract. Floating offshore wind turbine (FOWT) systems are subject to complex environmental loads, with significant potential for damage in extreme storm conditions. Design simulations in these conditions are required to assess the survivability of the device with some level of confidence. Aero-hydro-servo-elastic engineering tools can be used with a reasonable balance of accuracy and computational efficiency. The models require many input parameters to describe the air and water conditions, the system properties, and the load calculations. Each of these parameters has some possible range, due to either statistical uncertainty or variations with time. Variation in the input parameters can have important effects on the uncertainty in the resulting loads, but it is not practical to perform detailed assessments of the impact of this uncertainty for every input parameter. This work demonstrates a method to identify the input parameters that have the most impact on the loads to focus further inspection. The process is done specifically for extreme storm load cases defined in the International Electrotechnical Commission design requirements for floating offshore wind turbines. The analysis was performed using the International Energy Agency Wind 15 MW offshore reference wind turbine atop the University of Maine VolturnUS-S reference platform in two US offshore wind regions, the Gulf of Maine and Humboldt Bay. It was found that the direction of incident waves and current, yaw misalignment, and the length of mooring line sections were among the primary sensitivities.

17 WIND ENERGY↗

Addressing deep array effects and impacts to wake steering with the cumulative-curl wake model

Abstract. Wind farm design and analysis heavily rely on computationally efficient engineering models that are evaluated many times to find an optimal solution. A recent article compared the state-of-the-art Gauss-curl hybrid (GCH) model to historical data of three offshore wind farms. Two points of model discrepancy were identified therein: poor wake predictions for turbines experiencing a lot of wakes and wake interactions between two turbines over long distances. The present article addresses those two concerns and presents the cumulative-curl (CC) model. Comparison of the CC model to high-fidelity simulation data and historical data of three offshore wind farms confirms the improved accuracy of the CC model over the GCH model in situations with large wake losses and wake recovery over large inter-turbine distances. Additionally, the CC model performs comparably to the GCH model for single- and fewer-turbine wake interactions, which were already accurately modeled. Lastly, the CC model has been implemented in a vectorized form, greatly reducing the computation time for many wind conditions. The CC model now enables reliable simulation studies for both small and large offshore wind farms at a low computational cost, thereby making it an ideal candidate for wake-steering optimization and layout optimization.

17 WIND ENERGY↗

From Subsurface to System: Offshore CCS Development for the Northeastern U.S. Atlantic Shelf

This study evaluated offshore carbon sequestration potential and infrastructure design along the mid-north Atlantic outer continental shelf, addressing the limited onshore storage options in the northeastern U.S. The objective was to define viable CCS pathways by integrating geological characterization, reservoir modeling, and system-level engineering for decarbonizing regional industrial sources. The work was conducted under US DOE grant FE0032407 for the Regional Initiatives and builds on a previous prospective resources assessment project by Battelle.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Google/Makani Energy Kite Modeling (CRADA CRD-18-00569 Final Report)

In support of Makani’s energy kite development program, Makani engaged with NREL to develop, verify, and document a multiphysics engineering model of a megawatt-scale tethered energy kite (named KiteFAST). After the original development of KiteFAST was completed, Makani further engaged NREL to develop a software enhancement of KiteFAST to enable the dynamics modeling of an energy kite tethered to a floating offshore platform (named KiteFAST-OS). Before this project, the capability to model the aero-hydro-servo-elastic dynamics of an airborne wind energy (AWE) system with electricity generation on the flying device (fly gen) and crosswind flight operation did not exist. Such physics-based modeling capability is needed for loads analysis, structural design, and certification of energy kites. Throughout the project, an exclusive license kept KiteFAST and KiteFAST-OS available only to Makani, NREL, and its counterparts. With the ending of Makani, the KiteFAST and KiteFAST-OS software were merged into a single code base (named KiteFAST), the exclusive license was terminated, and the source code, documentation, and example models were released publicly.

17 WIND ENERGY↗