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DOE OSTI2024

Challenges and Opportunities for Floating Offshore Wind Energy in Ultradeep Waters of the Central Atlantic

This study, funded under an interagency agreement between the U.S. Department of Energy's (DOE) National Renewable Energy Laboratory (NREL) and Bureau of Ocean Energy Management (BOEM), is intended to provide BOEM with key information to inform their decision making about current and future leasing in the Central Atlantic region of the United States. The report will also benefit state governments, developers, research institutions, and the public which are seeking technical and market-based information about the unique aspects of the offshore wind energy development along the outer continental shelf of the Central Atlantic region of the United States. The study provides a broad top-level assessment of the key challenges and opportunities that are unique to offshore wind energy development in the Central Atlantic region. It focuses on BOEM's Central-Atlantic region Call areas. The research is based on the most current technology, deployment, and stakeholder information available to NREL. The topics include assessments of the physical environment, current leasing status and major stakeholder issues, state and federal energy policy, an assessment of future leasing requirements based on state targets, status and limitations of the technology, and supply chain status. The primary intent is to inform the readers about the prospects for deploying offshore wind in the designated deep water Call areas, E and F, identified by BOEM. The report makes recommendations regarding development in these regions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Toward prediction of turbulent atmospheric flows over propagating oceanic waves via machine-learning augmented large-eddy simulation

Wind-wave interactions have important effects on the energy harvesting of offshore wind farms. High-fidelity large-eddy simulation (LES) is a powerful approach for investigating wind-wave interactions in turbulent oceanic environments. Due to the large scale of the flow domain and the high grid resolution required to resolve multi-scale flow motions, however, brute-force LES of wind-wave interactions is computationally very expensive. We propose augmenting brute-force LES via machine-learning data-driven modeling (ML-LES) to dramatically reduce the computational time required to obtain converged turbulence statistics when the brute-force approach is employed. Namely, we employ a convolutional neural network (CNN) autoencoder trained and validated with LES data sets to develop a highly efficient ML-LES approach for computing turbulence statistics from just a few snapshots of instantaneous LES flow fields. Further, our results demonstrate the accuracy and efficiency of ML-LES in predicting the mean velocity, velocity fluctuations, and turbulence kinetic energy in highly stretched computational grid systems required to carry out simulations in real-life oceanic environments.

42 ENGINEERING↗

DOE OSTI2022

A Macroalgal Cultivation Modeling System (MACMODS): Evaluating the Role of Physical-Biological Coupling on Nutrients and Farm Yield

Offshore aquaculture has the potential to expand the macroalgal industry. However, moving into deeper waters requires suspended structures that will present novel farm-environment interactions. Here, we present a computational modeling framework, the Macroalgal Cultivation Modeling System (MACMODS), to explore within-farm modifications to light, seawater flow, and nutrient fields across time and space scales relevant to macroalgae. A regional ocean model informs the site-specific setting, the Santa Barbara Channel in the Southern California Bight. A fine-scale hydrodynamic model predicts modified flows and turbulent mixing within the farm. A spatially resolved macroalgal growth model, parameterized for giant kelp, Macrocystis pyrifera , predicts kelp biomass. Key findings from model integration are that regional ocean conditions set overall farm performance, while fine-scale within-farm circulation and nutrient delivery are important to resolve variation in within-farm macroalgal performance. Therefore, we conclude that models resolving within-farm dynamics can provide benefit to farmers with insight on how farm design and regional ocean conditions interact to influence overall yield. Here, the presence of repeating longlines aligned with the mean current generate flow diversions around the farm as well as attached Langmuir circulations and increased turbulence intensity. These flow-induced phenomena lead to less biomass in the interior portion of the farm relative to the edges. We also find that there is an effluent “footprint” that extends as much as 20 km beyond the farm. In this regard, MACMODS can be used to not only evaluate farm design and cultivation practices that maximize yield but also explore interactions between the farm and ecosystem in order to minimize impacts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Large-Amplitude Motion Platform: A New Ocean Simulator Can Help Technologies Succeed

Offshore renewable energy technologies - like wave energy devices, wind turbines, floating solar panels, and hybrid systems - can help decarbonize our power grids as well as offshore activities like international shipping and seafood farming. But it's not always easy to build technologies hearty enough to operate in a powerful ocean environment. And subjecting promising prototypes to real ocean waves can be an expensive, time-consuming, and risky way to get these technologies ready for the high seas. Now, with the National Renewable Energy Laboratory's (NREL's) new testing platform, called the large-amplitude motion platform (or LAMP for short), our experts can replicate powerful ocean waves in a low-risk laboratory setting. The LAMP, coupled with NREL's diverse array of testing instrumentation, can help technology developers rapidly hone their prototypes before embarking on a potentially costly and time-consuming ocean trial.

marine energy↗

DOE OSTI2021

Toward global comparability in renewable energy procurement

Not Available

Beiter, Philipp↗

NASA NTRS2014

Mars Habitability, Biosignature Preservation, and Mission Support

Our work has elucidated a new analog for the formation of giant polygons on Mars, involving fluid expulsion in a subaqueous environment. That work is based on three-dimensional (3D) seismic data on Earth that illustrate the mud volcanoes and giant polygons that result from sediment compaction in offshore settings. The description of this process has been published in the journal Icarus, where it will be part of a special volume on Martian analogs. These ideas have been carried further to suggest that giant polygons in the Martian lowlands may be the signature of an ancient ocean and, as such, could mark a region of enhanced habitability. A paper describing this hypothesis has been published in the journal Astrobiology.

Oehler, Dorothy Z.↗

NASA NTRS1983

Simulation and analysis of differential global positioning system for civil helicopter operations

A Differential Global Positioning System (DGPS) computer simulation was developed, to provide a versatile tool for assessing DGPS referenced civil helicopter navigation. The civil helicopter community will probably be an early user of the GPS capability because of the unique mission requirements which include offshore exploration and low altitude transport into remote areas not currently served by ground based Navaids. The Monte Carlo simulation provided a sufficiently high fidelity dynamic motion and propagation environment to enable accurate comparisons of alternative differential GPS implementations and navigation filter tradeoffs. The analyst has provided the capability to adjust most aspects of the system, the helicopter flight profile, the receiver Kalman filter, and the signal propagation environment to assess differential GPS performance and parameter sensitivities. Preliminary analysis was conducted to evaluate alternative implementations of the differential navigation algorithm in both the position and measurement domain. Results are presented to show that significant performance gains are achieved when compared with conventional GPS but that differences due to DGPS implementation techniques were small. System performance was relatively insensitive to the update rates of the error correction information.

Denaro, R. P.↗

DOE OSTI2024

Modeling and observations of North Atlantic cyclones: Implications for U.S. Offshore wind energy

To meet the Biden-Harris administration's goal of deploying 30 GW of offshore wind power by 2030 and 110 GW by 2050, expansion of wind energy into U.S. territorial waters prone to tropical cyclones (TCs) and extratropical cyclones (ETCs) is essential. This requires a deeper understanding of cyclone-related risks and the development of robust, resilient offshore wind energy systems. Here, this paper provides a comprehensive review of state-of-the-science measurement and modeling capabilities for studying TCs and ETCs, and their impacts across various spatial and temporal scales. We explore measurement capabilities for environments influenced by TCs and ETCs, including near-surface and vertical profiles of critical variables that characterize these cyclones. The capabilities and limitations of Earth system and mesoscale models are assessed for their effectiveness in capturing atmosphere–ocean–wave interactions that influence TC/ETC-induced risks under a changing climate. Additionally, we discuss microscale modeling capabilities designed to bridge scale gaps from the weather scale (a few kilometers) to the turbine scale (dozens to a few meters). We also review machine learning (ML)-based, data-driven models for simulating TC/ETC events at both weather and wind turbine scales. Special attention is given to extreme metocean conditions like extreme wind gusts, rapid wind direction changes, and high waves, which pose threats to offshore wind energy infrastructure. Finally, the paper outlines the research challenges and future directions needed to enhance the resilience and design of next-generation offshore wind turbines against extreme weather conditions.

17 WIND ENERGY↗

DOE OSTI2022

Evaluation of coupled wind-wave model simulations of offshore winds in the Mid-Atlantic Bight using lidar-equipped buoys.

From 2014 to 2017, two Department of Energy buoys equipped with Doppler lidar were deployed off the U.S. East Coast to provide long term measurements of hub-height wind speed in the marine environment. In this study, we performed simulations of selected cases from the deployment using a 5-km configuration of the Weather Research and Forecasting (WRF) model, to see if simulated hub height speeds could produce closer agreement with the observations than existing reanalysis products. For each case we performed two additional simulations: one in which marine surface roughness height was one-way coupled to forecast wave parameters from a standalone WaveWatch III (WW3) simulation, and another in which WRF and WW3 were two-way coupled using the Coupled-Ocean-Atmosphere-Wave-Sediment-Transport (COAWST) framework. It was found that all the 5-km WRF simulations improved 90-m wind speed statistics for the tropical cyclone case of 08 May 2015 and the cold frontal case of 25 Mar 2016, but not the nor-easter of 18 Jan 2016. The impact of wave coupling on buoy-level (4 m) wind speed was modest and case dependent, but when present, the impact was typically seen at 90 m as well, being as large as 10% in stable conditions. One-way wave coupling consistently reduced wind speeds, improving biases for 25 Mar 2016 but worsening them for 08 May 2015. Two-way wave coupling mitigated these negative biases, improved wave field representation and statistics, and mostly improved 4-m wind field correlation coefficients, at least at the VA buoy, largely due to greater self-consistency between wind and wave fields.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Constructing a High‐Resolution Aftershock Catalog for the 2017 Mw 8.2 Tehuantepec Earthquake Sequence Using a Machine Learning–Based Workflow

The 8 September 2017 Mw 8.2 Tehuantepec earthquake was the largest instrumentally recorded normal‐faulting earthquake in Mexico. The mainshock occurred offshore within the Tehuantepec seismic gap, generating >30,000 aftershocks in the following year. We applied an open‐source, machine learning (ML)–assisted workflow to construct a high‐resolution aftershock catalog using data from temporary and permanent seismic networks in southern Mexico. The workflow integrates PhaseNet for phase detection; GaMMA for phase association; and VELEST, HypoInverse, and HypoDD for velocity modeling and relocation. We processed seven months of continuous waveform data from 29 broadband stations, including a temporary rapid‐response deployment that improved station coverage of the offshore rupture zone. To evaluate performance, we compared our results against analyst‐reviewed picks and event locations from the Servicio Sismológico Nacional catalog. The resulting catalog contains 11,374 relocated earthquakes and represents the most comprehensive published dataset for this sequence, incorporating the first full use of the temporary network. Relocated hypocenters show improved depth control and align well with the Slab2.0 subduction geometry, revealing clearer separation between offshore slab events and onshore crustal seismicity. This study demonstrates that combining ML‐based detection with established methods provides a scalable and reproducible approach for constructing high‐quality earthquake catalogs in tectonically complex environments and offers practical guidance for adapting similar workflows to other earthquake sequences.

Garcia, Marc [The University of Texas at El Paso, ↗

DOE OSTI2026

FOCAL Campaign II/III: Applying Active Hull Controls Using Tuned-mass Dampers/Hull Flexibility and Internal Loads

Campaign II and III of the Floating Offshore-wind Controls Advanced Laboratory Experimental Program (FOCAL) aimed to generate a dataset enabling the validation of the performance and loads of a scaled hull, with and without structural hull control. The floating platform was subjected to a variety of wave environments and controlled using tuned-mass dampers (TMDs) tuned to two of the systems natural frequencies (Platform Pitch and Tower-bending). The floating platform is fully instrumented to record a variety of parameters in real time such as platform dynamics, accelerations, and loads at different points in the structure. The test data considered was generated at the University of Maine's Harold Alfond Wind and Wave (W2) testing facility. This testing was focused only on validation of wave loading, and wind conditions were not considered. As such the platform does not support a working turbine, and instead supports a structure designed to have the same mass properties as the 1:70 IEA 15MW Reference turbine. The Load Cases (LC) considered in this testing campaign are as follows: LC 1.X - Platform Static Offset (TMD off); LC 2.X - Platform Free-decays (TMD off); LC 3.X - Wave Cases (Regular Wave, Irregular Wave, Pink Noise Wave) with and without TMDs active. Detailed properties on the model system are found in the following reference: Lenfest E., Floating Offshore-wind Controls Advanced Laboratory (FOCAL) Experimental Program - Campaigns 2 and 3: 1:70 Model-scale Testing of the IEA-Wind 15MW Reference Turbine and the VolturnUS-S Hull. UMaine ASCC Report Number 23-56-1183.

17 WIND ENERGY↗

NASA NTRS1997

Near-Surface Phytoplankton Pigment from the Coastal Zone Color Scanner in the Subantarctic Region Southeast of New Zealand

Primarily based on satellite images, the phytoplankton concentration southeast (down- stream) of New Zealand in the High Nitrate - Low Chlorophyll (HNLC) Subantarctic water between the Subtropical Convergence (STC) and the Polar Front (PF) is believed to be higher than in the remainder of the Pacific Sector. Iron enrichment is assumed to be the reason, To study the question, near-surface phytoplankton pigment estimates from the Coastal Zone Color Scanner for up to 7 yr were reprocessed with particular attention to interference by clouds. Monthly mean images were created for the U,S. JGOFS Box along 170 deg W and means for individual dates calculated for 7 large areas between 170 deg E and 160 deg W, 45 deg and 58 deg S, well offshore of New Zealand and principally between and away from the STC and PF. The areal means are about as low as in other HNLC regions (most values between 0.1 and 0.4 or 0.5 mg/ sq m, with very few winter images; median of seasonal means, 0.26 mg/sq m) except at times near the STC, The higher means tend to occur in late summer and autumn, However, contrary to expectations, neither the PF nor the environs of the Subantarctic Front are distinguished by a zone of increased pigment. Also, of 24 spring-summer images of oceanic islands in mostly pigment-poor water, 17 yielded no recognizable elevated pigment; islands were 5 times surrounded by approximately doubled concentrations (ca 100 km in diameter), and 2 cases may have been associated with an extensive bloom. Inspection of offshore images showed concentrations of 1 greater than or equal to(up to 5) mg/sq m in rare patches of 65 to 200 km size on approximately one-tenth of the dates; such patches were not seen in Sub-antarctic waters of the eastern Pacific Sector. A case is made for Australian airborne iron supply being the cause that, presumably, would enhance large-celled phytoplankton. Since, however, the putative iron supply from the seabed around the oceanic islands or the near-by Campbell Plateau normally does not lead to phytoplankton increase, patches of neritic mesozooplankton advected from the shelves might be another mechanism that generates blooms of small-cetled phytoplankton, but there are no data. These alternatives can easily be field-tested from concentration and size composition of the phytoplankton.

Banse, Karl↗

DOE OSTI2026

Genesis Mission-Enabled Secure AI to Fortify Energy Process Safety (Genesis-SAFE)

Argonne National Laboratory is supporting the U.S. Department of Transportation’s (USDOT’s) Bureau of Transportation Statistics (BTS) with collaborative research on development and application of privacy preserving AI frameworks that leverage unmatched AI expertise and secure computing resources made available through the U.S. Genesis Mission1 . This research advances U.S. energy security goals by supporting a safe offshore energy industry with secure, domain-specific AI tools to analyze confidential industry datasets collected by BTS to rapidly improve identification of hazards, precursors, and systemic safety risks in high-risk operational environments. The staged, security-first approach begins with development and testing of Argonne’s Genesis Mission-enabled Secure AI to Fortify Energy Process Safety (Genesis-SAFE) framework within Argonne’s accredited secure computing enclave (ABLE) leveraging Argonne’s AI scientific assistant substrate (AISAC). Methods to build synthetic datasets were developed together with BTS for use in preparing synthetic datasets that can be used to validate data containment, governance, and security controls in the ABLE environment. Future research directions would focus on applying the Genesis-SAFE framework to CIPSEA-protected datasets entirely within ABLE to support confidentiality-preserving analysis of safety risks, trends, and contributing factors.

Kim, Hyekyung [Argonne National Laboratory (ANL), ↗

NASA NTRS2003

Tower-Perturbation Measurements in Above-Water Radiometry

This report documents the scientific activities which took place during June 2001 and June 2002 on the Acqua Alta Oceanographic Tower (AAOT) in the northern Adriatic Sea. The primary objective of these field campaigns was to quantify the effect of platform perturbations (principally reflections of sunlight onto the sea surface) on above-water measurements of water-leaving radiances. The deployment goals documented in this report were to: a) collect an extensive and simultaneous set of above- and in-water optical measurements under predominantly clear-sky conditions; b) establish the vertical properties of the water column using a variety of ancillary measurements, many of which were taken coincidently with the optical measurements; and c) determine the bulk properties of the environment using a diversity of atmospheric, biogeochemical, and meteorological techniques. A preliminary assessment of the data collected during the two field campaigns shows the perturbation in above-water radiometry caused by a large offshore structure is very similar to that caused by a large research vessel.

Hooker, Stanford B.↗

NASA NTRS2003

Tower-Perturbation Measurements in Above-Water Radiometry

Hooker, Stanford B.↗

DOE OSTI2026

Cybersecurity Center for Offshore Wind Energy (Final Project Report)

This project establishes a Cybersecurity Center for Offshore Wind Energy with the objective of designing and operating a cyber-physical testbed for wind energy farms (WEFs) that enables comprehensive cybersecurity research. The testbed incorporates a Supervisory Control and Data Acquisition (SCADA) system connected to turbine models via industrial-grade programmable logic controllers (PLCs) and remote terminal units (RTUs). It supports side-channel data acquisition, implementation and analysis of various cyberattack scenarios, and development of attack detection, mitigation, and best-practice guidance tailored to wind energy systems. During the project, the team expanded the number and fidelity of mathematical turbine models (MTMs), integrated these models with SCADA infrastructure, and deployed a scaled physical turbine and associated sensors. High-resolution operational and side-channel data streams were collected and used to refine machine-learning (ML)-based attack detection systems and to extend the WindCRAFT framework to multi-turbine threat scenarios. The project demonstrated a realistic, scalable environment for evaluating cyber threats, validated attack detection approaches using enriched datasets, and identified new multi-turbine and inter-turbine communication attack vectors. The resulting testbed, models, and security mechanisms provide a foundation for ongoing R&D and deployment of cyber-resilient offshore wind energy systems.

17 WIND ENERGY↗

DOE OSTI2024

2024 OES-Environmental 2024 State of the Science Report, Chapter 9: Beyond Single Marine Renewable Energy Devices: A System-wide Effects Approach

Global expansion of renewable energy, including marine renewable energy (MRE) technology development is necessary to mitigate the effects of climate change, facilitate a sustainable transition from carbon-based energy sources, and satisfy national energy security needs using locally produced electricity (European Commission 2022; IPCC 2023; IRENA 2020). As MRE engineering and research continue to focus on designing devices for deployment in nearshore and offshore waters around the world, researchers are also examining potential environmental effects on marine animals, habitats, and ecosystem processes. To date, the focus has been on interactions between small numbers of MRE devices (1-6) and the environment, such as collisions between animals and turbine blades, the effects of underwater noise and electromagnetic field (EMF) emissions, changes in habitats and oceanographic processes, risk of entanglement of animals, and displacement of animals (Boehlert & Gill 2010; Copping & Hemery 2020) (see Chapter 3).

16 TIDAL AND WAVE POWER↗

NASA NTRS1974

Application of ERTS-1 data to the protection and management of New Jersey's coastal environment

The author has identified the following significant results. Rapid access to ERTS data was provided by NASA GSFC for the February 26, 1974 overpass of the New Jersey test site. Forty-seven hours following the overpass computer-compatible tapes were ready for processing at EarthSat. The finished product was ready just 60 hours following the overpass and delivered to the New Jersey Department of Environmental Protection. This operational demonstration has been successful in convincing NJDEP as to the worth of ERTS as an operational monitoring and enforcement tool of significant value to the State. An erosion/ accretion severity index has been developed for the New Jersey shore case study area. Computerized analysis techniques have been used for monitoring offshore waste disposal dumping locations, drift vectors, and dispersion rates in the New York Bight area. A computer shade print of the area was used to identify intensity levels of acid waste. A Litton intensity slice print was made to provide graphic presentation of dispersion characteristics and the dump extent. Continued monitoring will lead to the recommendation and justification of permanent dumping sites which pose no threat to water quality in nearshore environments.

Yunghans, R. S.↗