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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

D–MOPH–25: diverse MOF–molecule pairs for Henry’s constants prediction

Computational methods like grand-canonical Monte Carlo simulations and machine learning (ML) have accelerated metal–organic frameworks (MOF) exploration but are typically limited to a narrow range of adsorbates due to data availability and force field constraints. In this study, we introduce a dataset of diverse MOF–molecule pairs for Henry’s constant prediction, D–MOPH–25, which systematically explores a diverse chemical space by combining 113 molecular adsorbates with over 5000 MOF structures through an active learning process. D–MOPH–25 constitutes the most diverse adsorbate dataset used in any ML study of molecular adsorption in MOFs to date. Our workflow builds a benchmark for predicting Henry’s constants at 300 K, leveraging conformal prediction for uncertainty quantification. Assessment through Shannon entropy and uniform manifold approximation and projection confirms the comprehensiveness of D–MOPH–25 while highlighting the importance of robust classification to filter out unphysical data points in regression tasks. Although future enhancements in model architecture and sampling criteria could improve predictive performance, our dataset already spans the target space using only 2.31% of total possibilities. This comprehensive dataset facilitates assessment of model generalizability across adsorbate species and can establish a foundation for high-throughput MOF screening and ML-driven separation processes.

active learning↗
DOE OSTI2019

Collaborative Robots vs. Master/Slaves - 19522

This paper will discuss the feasibility, application, and economy of applying collaborative robots (co-bots) in lieu of traditional through-the-wall tele-operated manipulator systems, traditionally used within hazardous (radioactive) environments. Both fixed facility and mobile applications will be discussed. Both single- and dual-armed co-bot systems will be employed. The six-axis, plus gripper, single-armed co-bots will provide for machine vision enhanced pick-n-place applications within shielded rooms and also include force-reflecting (haptic) teleoperations controls for non-routine materials-handling operations. The dual-armed system will be mounted to a motorized stand with motorized adjustment both vertically and rotationally (around its base). To complement these co-bots, both two-dimensional and three-dimensional vision technologies will be implemented. The vision technologies, in these applications, are used in lieu of traditional radiation shielding windows. two-dimensional video systems will provide for large area viewing, incorporating pan, tilt, and zoom capabilities. Three-dimensional video systems will be mounted to the dual-armed robot stand and provide viewing, including depth-of-perception, to the operator, performing material handling and other tasks, from an operator workstation located outside the hazardous environment. The unique workstation used with the dual-armed systems will also be described. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Conceptual Design of DUNE Near Detector Superconducting Magnet System

The Deep Underground Neutrino Experiment (DUNE) has formed a near detector design group (NDDG) tasked with delivering a CDR by the end of 2019. The DUNE Near Detectors will be housed in an underground hall on the Fermilab site. The two main detector systems are a liquid argon detector and a high-pressure gas time projection chamber (HPgTPC). The HPgTPC requires a magnet that generates a 0.5 T solenoidal magnetic field in a large volume of 6 m diameter, and 5 m length. Herein, we present a superconducting magnet system design. We investigated: an open air core magnet with three coils, and a five coils system having two active fringe field shielding coils. Coils positions were optimized to obtain the specified field homogeneity in the magnet good field region, while minimizing the Lorentz forces and the superconductor volume. We discuss the magnetic, mechanical, and thermal conceptual designs.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

The Full Scale Seal Experiment - A Seal Industrial Prototype for Cigeo - 13106

The Full Scale Seal (FSS) Experiment is one of various experiments implemented by Andra, within the frame of the Cigeo (the French Deep Geological Repository) Project development, to demonstrate the technical construction feasibility and performance of seals to be constructed, at time of Repository components (shafts, ramps, drifts, disposal vaults) progressive closure. FSS is built inside a drift model fabricated on surface for the purpose. Prior to the scale 1:1 seal construction test, various design tasks are scheduled. They include the engineering work on the drift model to make it fit with the experimental needs, on the various work sequences anticipated for the swelling clay core emplacement and the concrete containment plugs construction, on the specialized handling tools (and installation equipment) manufactured and delivered for the purpose, and of course on the various swelling clay materials and low pH (below 11) concrete formulations developed for the application. The engineering of the 'seal-as-built' commissioning means (tools and methodology) must also be dealt with. The FSS construction experiment is a technological demonstrator, thus it is not focused on the phenomenological survey (and by consequence, on the performance and behaviour forecast). As such, no hydration (forced or natural) is planned. However, the FSS implementation (in particular via the construction and commissioning activities carried out) is a key milestone in view of comforting phenomenological extrapolation in time and scale. The FSS experiment also allows for qualifying the commissioning methods of a real sealing system in the Repository, as built, at time of industrial operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Multichannel haptic feedback unlocks prosthetic hand dexterity

Abstract Loss of tactile sensations is a major roadblock preventing upper limb-absent people from multitasking or using the full dexterity of their prosthetic hands. With current myoelectric prosthetic hands, limb-absent people can only control one grasp function at a time even though modern artificial hands are mechanically capable of individual control of all five digits. In this paper, we investigated whether people could precisely control the grip forces applied to two different objects grasped simultaneously with a dexterous artificial hand. Toward that end, we developed a novel multichannel wearable soft robotic armband to convey artificial sensations of touch to the robotic hand users. Multiple channels of haptic feedback enabled subjects to successfully grasp and transport two objects simultaneously with the dexterous artificial hand without breaking or dropping them, even when their vision of both objects was obstructed. Simultaneous transport of the objects provided a significant time savings to perform the deliveries in comparison to a one-at-a-time approach. This paper demonstrated that subjects were able to integrate multiple channels of haptic feedback into their motor control strategies to perform a complex simultaneous object grasp control task with an artificial limb, which could serve as a paradigm shift in the way prosthetic hands are operated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Deep Convection: Onset, Diurnal Cycle, and Role in Climate Variability and Sensitivity (Final Report)

The ASR SGP testbed for continuous modeling offers new opportunities to improve GCM parameterizations. We conducted an ASR investigation of convective and cloud microphysical processes that used existing ARM data as a testing ground for meaningful approaches to model evaluation and set the stage for later strategic use of the testbed to improve cumulus parameterizations and better understand deep convective cloud feedback. Our research consisted of the following tasks: Diurnal cycle of continental convection Deep convection at the SGP occurs in two forms: Organized mesoscale convection that originates upstream and produces peak precipitation at night; and local shallow convection that develops into deep convection that peaks in late afternoon. Local transitions are a logical next step from the shallow convection that will be the early focus of the testbed. This transition constrains entrainment and cold pools, since GCMs produce a continental rain peak near noon. We studied ARSCL-observed transition cases using the WRF, determined the sources of SCM diurnal cycle errors and made parameterization changes as appropriate. Factors controlling convective detrainment and anvil evolution Convective detrainment is a major source of high cloud ice water content and cloud forcing. The GISS GCM diagnoses a convective updraft speed profile, assumes a particle size distribution (PSD), and uses size-fallspeed relations to determine the fraction of condensate carried upward vs. precipitating. We used SCM case studies for TWP-ICE and MC3E for which vertical velocity has been retrieved to test whether entrainment improvements produce realistic updraft speeds and then improved the updraft microphysics parameterization. We compared detrained ice water contents and fall speeds to ARM and other field experiment data to refine the GCM’s fall speed and PSD assumptions. Role of convective cloud radiative processes in the Madden-Julian Oscillation (MJO) Changes in entrainment and rain evaporation and a cold pool parameterization have produced an MJO in the GISS GCM for the first time and allowed us to reproduce the KAZR dependence of convection depth on humidity during AMIE-Gan. We determined whether recent model changes including cold pools improve or degrade the MJO and made adjustments accordingly.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Reinforcement Learning for Anomaly Detection in Nuclear Power Plant Operation and Maintenance

In nuclear power plants (NPPs), timely identification of sensor and human errors is critical to ensure safe and efficient plant operations. Anomaly detection models can be employed for this task. However, traditional anomaly detection approaches may have high dependency on labeled datasets and struggle with adaptability in complex, dynamic environments. Reinforcement learning (RL) has demonstrated significant potential in fault diagnosis and anomaly detection; however, its application to anomaly detection in NPPs remains a relatively underexplored research direction. Hence, to address this gap, in this study, we present a novel physics-informed reinforcement learning model, PIRL-AD: Physics-Informed Reinforcement Learning for Anomaly Detection, that integrates domain knowledge from calorimetric equations into the RL framework for enhanced sensor and human error anomaly detection. We evaluate the performance of PIRL-AD against a non-physics informed RL benchmark and a support vector machine (SVM) on data collected from a forced flow loop testbed. Experimental results suggest that PIRL-AD outperforms other baselines on a range of anomalous datasets that include both sensor and human-induced anomalies across key performance metrics, statistically outperforming the RL and SVM benchmarks with respect to geometric mean (respectively, 92.96% vs. 91.06% vs. 83.01%) and F1-score (respectively, 89.23% vs. 86.98% vs. 77.01%). Furthermore, the findings suggest the potential of physics-integrated reinforcement learning models for enhanced anomaly detection performance in NPPs.

Reinforcement learning↗
DOE OSTI2023

Data-Driven Transition Path Analysis Yields a Statistical Understanding of Sudden Stratospheric Warming Events in an Idealized Model

Abstract Atmospheric regime transitions are highly impactful as drivers of extreme weather events, but pose two formidable modeling challenges: predicting the next event (weather forecasting) and characterizing the statistics of events of a given severity (the risk climatology). Each event has a different duration and spatial structure, making it hard to define an objective “average event.” We argue here that transition path theory (TPT), a stochastic process framework, is an appropriate tool for the task. We demonstrate TPT’s capacities on a wave–mean flow model of sudden stratospheric warmings (SSWs) developed by Holton and Mass, which is idealized enough for transparent TPT analysis but complex enough to demonstrate computational scalability. Whereas a recent article (Finkel et al. 2021) studied near-term SSW predictability, the present article uses TPT to link predictability to long-term SSW frequency. This requires not only forecasting forward in time from an initial condition, but also backward in time to assess the probability of the initial conditions themselves. TPT enables one to condition the dynamics on the regime transition occurring, and thus visualize its physical drivers with a vector field called the reactive current . The reactive current shows that before an SSW, dissipation and stochastic forcing drive a slow decay of vortex strength at lower altitudes. The response of upper-level winds is late and sudden, occurring only after the transition is almost complete from a probabilistic point of view. This case study demonstrates that TPT quantities, visualized in a space of physically meaningful variables, can help one understand the dynamics of regime transitions.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Plutonium Dedicated Surface Probe Microscopy Capability

An atomic force microscope (AFM) equipped with gas dosing capabilities and a scanning tunneling microscope (STM) housed within a vacuum chamber with Pu sputtering capabilities and the potential for rapid heating via electron bombardment have been devised for investigations of Pu surface aging (such as oxidation, corrosion, and self-irradiation damage), reactivity, and rapid heating. These instruments are capable of probing Pu surface areas ranging from a fractions of nm2 (STM) to hundreds of μm2 (AFM) to obtain three dimensional imaging of surface microstructure and morphology, as well as mapping of the local electronic structure (i.e., the occupied and unoccupied electronic states), surface chemical, and mechanical properties. A detailed description of our surface probe microscopy (SPM) capability, specifically designed for handling of Pu coupons is given in the references. In FY20, four tasks have been undertaken: Resumed maintenance of Pu AFM and modification of STM capabilities including calibration, annual measurement of Pu surface, and implementation of additional instrumentation for rapid heating effort; Analyzed AFM FY19 gas dosing experiment data of 7 at% gallium-stabilized δ-phase Pu (δ-Pu) coupon; Determined the direction of future gas dosing experiments to investigate reversibility of surface features; and, Published a paper titled "Effects of ion sputtering on plutonium surfaces" in the Journal of Nuclear Materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Molecular dynamics simulations of uranyl and plutonyl cations in a task-specific ionic liquid

Ionic liquids (ILs) are a unique class of solvents with potential applications in advanced separation technologies relevant to the nuclear industry. ILs are salts with low melting points and a wide range of tunable physical properties, such as viscosity, hydrophobiciy, conductivity, and liquidus range. ILs have negligible vapor pressure, are often non-flammable, and can have high thermal stability and a wide electrochemical window, making them attractive for use in separations processes relevant to the nuclear industry. Metal salts generally have a low solubility in ILs; however, by incorporating new functional groups into the IL cation or anion that promote complexation with the metal, the solubility can be greatly increased. One such task-specific ionic liquid (TSIL) is 1-carboxy-N, N, N-trimethylglycine bis(trifluoromethylsulfonyl)imide ([Hbet][Tf 2 N]). Water, which is detrimental for electrochemical separations, is a common impurity in ILs and can coordinate with actinyl cations, particularly in ILs containing only weakly coordinating components. Understanding the behavior of actinides in TSIL/water mixtures on a molecular level is vital for designing improved separations processes. Classical molecular dynamics simulations of uranyl(VI) and plutonyl(VI) in 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][Tf 2 N]) with deprotonated Hbet (betaine) and water have been performed to understand the coordination and dynamics of the actinyl cations. We find that betaine is a much stronger ligand than water and prefers to coordinate the metal in a bidentate manner. Potential of mean force simulations yield a relative free energy for betaine coordination of approximately -120 to -90 kJ/mol in mixtures with water. As the amount of betaine coordinated to the actinide increases, the diffusion coefficient of the actinyl cation decreases. Moreover, the betaine ligand is able to bridge between two metal centers, resulting in dimeric complexes with actinide–actinide distances of ~5 Å. Potential of mean force simulations show that these structures are stable, with relative free energies of up to -40 kJ/mol. The crystal structure for [(UO 2 ) 2 (bet) 6 (H 2 O) 2 ][Tf 2 N] 4 shows that the betaine bridges between two uranium atoms to form dimeric complexes similar to those found in our simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Multiphysics Object Oriented Simulation Environment

The Multiphysics Object Oriented Simulation Environment (MOOSE) software library developed at Idaho National Laboratory is a tool. MOOSE, like other tools, doesn't actually complete a task. Instead, MOOSE seeks to reduce the effort required to create engineering simulation applications. MOOSE itself is a software library: a blank canvas upon which you write equations and then MOOSE can help you solve them. MOOSE is comparable to a spreadsheet application. A spreadsheet, by itself, doesn't do anything. Only once equations are entered into it will a spreadsheet application compute anything. Such is the same for MOOSE. An engineer or scientist can utilize the equation solvers within MOOSE to solve equations related to their area of study. For instance, a geomechanical scientist can input equations related to water flow in underground reservoirs and MOOSE can solve those equations to give the scientist an idea of how water could move over time. An engineer might input equations related to the forces in steel beams in order to understand the load bearing capacity of a bridge. Because MOOSE is a blank canvas it can be useful in many scientific and engineering pursuits.

Source record↗
DOE OSTI2024

High-Fidelity Numerical Wave Tank Verification & Validation Study: Wave Generation Through Paddle Motion: Preprint

This paper presents a numerical benchmark study of wave propagation due to a paddle motion using different high-fidelity numerical models, which are capable of replicating the nearly actual physical wave tank testing. A full time series of the measured wave generation paddle motion which was used to generate wave propagation in the physical wave tank will be utilized in each of the models contributed by IEA OES Task 10's participants, which includes both computational fluid dynamics (CFD) and smooth hydrodynamic particle (SPH). The high-fidelity simulations of the physical wave testcase will allow for the evaluation of the initial transient effects from wave ramp-up and its evolution in the wave tank over time for two representative regular waves with varying levels of nonlinearity. A couple of interesting metrics like the predicted wave surface elevation at select wave probes, wave period, and phase-shift in time will be assessed to evaluate the relative accuracy of numerical models versus experimental data within specified time intervals. These models will serve as a guide for modelers in the wave energy community and provide a base case to allow further and more detailed numerical modeling of the fixed Kramer Sphere Cases under wave excitation force wave tank testing.

HYDRO ENERGY,TIDAL AND WAVE POWER↗
DOE OSTI2026

Foundation models for atomistic simulation of chemistry and materials

Conventional computational methods for modeling chemical and materials systems are limited by system size and timescale, forcing a trade-off between quantum-mechanical accuracy and the sampling needed for realistic observables. Large language and vision foundation models — pre-trained on massive datasets using transformer architectures — have revolutionized many fields. It is thus interesting to ask whether a foundation model — subject to suitable data, parameter scaling and training — could enable learned simulations of chemistry and materials. Here, in this study, we review the field of machine-learned interatomic potentials (MLIPs) and posit that scaling up large and diverse chemical and materials datasets and highly expressive architectures using advanced training strategies should result in models that are: more efficient, transferable, robust to out-of-distribution scenarios, and easier to fine-tune to a variety of downstream physical observables than models trained from scratch on small datasets corresponding to specific, targeted atomistic simulation tasks. We provide specific criteria for creating such large-scale MLIP foundation models, coordinated strategies for their development, evaluation and deployment, and highlight potential emergent capabilities that could transform predictive simulations in chemistry and materials science and accelerate discovery across multiple technological domains.

Yuan, Eric C.-Y. [University of California, Berkel↗
DOE OSTI2023

The AXEAP2 program for K β X-ray emission spectra analysis using artificial intelligence

The processing and analysis of synchrotron data can be a complex task, requiring specialized expertise and knowledge. Our previous work addressed the challenge of X-ray emission spectrum (XES) data processing by developing a standalone application using unsupervised machine learning. However, the task of analyzing the processed spectra remains another challenge. Although the non-resonant K β XES of 3 d transition metals are known to provide electronic structure information such as oxidation and spin state, finding appropriate parameters to match experimental data is a time-consuming and labor-intensive process. Here, a new XES data analysis method based on the genetic algorithm is demonstrated, applying it to Mn, Co and Ni oxides. This approach is also implemented as a standalone application, Argonne X-ray Emission Analysis 2 ( AXEAP2 ), which finds a set of parameters that result in a high-quality fit of the experimental spectrum with minimal intervention. AXEAP2 is able to find a set of parameters that reproduce the experimental spectrum, and provide insights into the 3 d electron spin state, 3 d –3 p electron exchange force and K β emission core-hole lifetime.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Assessment on DNB performance for high pressure subcooled boiling with modified CASL boiling model

Understanding and predicting the Departure from Nucleation Boiling phenomena in the nuclear power industry has been a grand challenge due to its large impact on the reactor safety and operational economics. Over the past several years, CASL THM team has extensively investigated and demonstrated a state of art Multiphase CFD framework to provide a high-fidelity DNB simulation capability based on the two-fluid Eulerian model in conjunction with a wall heat flux partitioning approach. The overarching goal of this task is to develop and demonstrate a robust CFD-based DNB model which is capable of predicting an entire boiling history up to the DNB condition in which the wall boiling mode is transitioning from the nucleate boiling mode to the film boiling mode. Three different flow channel configurations (pipe flow, 5x5 fuel bundle with and without mixing vane tests) were studied and thorough closure sensitivity studies were performed to evaluate the wall boiling and momentum closure effect on the DNB performance. Predicated DNB values were compared to the measurements from high pressure subcooled flow boiling tests resulting in a consistent under-predictive trend for all three validation campaigns in FY16-18. With extensive closure sensitivity study, a modified CASL boiling closure model (i.e. Gen1-FY19) is introduced with the following key changes: 1) improved wall boiling closure for high pressure application, 2) newly calibrated lift and wall lubrication force models with modified interfacial length scale model, and 3) updated liquid phase condensation model calibrated for the subcooled boiling application.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Comparison of loads from HAWC2 and OpenFAST for the IEA Wind 15 MW Reference Wind Turbine

Reference wind turbines (RWTs) that reflect the state-of-the-art of current wind energy technology are necessary in order to properly evaluate innovative methods in wind turbine design and evaluation. The International Energy Agency (IEA) Wind Technology Collaboration Platform (TCP) Task 37 has recently developed a new RWT geared towards offshore floating-foundation applications: the IEA Wind 15 MW. The model has been implemented in two aeroelastic codes, OpenFAST and HAWC2, based on an underlying common ontology. However, these toolchains result in slightly different structural parameters, and the two codes utilise different structural models. Thus, to increase the utility of the model, it is necessary to compare the aeroelastic responses. This paper compares aeroelastic loads calculated using different fidelities of the blade model in OpenFAST (ElastoDyn and BeamDyn) and HAWC2 (prismatic Timoshenko without torsion and Timoshenko with fully populated stiffness matrix), where both codes use the DTU Basic controller and the same turbulence boxes to reduce discrepancies. The aeroelastic responses to steady wind, step wind and turbulent wind (per IEC 61400-1 wind class IB) are considered. The results indicate a generally good agreement between the loads dominated by aerodynamic thrust and force, especially for the no-torsion blade models. Discrepancies were observed in other load channels, partially due to differences in the asymmetric loading of the rotor and partially due to differing closed-loop dynamics, and they will be the subject of future investigations.

17 WIND ENERGY↗
DOE OSTI2013

National Open-ocean Energy Laboratory (Final Technical Report)

Under the authorization provided by Section 634 of the Energy Independence and Security Act of 2007 (P.L. 110-140), in 2009 FAU was awarded U.S. Congressionally Directed Program (CDP) funding through the U.S. Department of Energy (DOE) to investigate and develop technologies to harness the energy of the Florida Current as a source of clean, renewable, base-load power for Florida and the U.S. A second CDP award in 2010 provided additional funding in order to enhance and extend FAU’s activities. These two CDPs in 2009 and 2010 were combined into a single DOE grant, DE-EE0000319, and are the subject of this report. Subsequently, in July 2010 funding was made available under a separate contract, DE-EE0004200. Under that funding, DOE’s Wind and Water Power Program designated FAU’s state of Florida marine renewable energy (MRE) center as the Southeast National Marine Renewable Energy Center (SNMREC). This report discusses SNMREC activities funded by the DE-EE0000319 grant, but will make reference, as appropriate, to activities that require further investigation under the follow-on grant. The concept of extracting energy from the motions of the oceans has a long history. However, implementation on large scales of the technologies to effect renewable energy recovery from waves, tides, and open-ocean currents is relatively recent. DOE’s establishment of SNMREC recognizes a significant potential for ocean current energy recovery associated with the (relatively) high-speed Florida Current, the reach of the Gulf Stream System flowing through the Straits of Florida, between the Florida Peninsula and the Bahamas Archipelago. The proximity of the very large electrical load center of southeast Florida’s metropolitan area to the resource itself makes this potential all the more attractive. As attractive as this potential energy source is, it is not without its challenges. Although the technology is conceptually simple, its design and implementation in a commercially-viable fashion presents a variety of challenges. Beyond the technology itself (and, especially, the effects on the technology of the harsh oceanic environment), it is important to consider the possible environmental impacts of commercial-scale implementation of oceanic energy extraction. Further, because such implementation represents a completely new undertaking, the human resources required do not exist, so education and training programs are critical to eventual success. This project, establishing a national open-ocean energy laboratory, was designed to address each of these three challenges in a flexible framework allowing for adaptive management as the project proceeded. In particular: the technology challenge, including resource assessment, evolved during the project to recognize and address the need for a national testing facility in the ocean for small-scale prototype MRE systems developed by industry; the environmental challenge became formalized and expanded during the permitting process for such a testing facility; and the human resources/societal challenges, both in terms of the need for education and training and in terms of public acceptance of MRE, stimulated a robust outreach program far beyond that originally envisioned at SNMREC. While all of these activities at SNMREC are ongoing, a number of significant milestones (in addition to the contributions listed in the appendices) were achieved under the auspices of this award. These include: Planning and site selection for the first-phase test facility, offshore of Dania Beach, FL, including some equipment for the facility, submission of an Interim Policy Lease Application to the U.S. Department of Interior’s Bureau of Ocean Energy Management (BOEM), and completion of an Environmental Assessment by BOEM and a positive Consistency Determination by the State of Florida; Measurements using acoustic profilers of the current structure and variability in the vicinity of the site under a variety of weather conditions, seasons and time durations; Design and implementation of instrumentation for the first phase of the offshore testing facility, the wet- and top-side data acquisition systems, and shore-based analysis systems; Implementation of a laboratory-scale dynamometer system to test generators of up to 25 kW capacity using real-world (simulated) forcing; Completion of 24 months of (airborne) marine vertebrate surveys and associated analysis of sea turtle offshore activity, marine mammal vocalization research, and ocean current turbine hydrodynamic noise characterization; Development of a secondary-school (nominally grade 10) curriculum about hydrokinetic MRE, “Energy from the Oceans: The New Renewable”, and training of over 200 high-school teachers in its use and in how to educate their colleagues in application of the material in the classroom; Presentations to over 50 interested civic groups in the region on various aspects of MRE in SE Florida A series of public lectures to over 600 residents of south Florida to provide broader education on MRE. Development of an interactive kiosk for installation in local science museums. These, and other accomplishments detailed in this report contribute to a comprehensive ongoing program at the SNMREC to support the affordable, responsible, and achievable commercialization of MRE. Many of the tasks of this award are continued or will be verified with follow-on funding DE-EE0004200, and its goal: the installation of the world’s first offshore ocean current turbine testing and validation capability.

16 TIDAL AND WAVE POWER↗
DOE OSTI2013

Offshore Code Comparison Collaboration, Continuation: Phase II Results of a Floating Semisubmersible Wind System: Preprint

Offshore wind turbines are designed and analyzed using comprehensive simulation tools that account for the coupled dynamics of the wind inflow, aerodynamics, elasticity, and controls of the turbine, along with the incident waves, sea current, hydrodynamics, and foundation dynamics of the support structure. The Offshore Code Comparison Collaboration (OC3), which operated under the International Energy Agency (IEA) Wind Task 23, was established to verify the accuracy of these simulation tools [1]. This work was then extended under the Offshore Code Comparison Collaboration, Continuation (OC4) project under IEA Wind Task 30 [2]. Both of these projects sought to verify the accuracy of offshore wind turbine dynamics simulation tools (or codes) through code-to-code comparison of simulated responses of various offshore structures. This paper describes the latest findings from Phase II of the OC4 project, which involved the analysis of a 5-MW turbine supported by a floating semisubmersible. Twenty-two different organizations from 11 different countries submitted results using 24 different simulation tools. The variety of organizations contributing to the project brought together expertise from both the offshore structure and wind energy communities. Twenty-one different load cases were examined, encompassing varying levels of model complexity and a variety of metocean conditions. Differences in the results demonstrate the importance and accuracy of the various modeling approaches used. Significant findings include the importance of mooring dynamics to the mooring loads, the role nonlinear hydrodynamic terms play in calculating drift forces for the platform motions, and the difference between global (at the platform level) and local (at the member level) modeling of viscous drag. The results from this project will help guide development and improvement efforts for these tools to ensure that they are providing the accurate information needed to support the design and analysis needs of the offshore wind community.

17 WIND ENERGY↗