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DOE OSTI2026

Divergent carbon use efficiency-growth rate tradeoff in popular biological growth models

Carbon use efficiency (CUE) is an important trait emerging from processes regulating biological growth. CUE can be computed either based on the growth of structural biomass or total biomass divided by substrate uptake rate. Nonequilibrium thermodynamics and observations suggest that, for an exponentially growing population of cells, structural biomass CUE should first increase, then peak, and finally decrease with specific growth rate; meanwhile, total biomass CUE increases asymptotically with specific growth rate. We compared predictions from six popular models that are often used for plant and microbial growth in existing ecosystem models. We found that, for an exponentially growing population of biological cells, (1) the source-driven Pirt and Compromise models predict that structural biomass CUE increase asymptotically with growth rate; (2) the apparent sink-driven modified Droop model predicts that structural biomass CUE decreases with growth rate; and (3) the sink-driven variable internal storage model and two dynamic energy budget models predict that structural biomass CUE first increases, then peaks, and finally decreases with growth rate. Moreover, the modified Droop model predicts that total biomass CUE is constant with growth rate, while all other five models predict that total biomass CUE increases with growth rate asymptotically. For non-exponential biological growth, we show that there is no static relationship between total biomass CUE or structural biomass CUE with respect to either growth rate or temperature. Therefore, we contend that biological growth models should explicitly represent interactions between substrate acquisition, substate transformation, and maintenance respiration to better capture observed CUE dynamics, and the sink-driven model should be preferred for general ecosystem biogeochemistry modeling.

Tang, Jinyun [Lawrence Berkeley National Laborator↗

DOE OSTI2026

Roadmap and Benchmarking: Privacy in Federated Load Forecasting

Data-driven techniques for energy demand forecasting continue to emerge with promising impacts on distribution grid planning. However, the development of robust and generalizable machine learning models requires that representative high quality training data are available. Distributed energy resources have begun to embed intelligence, gathering large amounts of data on customer demand, behavior, and household devices that are connected to the grid. Though utilities aggregate meter-level demand data for load shaping, demand response, outage management, reliability planning, and billing applications, there lies an inherent privacy concern in sharing consumption data that may identify individual consumer behavioral patterns. Hence, while sharing the data is crucial, the private sensitive customer data must be safeguarded from being exposed or manipulated. In this study, we propose a roadmap for implementing a based privacy preserving framework to support the advancement of data-driven analytics in data-sensitive distributed energy resources environments. The roadmap incorporates federated learning–a distributed training framework, differential privacy–a statistical framework that provides guarantees to safeguard the leakage of sensitive data, secure multiparty computation and homomorphic encryption– techniques for encrypting model gradients and applying secure aggregation on the server. Moreover, we perform baseline experiments on the federated short-term load forecasting (STLF) task using open-source residential load profile datasets, offering insights into the challenges of integrating differential privacy into federated learning.

Abebe, Waqwoya [Oak Ridge National Laboratory (ORN↗

DOE OSTI2023

Interface Design for High‐Performance All‐Solid‐State Lithium Batteries

All‐solid‐state batteries suffer from high interface resistance and lithium dendrite growth leading to low Li plating/stripping Coulombic efficiency (CE) of <90% and low critical current density at high capacity. Here, in this work, both challenges are simultaneously addressed and the Li plating/stripping CE is significantly increased to 99.6% at 0.2 mA cm −2 /0.2 mAh cm −2 , and critical current density (CCD) of > 3.0 mA cm −2 /3.0 mAh cm −2 by inserting a mixed ionic‐electronic conductive (MIEC) and lithiophobic LiF‐C‐Li 3 N‐Bi nanocomposite interlayer between Li 6 PS 5 Cl electrolyte and Li anode. The highly lithiophobic LiF‐C‐Li 3 N‐Bi interlayer with high ionic conductivity (10 −5 S cm −1 ) and low electronic conductivity (3.4×10 −7 S cm −1 ) enables Li to plate on the current collector (CC) surface rather than on Li 6 PS 5 Cl surface avoiding Li 6 PS 5 Cl electrolyte reduction. During initial Li plating on CC, Li penetrates into porous LiF‐C‐Li 3 N‐Bi interlayer and lithiates Bi nanoparticles into Li 3 Bi. The lithiophilic Li 3 Bi and Li 3 N nanoparticles in LiF‐C‐Li 3 N‐Li 3 Bi sub‐interlayer will move to CC along with plated Li, forming LiF‐C/Li 3 N‐Li 3 Bi lithiophobic/lithiophilic sublayer during the following Li stripping. This interlayer enables Co 0.1 Fe 0.9 S 2 /Li 6 PS 5 Cl/Li cell with an areal capacity of 1.4 mAh cm −2 to achieve a cycle life of >850 cycles at 150 mA g −1 . The lithiophobic/lithiophilic interlayer enables solid‐state metal batteries to simultaneously achieve high energy and long cycle life.

25 ENERGY STORAGE↗

DOE OSTI2023

Photoelectrochemical materials for solar energy conversion

Research and development on semiconductors for applications in solar energy conversion has witnessed rapid growth over the past several decades. With the aim of producing chemical fuels from sunlight, intense research efforts have focused on the discovery of semiconductors with crystalline structures and chemical compositions that have the potential to satisfy the complex set of required photoelectrochemical properties. This chapter focuses on the foundational structure-property relationships of selected oxide and nitride semiconductors relevant to their uses as n-/p-type photoelectrodes and as photocatalysts. Their solid-state structures and compositions are described, with a special emphasis on strategies proven effective at targeting suitable band gaps with strong visible-light absorption, efficient charge separation and diffusion of charge carriers, and optimal band edge energies for driving surface redox reactions for water splitting.

O’Donnell, Shaun↗

DOE OSTI2026

A multiscale packed-bed reactor model for sustainable ethylene production via chemical looping oxidative coupling of methane

The rising global warming concerns and shale gas discovery have prompted research in the direction of greenhouse gas (GHG), such as methane, reduction and conversion. Oxidative coupling of methane (OCM) offers a pathway to low carbon-intense valorization of methane while producing ethylene, a chemical regarded as central to the petrochemical industry. Even after decades of OCM discovery, researchers keep understanding the process and underlying chemical reactions in a pursuit to achieve industrial viability for OCM. Here, in general, OCM suffers from low C 2 selectivity, yield and reactor temperature runaways due to highly exothermic nature of its reactions. Computational Fluid Dynamics (CFD) tools help analyze spatial gradients within the reactor to deeply understand the diffusion of species, mass and heat transfer phenomena. Furthermore, challenges associated with scaling up such as hot spot formation and parametric sensitivity can be addressed without having to expend on costly experiments. The current paper presents a multiscale packed-bed reactor CFD model coupled with a chemical kinetic model for the chemical looping OCM. The CFD model includes two scales i.e., macroscale for catalyst bed and microscale for individual pellets. Moreover, a chemical kinetic model based on 10 gas-phase reactions is integrated with the CFD model. An additional surface reaction for the formation of gas-phase oxygen from catalyst surface is added to account for the absence of feed oxygen. The model is calibrated against experimental results. The calibrated model captures trends in CH 4 conversion, C 2 selectivity and C 2 yield within a ± 4.35 % range across a temperature range of 700-900 °C. Moreover, model fidelity is evaluated by varying key computational parameters such as mesh resolution and time step size. The model is also verified by varying the inlet methane concentration and the gas hourly space velocity (GHSV) and comparing the results with literature. A sensitivity analysis and scale-up of the current model is undergoing.

Chemical looping↗

DOE OSTI2025

A molecular conveyor belt-associated protein controls the rotational direction of the bacterial type 9 secretion system

ABSTRACT Many bacteria utilize the type 9 secretion system (T9SS) for gliding motility, surface colonization, and pathogenesis. This dual-function motor supports both gliding motility and protein secretion, where rotation of the T9SS plays a central role. Fueled by the energy of the stored proton motive force and transmitted through the torque of membrane-anchored stator units, the rotary T9SS propels an adhesin-coated conveyor belt along the bacterial outer membrane like a molecular snowmobile, thereby enabling gliding motion. However, the mechanisms controlling the rotational direction and gliding motility of T9SS remain elusive. Shedding light on this mechanism, we find that in the gliding bacteriumFlavobacterium johnsoniae, deletion of the C-terminus of the conveyor belt-associated protein GldJ controls and, in fact, reverses the rotational direction of T9SS from counterclockwise (CCW) to clockwise (CW). This suggests that the interface between the conveyor belt-associated protein GldJ and the T9SS ring protein GldK plays an important role in controlling the directionality of T9SS, potentially by modulating its interaction with the stator complex GldLM, which drives motor rotation. Combined with MD simulation of the T9SS stator units GldLM, we suggest a “tri-component gearset” model where GldJ controls the rotational direction of its driver, the T9SS, thus providing adaptive sensory feedback to influence the motility of the gliding bacterium. IMPORTANCE The type 9 secretion system (T9SS) is fundamental to bacterial gliding motility, pathogenesis, and surface colonization. Our findings reveal that the C-terminal region of the conveyor belt-associated protein GldJ functions as a molecular switch which is capable of reversing the rotational direction of T9SS. Through the coordinated actions of the T9SS stator units (akin to a driving motor), the GldK ring (the gear that converts rotational energy into linear movement), and GldJ, this machinery forms a smart conveyor belt system reminiscent of flexible or cognitive mechanical conveyors. Such advanced conveyors can alter their direction to adapt to shifting demands. Here, we show that the bacterial T9SS similarly adjusts its rotational bias based on feedback from the conveyor belt-associated protein GldJ. This dual-role feedback mechanism underscores an evolved, controllable biological snowmobile, offering new avenues for studying how bacteria fine-tune motility in dynamic environments.

Microbiology↗

DOE OSTI2025

Wettability of Two-Dimensional Carbon Allotropes from Molecular Simulations

Force-field Monte Carlo and Molecular Dynamics simulations are used to compare wetting behaviors of model carbon sheets mimicking neat graphene, its saturated derivative, graphane, and related planar allotropes penta-graphene, γ-graphyne, and ψ-graphene in contact with aqueous droplets or an aqueous film confined between parallel carbon sheets. Atomistic and area-integrated surface/water potentials are found to be essentially equivalent in capturing moderate differences between the wetting free energies of tested substrates. Despite notable differences in mechanical and electric properties of distinct allotropes, the predicted allotrope/water contact angles span a narrow window of weakly hydrophilic values. Contact angles in the range of 80 ± 10° indicate modest hydration repulsion incapable of competing with van der Waals attraction between carbon particles. Poor dispersibility in neat water is hence a common feature of studied materials.

Biochemistry & Molecular Biology↗

DOE OSTI2026

Chronology of ungrouped achondrites Northwest Africa 11119 and 7325/8486: implications for early evolution of a heterogeneous crust on a differentiated planetesimal

The chronology of ungrouped achondrites provides key insights into the timeline of igneous activity in the early Solar System. Two ungrouped achondrites – Northwest Africa (NWA) 11119 (andesite-dacite) and NWA 8486 and its pair NWA 7325 (olivine gabbro) – are the focus of this study, where their chronologies are investigated using multiple high-resolution techniques. Here we report the lead-lead (207Pb-206Pb) and manganese-chromium (53Mn-53Cr) systematics of NWA 11119, as well as the 207Pb-206Pb systematics of NWA 8486 alongside aluminum-magnesium (26Al-26Mg) systematics for NWA 7325. The U-corrected 207Pb-206Pb ages of NWA 11119 and the combined ages of NWA 7325/8486 are 4566.4 ± 0.8 Ma and 4563.8 ± 1.9 Ma, respectively. Additionally, we report the 53Mn-53Cr age of NWA 11119 to be 4564.4 ± 2.5 Ma and the 26Al-26Mg age of NWA 7325/8486 to be 4563.1 ± 0.3 Ma. The formation of NWA 11119 requires partial melting of a (likely chondritic) source reservoir leading to eruption of Si rich, alkali depleted magmas, while NWA 7325/8486 likely formed from a chemically fractionated reservoir with superchondritic Al/Mg. The clear geochemical and isotopic similarities of these achondrites, combined with the chronology reported here, is suggestive of formation of these two ungrouped achondrites on a common parent body which likely formed in the inner Solar System and experienced early differentiation under reducing conditions. If these achondrites did share a parent body, it would suggest that primary asteroids in the early Solar System commonly produced mineralogically and geochemically heterogeneous crusts. While mineralogical and geochemical heterogeneity is known to exist in the (mostly mafic) crust of asteroid Vesta, our findings show that even more significant crustal heterogeneity (representing felsic and mafic compositions) may exist on other asteroids.

Cartwright, Julia [University of Leicester, UK]↗

DOE OSTI2026

Qualifying LaBr3:Ce+Sr detector performance for the Mu2e experiment at Fermilab Using the ELBE Accelerator

A LaBr3:Ce+Sr detector will be used to measure the stopped muon captures at the Mu2e experiment at Fermilab. It has been benchmarked in a test beam experiment performed at the ELBE electron accelerator located at the Helmholtz-Zentrum Dresden-Rossendorf, Germany. ELBE’s pulsed bremsstrahlung beam line was set to deliver an average γ -ray energy of between 4–5 MeV. The detector response was mapped to match Mu2e beam conditions, including rates up to 1 Mcps, energy flux, and time structure. A radioactive calibration source was used to mimic the characteristic 1808.7 keV γ -ray, emitted during the atomic muon nuclear capture in the Mu2e aluminum stopping target. The detector energy resolution was measured as a function of the average energy flux: up to 1 TeV/s for 0.34 s, the steady-operation beam-on time and up to 4 TeV/s for 5 ms to get a conservative estimate of the effect of high intensity Mu2e beam fluctuations. The PMT gain variation as a function of the beam spill length and average intensity has been parametrized and corrected for. When a PMT gain correction corresponding to the average beam-spill intensity is applied, the residual effect of beam intensity fluctuations around the average degrades the energy resolution, σ E γ /E γ , at 1808.7 keV from 0.66% to 0.83%.

Huang, Shihua [Purdue U., West Lafayette]↗

DOE OSTI2025

Selective Binding and Light-Driven Release of Fluorous PF 6 – and Radioactive 99 TcO 4 – Anions for All-to-Nothing Liquid–Liquid Extraction

The removal of anions from aqueous media using molecular receptors in liquid–liquid extraction is a long-standing strategy to clean up contaminated water sources. Therein, high selectivity is needed to remove specific ions from mixtures of other ions, and high affinity provides extractions at low concentrations. However, the high affinity creates a conundrum by impeding the release of the ions in any stripping steps needed for further processing. To circumvent this problem, light-responsive receptors have been proposed as candidates for turning off the binding, but they are currently untested in liquid–liquid extraction. We tested the feasibility of light-driven release using a cyanostar macrocycle. We demonstrate the selective extraction of PF$^{–}_{6}$ anions over large excesses of competing anions (Cl – , NO$^{–}_{3}$, SO$^{2–}_{4}$) followed by photodriven release for quantitative isolation of the target. Release relies on photoisomerization of the macrocycle’s five stilbenes generating distorted isomers to turn off binding. With modest reversibility, only a single-shot release was demonstrated, akin to photodriven uncaging. These methods were extended to the capture and photodriven release of ReO$^{–}_{4}$ and radioactive 99 TcO$^{–}_{4}$ anions at ∼90% efficiency. Extraction was demonstrated down to the highly dilute 4 ppb levels of the 99 TcO$^{–}_{4}$ anion. Furthermore, this proof-of-concept demonstration verifies the use of a large change in affinity for the all-to-nothing capture and release of target anions between liquid phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Working Fluid Characterization and Performance Assessment of Subcritical Organic Rankine Cycles Based on the Lee–Kesler Approach for Energy Recovery

Here, a generalized model using the Lee–Kesler approach based on the corresponding states principle is developed to assess the performance of subcritical Organic Rankine Cycles operating with different working fluids. Each fluid is characterized by five parameters: the acentric factor, critical temperature, critical pressure, molar mass, and the ideal-gas ratio of specific heats at the critical temperature. The model was developed using the compressibility factor modified version of the Benedict–Webb–Rubin equation proposed by Lee and Kesler and the enthalpy and entropy functions to calculate thermodynamic state properties. The model was validated by comparing the results calculated with the model and working fluid thermodynamic properties obtained with the CoolProp database. This comparison was conducted for 91 working fluids, obtaining a relative error below 5% for 88 out of the 91 fluids (∼97%). A generalized parametric study was conducted to determine the influence of the pinch point and each fluid parameter on the performance of Organic Rankine Cycle (ORC) systems. It was found that efficiency increases with critical temperature, ideal-gas ratio of specific heats at the critical temperature, and acentric factor, reaching up to 13%. The developed model enables the evaluation of ORC system performance for existing working fluids. It also allows the formulation and evaluation of new fluids to enhance the performance of the ORC while retrieving energy from any kind of source; and likewise, the methodology can be applied to other power generation cycles.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Development of large-scale, 3D Printed high temperature ceramic material

Through this collaborative effort, a new 3D printing platform for ceramics called laser-induced slip casting (LIS) was explored and developed for improving the processing and manufacture of silicon carbide (SiC), a high temperature ceramic material. This method prints layers of ceramic slips/slurries with subsequent selective-laser heating to dry each layer to build a 3D structure. The completed and dried part is then sintered. This manufacturing process is inherently lower cost than alternative ceramic printing methods such as binder jet technology or stereolithography when it comes to the feedstock material but is more expensive than robocasting or direct ink writing. However, it has the potential to make more controlled parts with less defects compared to robocasting. The largest cost is the heating source for the printer. With this technique, there is potential to make large ceramic parts in a near-net shape. Further, there is no known commercial manufacturing of 3D printed ceramics that creates a large range of different high-density ceramics at large scale. The goals and outcomes for the development of the new printing technology were: 1) assessing the technology with alumina by characterizing coupons, 2) printing and sintering of silicon carbide (SiC), and 3) characterization and properties testing of materials printed and a scale-up of SiC part(s). Through this collaborative project, it was sought to provide the best solution to achieving highly dense and near-net shaped ceramic parts at large scale and reduced cost. The goal was to produce high density sintered materials for applications in defense, energy generating systems, armor, and wear parts using 3D printing methods. Variables including powder particle sizes, dispersant molecular weights (MWs), binders, printing parameters, and post processing were explored as well as the characterization of the physical properties (add specifics here).

36 MATERIALS SCIENCE↗

DOE OSTI2024

Converting Second‐Order Saddle Points to Transition States: New Principles for the Design of 4π Photoswitches

Abstract Molecular photoswitches have demonstrated potential for storing solar energy at the molecular level, with power densities comparable to commercial batteries and hydroelectric energy storage. However, development of efficient photoswitches is hindered by limitations in cyclability and optical properties of existing materials. We here demonstrate that certain limitations in photoswitches based on electrocyclizations stem from the issue of controlling competition between Woodward‐Hoffmann allowed and forbidden pathways. Our approach moves beyond the traditional view of activation barriers and reveals that second‐order saddle points are crucial in dictating the competition between disrotatory and conrotatory pathways. These insights suggest new opportunities to manipulate the competition between these pathways through geometric constraints, fundamentally altering the connectivity of the potential energy surface. Our study also emphasizes the necessity of multi‐reference methods and the need to conduct higher‐dimensional explorations for competing pathways beyond photoswitch design.

Chemistry↗

DOE OSTI2023

The brighter-fatter effect in the JWST MIRI Si:As IBC detectors: I. Observations, impact on science, and modeling

Context.The Mid-Infrared Instrument (MIRI) on board theJames WebbSpace Telescope (JWST) uses three Si:As impurity band conduction (IBC) detector arrays. The output voltage level of each MIRI detector pixel is digitally recorded by sampling up the ramp. For uniform or low-contrast illumination, the pixel ramps become nonlinear in a predictable way, but in areas of high contrast, the nonlinearity curve becomes much more complex. The origin of the effect is poorly understood and currently not calibrated out of the data. Aims.We provide observational evidence of the brighter-fatter effect (BFE) in MIRI conventional and high-contrast coronagraphic imaging, low-resolution spectroscopy, and medium-resolution spectroscopy data, and we investigate the physical mechanism that gives rise to the effect on the MIRI detector pixel raw voltage integration ramps. Methods.We used public data from the JWST/MIRI commissioning and Cycle 1 phase. We also developed a numerical electrostatic model of the MIRI detectors using a modified version of the publicPoisson_CCDcode. Results.We find that the physical mechanism behind the BFE manifesting in MIRI data is fundamentally different to that of charge-coupled devices and photodiode arrays such as the Hawaii-XRG near-infrared detectors used by the NIRISS, NIRCam, and NIRSpec instruments on board JWST. Observationally, the BFE makes the JWST MIRI data yield 10–25% larger point sources and spectral line profiles as a function of the relative level of de-biasing of neighboring detector pixels. This broadening impacts the MIRI absolute flux calibration, time-series observations of faint companions, and point spread function modeling and subtraction. We also find that the intra-pixel 2D profile of the shrinking Si:As IBC detector depletion region directly impacts the accuracy of the pixel ramp nonlinearity calibration model.

Astronomy & Astrophysics↗

DOE OSTI2026

Dynamic Interfacial Design in Adaptive Hybrid Materials Enables Reversible and Tunable Mechano-Optic Smart Responses

Next-generation polymeric materials are shifting toward adaptive and interactive behaviors of living systems; however, designing materials that can reversibly modulate optical properties under mechanical deformation while maintaining mechanical robustness remains a key challenge. Here, we report a mechanically robust vitrimer-based adaptive hybrid material (AHM) that exhibits a stretch-induced reversible transparency-to-opacity transition, enabled by the integration of dynamic interactions at the polymer–silica nanoparticle interface and controlled nanoparticle self-assembly. The AHM combines boronic ester–functionalized polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (S-Bpin) with diol-functionalized silica nanoparticles (diol-SiNPs) to form a hybrid network hosting both dynamic boronic ester and hydrogen-bonding interactions. These reversible linkages facilitate controlled nanoparticle self-assembly and enable strain-induced nanoparticle alignment/aggregation. Upon stretching, SiNP-rich domains align and aggregate within the polymer matrix, while local modulus mismatch between stiff aggregated SiNP/borylated-styrene-rich regions and the softer elastomeric midblock induces surface microwrinkle formation. These internal aggregates and surface wrinkles cooperatively enhance light scattering, producing the opaque state under strain. Furthermore, the tailored AHM exhibits high toughness, thermomechanical stability, reprocessability, and programmable shape-memory behavior. This work presents a dynamic interfacial design strategy for mechanically robust, optically reconfigurable, and reusable soft materials for adaptive optics, smart windows, sensing, soft robotics, and circular smart-material platforms.

adaptive hybrid materials↗

DOE OSTI2023

Long‐Life Lithium‐Metal Batteries with an Ultra‐High‐Nickel Cathode and Electrolytes with Bi‐Anion Activity

Abstract Anion chemistry in electrolytes can greatly dictate the nature and quality of passivation layers on both cathode and anode surfaces. This will be more significant when it comes to highly reactive Li‐metal anode and aggressive high‐nickel cathodes. Herein, a competitive bi‐anion activity is found in electrolytes with the co‐existence of two anions, which leads to a controlled Li‐salt decomposition kinetics and entirely favorable interphasial chemistry on both Li‐metal anode and ultrahigh‐nickel cathode. The proposed bi‐anion localized high‐concentration electrolytes are demonstrated to exhibit superior electrochemical compatibility toward Li metal and long‐term cycling stabilities under both 4.4 and 4.6 V in Li‐metal batteries with ultrahigh‐nickel cathode. This study sheds fresh light on dendrite‐free Li‐metal anodes and provides guidance to achieve high‐energy‐density batteries.

Chemistry↗

DOE OSTI2026

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an↗

DOE OSTI2023

Impact of Limited Degree of Freedom Drag Coefficients on a Floating Offshore Wind Turbine Simulation

The worldwide effort to design and commission floating offshore wind turbines (FOWT) is motivating the need for reliable numerical models that adequately represent their physical behavior under realistic sea states. However, properly representing the hydrodynamic quadratic damping for FOWT remains uncertain, because of its dependency on the choice of drag coefficients (dimensionless or not). It is hypothesized that the limited degree of freedom (DoF) drag coefficient formulation that uses only translational drag coefficients causes mischaracterization of the rotational DoF drag, leading to underestimation of FOWT global loads, such as tower base fore-aft shear. To address these hydrodynamic modeling uncertainties, different quadratic drag models implemented in the open-source mid-fidelity simulation tool, OpenFAST, were investigated and compared with the experimental data from the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project. The tower base fore-aft shear and up-wave mooring line tension were compared under an irregular wave loading condition to demonstrate the effects of the different damping models. Two types of hydrodynamic quadratic drag formulations were considered: (1) member-based dimensionless drag coefficients applied only at the translational DoF (namely limited-DoF drag model) and (2) quadratic drag matrix model (in dimensional form). Based on the results, the former consistently underestimated the 95th percentile peak loads and spectral responses when compared to the OC5 experimental data. In contrast, the drag matrix models reduced errors in estimates of the tower base shear peak load by 7–10% compared to the limited-DoF drag model. The underestimation in the tower base fore-aft shear was thus inferred be related to mischaracterization of the rotational pitch drag and the heave motion/drag by the limited-DoF model.

17 WIND ENERGY↗