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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Controlling protein adsorption modes electrostatically

Protein adsorption on surfaces is ubiquitous in biology and in biotechnology. There are various forces required for controlling protein adsorption. Here, we introduce an explicit ion coarse-grained molecular dynamics simulation approach for studying the effects of electrostatics on protein adsorption, and 2D protein assembly on charged surfaces. Our model accounts for the spatial distribution of protein charges. We use catalase as our model protein. We find that the preferential adsorption mode of proteins at low protein concentration on a charged surface is “standing up”. When the protein concentration in a solution increases to reach a critical density on the surface, the adsorption mode switches from “standing up” to a mixed state “flat on” and “standing up”, which increases the lateral correlations among the adsorbed proteins. As such, the changes in the adsorption mode arise from the protein adsorption that cancel the surface charge and the protein–protein repulsion. This correlated surface structure melts as the salt concentration increases because the charged surface is cancelled by the salt ions and the proteins de-adsorb. For the case of strongly charged surfaces the “standing up” conformation remains more favorable even at high protein adsorption at low salt concentrations since in that conformation the surface charge is cancelled more effectively, generating an even more laterally correlated structure. We elucidate the effects of parameters such as surface charge density, salt concentration, and protein charges on the different adsorption modes and the structure and organization of proteins on the charged surfaces. Finally, this study provides a guide for controlling protein assembly on surfaces.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Improvements to the Modeling of the TREAT Reactor and Experiments

This paper summarizes the latest improvements and lessons learned from the modeling and simulation of the transient test reactor at Idaho National Laboratory using the MAM- MOTH reactor physics application. MAMMOTH is a MOOSE-based, Finite Element Method application that specializes in the analysis of the spatial dynamics behavior of nuclear reactors. Since early 2018 several transient tests have been conducted at TREAT, thus providing the opportunity to apply and benchmark modern modeling and simulation tools. MAMMOTH was used to provide predictions of the power coupling factor between the core and the experiment for various experiments. Even though the power coupling factor predictions agree very well with the experimental data, within the bounds of the experimental uncertainty, one shortcoming was the underprediction of the total energy deposited in the core and in the experiment. Determination of the sources for this discrepancy are ongoing, but several key problems have been identified and resolved, thus providing valuable insights for future research. This paper discusses several of these lessons learned. First, the heat capacity data for the TREAT fuel has some significant problems due to limitations of the measurement techniques used circa 1960s. The sensitivity of the peak power and the total energy deposition to various representations of the heat capacity is approximately 5%. Second, the effects of the biological shield and thermal column on the modeling of the core are non-negligible, since they affect the mean generation time and the effective reflection of neutrons back into the core, which is suspected to be important during the core heat up. Matching the reactor period resolves the fact that the reduced spatial domain used in the MAMMOTH model underpredicts the mean generation time. The neutron reflection from these regions is marginally improved with the use of an albedo boundary condition. Third, modeling of the control rod movement with a multi-scheme method is introduced and its current limitations are exposed. Fourth, we explore the effects of using a homogenized model with Superhomogenization equivalence and how that differs from fully heterogeneous simulations. Finally, the energy condensation effects for this graphite core are significant. Solutions with 10 and 26 energy groups show the benefits of using a finer coarse group structure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Optimization of WAAM Process to Produce AUSC Components with Increased Service Life

Additive manufacturing has the potential to revolutionize industrial hardware and unlock efficiency gains through the fabrication of geometries and architectures not possible by conventional processing. Wire Arc Additive manufacturing (WAAM) process is a class of directed energy deposition process enabling higher build rate and allowing custom wire feedstock allowing spatial variation of microstructure. The larger spot size and lower speed creates a larger melt pool, reducing residual stress and often time creating directional/columnar microstructure for Ni-superalloy. The use of flexible platform provides freedom in deposition strategy, which can accommodate complex substrates, including feature addition onto existing structures, non-flat layers, and repair methods. However, the certification of the final component needs to match the strength requirement. Hence, the quality of the component produced is stringently monitored to avoid buildup of residual stress, cracks, porosity and to reduce detrimental segregated phases commonly observed during alloy solidification. Simulation plays a huge role in predicting the melt pool dimension and can be used to optimize the process parameter. Similar development is also required to perform physics-based modeling of microstructural development in WAAM that can predict the microstructural features during solidification and can be used to optimize the process more effectively. To move toward this goal, Raytheon Technologies Research Center together with Siemens worked to create a set of computational tools to control the process parameters, enable on-line measurements and acquisition with feedback to the optimized process parameters, and eventually track material evolution through each step of the additive process. Computational fluid dynamics is used for accurate prediction and calibration of the thermal field during WAAM process. and phase field models for microstructure evolution as a function of processing parameters to establish a connection between additive parameters and the final microstructure. Here we report cellular automata (CA) model development to predict the dendritic microstructure evolution with surface and bulk nuclei for single track and multiple layers. The CA model was developed to account for secondary element addition and predict segregation, local melting, and latent heat release as well as prediction of Euler angles from orientation information and validated against experiments. This framework was utilized to tailor spatially-varying composition in a part by appropriately controlling the microstructure evolution during the additive process. Functionally graded Haynes 282 alloy with high Cr content at the surface was tested for oxidation and mechanical properties. An advanced physics-based reaction-diffusion model predicting the simultaneous creation of chromium oxide and alumina is developed and validated to extend life expectancy of the WAAM manufactured high temperature part. A machine-learning data-driven framework establishing the process-structure relationship from a dataset of real microstructure images and corresponding process history data has been developed and implemented in the NX Siemens design system. The digital twin configuration along with the tool path generation enabled prediction of WAAM component buildup time and the techno-economic analysis provided a favorable option for all 4 cases with 15-40% cost reduction.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Nonlinear Nano‐Imaging of Interlayer Coupling in 2D Graphene‐Semiconductor Heterostructures

The emergent electronic, spin, and other quantum properties of 2D heterostructures of graphene and transition metal dichalcogenides are controlled by the underlying interlayer coupling and associated charge and energy transfer dynamics. However, these processes are sensitive to interlayer distance and crystallographic orientation, which are in turn affected by defects, grain boundaries, or other nanoscale heterogeneities. This obfuscates the distinction between interlayer charge and energy transfer. Here, nanoscale imaging in coherent four‐wave mixing (FWM) and incoherent two‐photon photoluminescence (2PPL) is combined with a tip distance‐dependent coupled rate equation model to resolve the underlying intra‐ and inter‐layer dynamics while avoiding the influence of structural heterogeneities in mono‐ to multi‐layer graphene/WSe 2 heterostructures. With selective insertion of hBN spacer layers, it is shown that energy, as opposed to charge transfer, dominates the interlayer‐coupled optical response. From the distinct nano‐FWM and ‐2PPL tip‐sample distance‐dependent modification of interlayer and intralayer relaxation by tip‐induced enhancement and quenching, an interlayer energy transfer time of τ ET ≈ ( 0 . 35 − 0.15 + 0.65 ) $\tau _{\rm ET} \approx (0.35^{+0.65}_{-0.15})$ ps consistent with recent reports is derived. As a local probe technique, this approach highlights the ability to determine intrinsic sample properties even in the presence of large sample heterogeneity.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Calibration, measurement, and characterization of soil moisture dynamics in a central Amazonian tropical forest

Soil moisture plays a key role in hydrological, biogeochemical, and energy budgets of terrestrial ecosystems. Accurate soil moisture measurements in remote ecosystems such as the Amazon are difficult and limited because of logistical constraints. Time domain reflectometry (TDR) sensors are widely used to monitor soil moisture and require calibration to convert the TDR's dielectric permittivity measurement (K a ) to volumetric water content (θ v ). In this study, our objectives were to develop a field-based calibration of TDR sensors in an old-growth upland forest in the central Amazon, to evaluate the performance of the calibration, and then to apply the calibration to determine the dynamics of soil moisture content within a 14.2 -m-deep vertical soil profile. Depth-specific TDR calibration using local soils in a controlled laboratory setting yielded a novel K a –θ v third-degree polynomial calibration. The sensors were later installed to their specific calibration depth in a 14.2-m pit. The widely used K a –θ v relationship (Topp model) underestimated the site-specific θ v by 22–42%, indicating significant error in the model when applied to these well-structured, clay-rich tropical forest soils. The calibrated wet- and dry-season θ v data showed a variety of depth and temporal variations highlighting the importance of soil textural differentiation, root uptake depths, as well as event to seasonal precipitation effects. Data such as these are greatly needed for improving our understanding of ecohydrological processes within tropical forests and for improving models of these systems in the face of changing environmental conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Real-Time In Situ Observation of CsPbBr 3 Perovskite Nanoplatelets Transforming into Nanosheets

The manipulation of nano-objects through heating is an effective strategy for inducing structural modifications and therefore changing the optoelectronic properties of semiconducting materials. Despite its potential, the underlying mechanism of the structural transformations remains elusive, largely due to the challenges associated with their in situ observations. To address these issues, we synthesize temperature-sensitive CsPbBr 3 perovskite nanoplatelets and investigate their structural evolution at the nanoscale using in situ heating transmission electron microscopy. We observe the morphological changes that start from the self-assembly of the nanoplatelets into ribbons on a substrate. We identify several paths of merging nanoplates within ribbons that ultimately lead to the formation of nanosheets dispersed randomly on the substrate. These observations are supported by molecular dynamics simulations. We correlate the various paths for merging to the random orientation of the initial ribbons along with the ligand mobility (especially from the edges of the nanoplatelets). This leads to the preferential growth of individual nanosheets and the merging of neighboring ones. These processes enable the creation of structures with tunable emission, ranging from blue to green, all from a single material. Our real-time observations of the transformation of perovskite 2D nanocrystals reveal a route to achieve large-area nanosheets by controlling the initial orientation of the self-assembled objects with potential for large-scale applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Contrasting Responses of Soil Inorganic Carbon to Afforestation in Acidic Versus Alkaline Soils

Afforestation is recommended as an effective approach for carbon sequestration and environmental benefits. However, it remains less clear, and sometimes controversial, regarding how afforestation may impact soil inorganic carbon (SIC), a crucial component of the ecosystem carbon pool. Here, using field data from 619 afforested plots and 163 control plots across northern China, we investigated the relative and absolute differences in SIC between afforested and corresponding control plots. Our results suggested that afforestation increased SIC in acidic soils, while decreased SIC in alkaline soils. Fitting a linear mixed model and further a structure equation model, we found that afforestation-induced soil pH change was the most significant factor regulating SIC responses. In particular, SIC was more sensitive to pH change in more arid areas, where both soil pH and SIC stocks were high. Other factors could indirectly affect SIC responses to afforestation through modulating soil pH and soil organic carbon (SOC) dynamics. Moreover, afforestation-induced SIC changes also varied considerably among different species of tree plantations and across different soil depths. Importantly, in plantations of Pinus sylvestris var. mongholica, Pinus tabuliformis, and Populus spp., changes in SIC caused by afforestation were even comparable to that in SOC. Overall, our findings provide a data-based understanding on the comprehensive soil carbon dynamics following afforestation and its underlying mechanisms. With the increased use of afforestation and reforestation as nature-based solutions to climate change, their associated impacts on SIC need to be taken into account, especially in SIC-rich areas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Hydrogen in disordered titania: connecting local chemistry, structure, and stoichiometry through accelerated exploration

Hydrogen incorporation in native surface oxides of metal alloys often controls the onset of metal hydriding, with implications for materials corrosion and hydrogen storage. A key representative example is titania, which forms as a passivating layer on a variety of titanium alloys for structural and functional applications. These oxides tend to be structurally diverse, featuring polymorphic phases, grain boundaries, and amorphous regions that generate a disparate set of unique local environments for hydrogen. Here, we introduce a workflow that can efficiently and accurately navigate this complexity. First, a machine learning force field, trained on ab initio molecular dynamics simulations, was used to generate amorphous configurations. Density functional theory calculations were then performed on these structures to identify local oxygen environments, which were compared against experimental observations. Second, to classify subtle differences across the disordered configuration space, we employ a graph-based sampling procedure. Finally, local hydrogen binding energies and hopping kinetics are computed using exhaustive density functional theory calculations on representative configurations. Here, we leverage this methodology to show that hydrogen binding energetics are described by local oxygen coordination, which in turn is affected by stoichiometry, and form the basis of hopping kinetics and diffusion. Together these results imply that hydrogen incorporation and transport in TiO x can be tailored through compositional engineering, with implications for improving the performance and durability of titanium-derived alloys in hydrogen environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Out of the Lab: 3D Printing on Non-Ideal Surfaces

In this work, coaxial direct ink writing is utilized to print sensitive or encapsulated materials onto heterogeneous and rough substrates. By enclosing the core fluid within a rigid ceramic shell, continuity is maintained even when printing on substrates traditionally considered challenging. This work presents the development of a coaxial ceramic direct ink writing system and investigates co-flow dynamics through microfluidic principles. A specially designed coaxial nozzle enables the co-extrusion of an alumina shell, with indium-tin-oxide inks serving as the core material. This approach allows the fabrication of core-shell ceramic structures suitable for future high-temperature applications on rough surfaces. The colloidal inks are tailored to achieve the necessary rheological properties and sintering performance. Additionally, flow simulations, guided by microfluidic co-flow principles, are employed to define the processing parameters for coaxial printing, ensuring precise control over the core-shell architectures. Physical modeling is further applied to study core deformation and eccentricity. These simulations are experimentally validated, supporting the successful deposition of coaxial ceramic features on heterogeneous, high-temperature ceramic substrates.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Extended anharmonic collapse of phonon dispersions in SnS and SnSe

The lattice dynamics and high-temperature structural transition in SnS and SnSe are investigated via inelastic neutron scattering, high-resolution Raman spectroscopy and anharmonic first-principles simulations. We uncover a spectacular, extreme softening and reconstruction of an entire manifold of low-energy acoustic and optic branches across a structural transition, reflecting strong directionality in bonding strength and anharmonicity. Further, our results solve a prior controversy by revealing the soft-mode mechanism of the phase transition that impacts thermal transport and thermoelectric efficiency. Our simulations of anharmonic phonon renormalization go beyond low-order perturbation theory and capture these striking effects, showing that the large phonon shifts directly affect the thermal conductivity by altering both the phonon scattering phase space and the group velocities. These results provide a detailed microscopic understanding of phase stability and thermal transport in technologically important materials, providing further insights on ways to control phonon propagation in thermoelectrics, photovoltaics, and other materials requiring thermal management.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Spectral widths and Stokes shifts in InP-based quantum dots

InP-based quantum dots (QDs) have Stokes shifts and photoluminescence (PL) line widths that are larger than in II–VI semiconductor QDs with comparable exciton energies. The mechanisms responsible for these spectral characteristics are investigated in this paper. Upon comparing different semiconductors, we find the Stokes shift decreases in the following order: InP > CdTe > CdSe. We also find that the Stokes shift decreases with core size and decreases upon deposition of a ZnSe shell. We suggest that the Stokes shift is largely due to different absorption and luminescent states in the angular momentum fine structure. The energy difference between the fine structure levels, and hence the Stokes shifts, are controlled by the electron–hole exchange interaction. Luminescence polarization results are reported and are consistent with this assignment. Spectral widths are controlled by the extent of homogeneous and inhomogeneous broadening. Here, we report PL and PL excitation (PLE) spectra that facilitate assessing the roles of homogeneous and different inhomogeneous broadening mechanisms in the spectra of zinc-treated InP and InP/ZnSe/ZnS particles. There are two distinct types of inhomogeneous broadening: size inhomogeneity and core–shell interface inhomogeneity. The latter results in a distribution of core–shell band offsets and is caused by interfacial dipoles associated with In–Se or P–Zn bonding. Quantitative modeling of the spectra shows that the offset inhomogeneity is comparable to but somewhat smaller than the size inhomogeneity. The combination of these two types of inhomogeneity also explains several aspects of reversible hole trapping dynamics involving localized In 3+ /V Zn 2– impurity states in the ZnSe shells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Understanding the dynamic nature of plant lipid anabolic and catabolic metabolism is key to sustainable oilseed engineering

Plant-derived oils are essential sources of reduced carbon and various fatty acid (FA) structures for food, biofuels, and the oleochemical industry. Despite extensive efforts, engineering mainstream oilseed crops to produce high levels of industrially valuable unusual FAs (UFAs) remains challenging. This review synthesizes recent advances in the understanding of lipid metabolic networks, emphasizing how species-specific regulation of FA synthesis, activation, and delivery influences triacylglycerol (TAG) assembly to govern the efficiency of UFA accumulation. Key insights reveal that acyl flux through anabolic and catabolic branches of lipid metabolism is tightly controlled by enzyme substrate selectivities, diacylglycerol (DAG) pool compartmentalization, and metabolic context, including lipid remodeling and degradation pathways. Engineering success is often constrained by incompatibilities between UFA biosynthetic enzymes and endogenous host metabolism, leading to flux imbalances, futile cycles, and undesired phenotypes. We highlight emerging strategies to overcome these barriers, such as the use of UFA-selective acyltransferases, coordinated manipulation of DAG source pools, suppression of competing endogenous enzymes, and exploitation of TAG remodeling mechanisms. This integrated synthesis provides a conceptual framework for logic-based engineering of oilseeds with enhanced UFA content by offering new avenues for sustainable biomanufacturing of valuable lipids.

acyltransferase specificity↗
DOE OSTI2022

Model files for estimating snow dynamics and stable water isotopes across the East River, CO.

A coupled hydrologic and snowpack stable water isotope model is used to assesses controls on isotopic inputs across the East River, Colorado, a large, mountainous basin. The hydrologic model uses the semi-empirical, spatially distributed and publicly available U.S. Geological Survey numerical code Precipitation-Modelling Runoff System (PRMS). Water and energy are tracked daily through the atmosphere, canopy and subsurface at a 100-m grid resolution. The isotope mass balance model follows previous work by Ala-aho et al. (2017) to track stable isotopes entering the soil system as snowmelt or rain. Water stores and fluxes needed for the isotope model use hydrologic model output for each timestep and model modeled grid location. This data package provides all files related to the hydrologic model (executable, input and output files), the isotopic model calibration and the historic isotopic model (water years 2015-2020). The isotope model source code and executable are provided. The file "readme.txt" includes information on the file structure, steps to run the model, and description of included folders.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Time-Dependent Density Functional Theory Description of 238 U⁡(n,f), 240,242 Pu⁢(n,f), and 237 Np(n,f) Reactions

In nuclei with an odd nucleon number the nonvanishing spin number density is the source of a pseudomagnetic field, which favors the splitting of the nucleon Cooper pairs. Such a pseudomagnetic field is generated always in the dynamics of any nucleus, but its effects on Cooper pairs are significantly enhanced in the dynamic evolution of nuclei with an odd number of nucleons. We present for the first time a microscopic study of the induced fission of the odd neutron compound nuclei 239 U, 241,243 Pu, and the odd proton, odd neutron compound nucleus 238 Np, performed within the time-dependent density functional theory extended to superfluid fermion systems, without any simplifying assumptions, with controlled numerical approximations, and for a very large number of initial conditions. Because of the presence of the unpaired odd nucleon(s), the time-reversal symmetry of the fission compound nucleus is spontaneously broken, an aspect routinely neglected in the most advanced microscopic approaches of the past. The emerging fission fragment properties are quite similar to the properties of fission fragments of neighboring even-even nuclei. The time from saddle-to-scission is often significantly longer in odd-odd or odd-mass nuclei than for even-even nuclei, since systems with unpaired nucleons are easier to excite and the potential energy surfaces of these nuclei have more structure, often resembling a very complicated obstacle course, rather than a more direct evolution of the nuclear shape from the top of the outer fission barrier to the scission configuration. The Pauli blocking approximation, often invoked in the literature, expected to inhibit the fission of nuclei with unpaired nucleons, is surprisingly strongly violated during the fission dynamics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Influence of Cation Size on the Local Atomic Structure and Electronic Properties of Ta Perovskite Oxynitrides

Partial anion substitution in transition metal oxides provides rich opportunities to control and tune physical and chemical properties, for example, combining the merits of oxides and nitrides. In addition, the possibility of resulting anion sublattice order provides a means to target polar and chiral structures based on a wide array of accessible structural archetypes by design. Here, in this work, we investigate the local structures of a family of perovskite tantalum oxynitrides—ATaO 2 N (A = Ba, Sr, and Ca)—using a combination of experimental and theoretical approaches including neutron total scattering, density functional theory (DFT), and ab initio molecular dynamics (AIMD) simulations. We present the first experimental study of chemical short-range order (CSRO) in CaTaO 2 N, confirming local cis N ordering of the anion sub-lattice. Our systematic exploration of a local structure across the A cation size series (from the larger Ba to the smaller Ca) reveals a perovskite motif increasingly distorted with respect to long-range average structures. DFT and AIMD simulations support the observed trends. Overall, structures with cis ordering of the nitrogen anions in each TaO 4 N 2 octahedron are favored over those with trans ordering. With diminishing A cation size, local cis ordering and Ta off-centering play decreasing roles in overall lattice stability, overshadowed by the stabilizing effects of octahedral tilting. The influence of these factors on local dipole formation and frustrated dipole ordering are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

On-the-fly autonomous control of neutron diffraction via physics-informed Bayesian active learning

We demonstrate the first live, autonomous control over neutron diffraction experiments by developing and deploying ANDiE: the autonomous neutron diffraction explorer. Neutron scattering is a unique and versatile characterization technique for probing the magnetic structure and behavior of materials. However, instruments at neutron scattering facilities in the world is limited, and instruments at such facilities are perennially oversubscribed. We demonstrate a significant reduction in experimental time required for neutron diffraction experiments by implementation of autonomous navigation of measurement parameter space through machine learning. Prior scientific knowledge and Bayesian active learning are used to dynamically steer the sequence of measurements. We show that ANDiE can experimentally determine the magnetic ordering transition of both MnO and Fe 1.09 Te all while providing a fivefold enhancement in measurement efficiency. Furthermore, in a hypothesis testing post-processing step, ANDiE can determine transition behavior from a set of possible physical models. ANDiE's active learning approach is broadly applicable to a variety of neutron-based experiments and can open the door for neutron scattering as a tool of accelerated materials discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Do ambient shear and thermal stratification impact wind turbine tip-vortex breakdown?

Modern wind turbines experience uneven inflow conditions across the rotor, due to the ambient flow’s shear and thermal stratification. Such conditions alter the shape and length of turbine wakes and thus impact the loads and power generation of downstream turbines. To this end, understanding the spatial evolution of the individual wakes under different atmospheric conditions is key to controlling and optimising turbine arrays. With this numerical study we aim to obtain a better understanding of the fundamental physics governing the near-wake dynamics of wind turbines under shear and thermal stability, by examining their tip-vortex breakup mechanisms. Our approach considers scale-resolving simulations of a single turbine wake under a linear shear profile as well as the application of harmonic tip perturbations to trigger flow instabilities. For the subsequent analysis we use the proper orthogonal decomposition (POD) method to extract coherent structures from the flow, and we also calculate mean kinetic energy fluxes to quantify each coherent structure’s contribution to wake recovery. The wake’s helical spiral is found to hinder wake recovery for all studied ambient flow conditions, whereas the mutual inductance instability has positive MKE flux leading to an enhanced wake recovery. Finally, the ambient shear has the largest impact on the local MKE flux with respect to downstream location by changing the shape of the curve and location of extrema, whereas thermal stratification has only a minimal impact on the magnitude of the near-wake local MKE flux distribution.

17 WIND ENERGY↗
DOE OSTI2025

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↗