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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 199 records · Page 11

High Sulfur Loading and Capacity Retention in Bilayer Garnet Sulfurized‐Polyacrylonitrile/Lithium‐Metal Batteries with Gel Polymer Electrolytes

The cubic‐garnet (Li 7 La 3 Zr 2 O 12 , LLZO) lithium–sulfur battery shows great promise in the pursuit of achieving high energy densities. The sulfur used in the cathodes is abundant, inexpensive, and possesses high specific capacity. In addition, LLZO displays excellent chemical stability with Li metal; however, the instabilities in the sulfur cathode/LLZO interface can lead to performance degradation that limits the development of these batteries. Therefore, it is critical to resolve these interfacial challenges to achieve stable cycling. Here, an innovative gel polymer buffer layer to stabilize the sulfur cathode/LLZO interface is created. Employing a thin bilayer LLZO (dense/porous) architecture as a solid electrolyte and significantly high sulfur loading of 5.2 mg cm −2 , stable cycling is achieved with a high initial discharge capacity of 1542 mAh g −1 (discharge current density of 0.87 mA cm −2 ) and an average discharge capacity of 1218 mAh g −1 (discharge current density of 1.74 mA cm −2 ) with 80% capacity retention over 265 cycles, at room temperature (22 °C) and without applied pressure. Achieving such stability with high sulfur loading is a major step in the development of potentially commercial garnet lithium–sulfur batteries.

25 ENERGY STORAGE↗

Establishing a process-structure-property-performance framework for SLS additive manufacturing through integrated multiscale modeling

This study presents a comprehensive suite of high-fidelity computational models that integrate multiscale and multiphysics simulations to capture the full Selective Laser Sintering (SLS) additive manufacturing process—from initial melting and solidification to mechanical response under external loads. Process simulations are linked with mechanical analysis through Representative Volume Elements (RVEs), establishing a process-structure–property-performance framework. The interaction between laser light and polyamide 12 (PA12) powder is modeled, accounting for laser characteristics and the optical, thermal, and geometrical properties of the powder. The heat source is incorporated into a heat transfer model, coupled with crystallization kinetics and densification models to predict material density and crystallinity. The porosity distribution from the densification model and crystallinity interpolated from experimental data are used to construct the RVEs. A multi-mechanism constitutive model is then calibrated using mechanical tests to predict the stress–strain response. Simulation results show good agreement with experimental data in terms of porosity, crystallinity, and mechanical performance when sufficient laser power (62 W or higher) is used. This research supports the inverse design of 3D-printed structures by introducing a high-fidelity framework that combines multiscale and multiphysics modeling with experimental calibration for predictive and performance-driven additive manufacturing.

SLS↗

Linking structural and rheological memory in disordered soft materials

Linking the macroscopic flow properties and nanoscopic structure is a fundamental challenge to understanding, predicting, and designing disordered soft materials. Under small stresses, these materials are soft solids, while larger loads can lead to yielding and the acquisition of plastic strain, which adds complexity to the task. In this work, we connect the transient structure and rheological memory of a colloidal gel under cyclic shearing across a range of amplitudes via a generalized memory function using rheo-X-ray photon correlation spectroscopy (rheo-XPCS). Our rheo-XPCS data show that the nanometer scale aggregate-level structure recorrelates whenever the change in recoverable strain over some interval is zero. The macroscopic recoverable strain is therefore a measure of the nano-scale structural memory. We further show that yielding in disordered colloidal materials is strongly heterogeneous and that memories of prior deformation can exist even after the material has been subjected to flow.

Kamani, Krutarth M. [Univ. of Illinois at Urbana-C↗

Influence of Ordered Mesoporous Oxides in Plasma-Assisted Ammonia Synthesis

Widespread implementation of dielectric barrier discharge (DBD)-assisted NH 3 synthesis, a nascent technology operating under sustainable, ambient conditions, is hindered by low energy yields due to, in part, poor fundamental understanding. Porous oxides used to support metal nanoparticle catalysts have shown significant energy yield contributions for DBD-assisted NH 3 synthesis even without metal. Using an AC-powered, coaxial, single-stage reactor at 16 kV with equimolar (N 2 /H 2 ) feed, we measured NH 3 synthesis rates in the presence of different nonordered oxides, ordered SiO 2 structures (SBA-15 and MCM-41), and ordered Al-incorporated analogues (γ-Al 2 O 3 -coated with varying Al-loadings and Al-substitution, respectively: Al 2 O 3 -SBA-15 and Al-MCM-41). We systematically quantified NH 3 energy yield dependence on pore structures and material identities (i.e., ordered pores and Al incorporation) known to facilitate higher DBD-assisted NH 3 synthesis rates. SBA-15 displayed a higher steady-state energy yield than MCM-41, indicating that framework type is a crucial factor, with both ordered porous systems outperforming fumed SiO 2 . 10 wt % Al maximized in situ NH 3 uptake among the various Al loadings, exhibiting a higher steady-state energy yield and similar power to SBA-15. However, Al-MCM-41 had a similar steady-state energy yield and lower power than MCM-41, likely due to the extended γ-Al 2 O 3 surface that has a dielectric constant higher than that of SiO 2 . Both Al-incorporated analogues benefit from surface acid sites that can adsorb NH 3 in situ, resulting in higher overall NH 3 energy yields than that of their parent ordered SiO 2 . Al 2 O 3 -SBA-15 shielded more NH 3 than Al-MCM-41, likely due to a higher acid site density than the acid site identity. Furthermore, Al incorporation via γ-Al 2 O 3 coating more successfully improves the NH 3 energy yield; together with the high-performing ordered framework, these analogues are potential metal catalyst supports with promising energy yields for DBD-assisted synthesis of NH 3 and other chemicals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular origin of anisotropic shear elastoplasticity in chitin

Chitin nano- and mesoscale structures present in the exoskeleton of crustaceans exhibit exceptional longitudinal stiffness and toughness, rivaling or even exceeding that of many synthetic polymer architectures. Here, we reveal the origin of the asymmetric shear response in chitin multiscale architectures, marked by pronounced anisotropy in deformation. Under shear aligned with the molecular axis, chitin accommodates strain through coherent atomic rearrangements that enable elastic recovery. In contrast, shear applied perpendicular to this axis induces liquid-like plasticity via localized sliding. These results demonstrate the intrinsic mechanical anisotropy of chitin, underpinning a dual function in resisting repetitive loading while dissipating internal stress during high-strain events. Our findings establish the molecular basis of shear elastoplasticity in multiscale chitin structures, wherein axial elasticity supports energy storage in load-bearing regions, whereas transverse plasticity enables controlled energy dissipation. These atomic-scale insights lay a foundation for the predictive design of chitin-based materials with tunable strength-toughness profiles.

Wan, Zhangmin [University of British Columbia, Van↗

Evaluating Model Robustness for Defect Identification and Classification in a Composite Aerostructure Material

Aircraft structures are required to have a high level of quality to satisfy their need for light weight, efficient flight, and withstanding high loads over their lifespan. These aerostructures are typically made from a composite material due to their good tensile strength and resistance to compression. To ensure their structural integrity, the composite material requires inspection for common flaws such as porosity, delaminations, voids, foreign object debris, and other defects. Ultrasonic testing (UT) is a popular non-destructive inspection (NDI) technique used for effectively evaluating the composite material. Current inspection methods rely heavily on human experience and are extremely time consuming. Therefore, there is a need for the development of techniques to reduce the manual inspection time. This work compares the performance of different deep learning-based methods in the identification and classification of defects. Deep learning has shown great promise in numerous fields, and we show its effectiveness in the evaluation of the composite aerostructure material. The methods developed here are both highly reliable with a top recall value of 98.64% as well as extremely efficient requiring an average of 4 s during the inferencing stage to evaluate new composites. Lastly, we investigate model robustness to concept drift by measuring its performance over time.

36 MATERIALS SCIENCE↗

Backup power or bill savings? How electricity tariffs impact residential solar-plus-storage usage in the United States

Adoption of paired solar-plus-storage systems has accelerated in recent years, driven by both the demand for backup power and a desire to manage utility bills. Tradeoffs between those two uses can arise through the reserve setting on the battery storage system, which serves to maintain a minimum state of charge in case of a power interruption. Our paper applies an economic framework to evaluate this tradeoff in terms of changes in bill savings and customer reliability value across reserve levels, considering how those tradeoffs depend on the underlying electricity rate structure and levels. The analysis is based on a representative set of load profiles, solar profiles, tariff designs, and stochastic power interruption events across ten different regions in the United States. We find that the opportunity cost of holding storage capacity in reserve, in terms of foregone bill reductions, outweighs any gains in reliability value from mitigated power interruptions in the majority of customer situations. Higher storage reserve levels increase total customer value only in specific circumstances, such as for customers with inferior reliability (10x average interruptions), with a very high value of lost load ($50/kWh), and with tariff or interconnection rules that disallow grid charging. However, even this result is dampened when considering tariff designs with higher price differentials that increase the opportunity cost of holding storage in reserve (e.g. import/export or time-of-use rates). Allowing grid charging in tariffs essentially eliminates the necessity to hold any storage in reserve in all sensitivity cases explored.

Electric resilience↗

Active Sites in the Dealuminated Beta Zeolite-Supported Cobalt Catalyst for Non-Oxidative Ethane Dehydrogenation

Dispersed metal species in siliceous zeolites have been actively studied for non-oxidative dehydrogenation of ethane (NDE). Fundamental insights into the dynamics of metal species in zeolites under reaction conditions have rarely been explored. Herein, we report an atomic level understanding of the dynamics and activity of cobalt (Co) sites in dealuminated Beta zeolite (DeAl-BEA) for NDE during induction and reaction conditions with extensive characterization techniques such as diffuse reflectance UV–vis, solid state nuclear magnetic resonance and X-ray photoelectron, X-ray diffraction along with in situ Fourier transform infrared and X-ray absorption spectroscopy. For a catalyst with 0.5 mass % Co loading, tetrahedral Co 2+ mononuclear sites, di-coordinated to the zeolite framework and with two silanol groups in vicinity (i.e., (≡SiO) 2 Co(HO–Si≡) 2 ), form upon exposure to hydrogen during induction and persist through the NDE reaction. Increasing the Co loading to 3.0 mass % yielded Co sites with similar electronic and coordination structures but slightly elongated Co–O bonds. Upon cooling to room temperature, the Co sites persisted in the same coordination environment, though the disappearance of a feature in the Co K-edge near-edge region revealed changes in the active site’s electronic structure coinciding with modest shifts in bond lengths. The electronic structure and activity of (≡SiO) 2 Co(HO–Si≡) 2 sites were studied comparatively to a few other hypothetical Co 2+ coordination structures, using electronic structure calculations and microkinetic simulations. The simulations showed that NDE is controlled by β-hydride elimination following C–H bond activation and that Co-sites possessing flexibility because of neighboring silanol defects are more active. Interestingly, dinuclear Co–O–Co sites (i.e., (≡SiO)Co(HO–Si≡) 2 –O–(HO–Si≡) 2 Co(≡SiO)) were more active than the mononuclear (≡SiO) 2 Co(HO–Si≡) 2 sites because of favorable hydrogen bonding with the vicinal silanol groups. In conclusion, the present study bridges the gap between the knowledge acquired by ex-situ characterizations and the active sites under the reaction conditions in alkane dehydrogenation chemistry.

36 MATERIALS SCIENCE↗

Crack Propagation Modeling of a High-Speed Outer Rotor Motor

This study aims to investigate the propagation of initial cracks in electric motors and their rate of spread through the rotor structure under various operating conditions. Traction motors are subjected to high centrifugal load owing to their speed and rapid acceleration and deceleration. In the manufacturing process, some initial imperfections or cracks in the rotor components are likely to occur. Under the influence of loading, these cracks will grow, and factors such as loading frequency, material strength, and location of material voids will affect this threshold speed. In the current study, a fracture mechanics–based approach has been used to investigate the crack growth rate for a 100 kW outer rotor motor with a rated speed of 6,000 rpm and a peak speed of 20,000 rpm for an integrated drive application.

Barua, Himel↗

Probabilistic Deliverability Assessment of Distributed Energy Resources via Scenario-Based AC Optimal Power Flow

As electric grids decarbonize and distributed energy resources (DERs) become increasingly prevalent, interconnection assessments must evolve to reflect operational variability and control flexibility. This paper highlights key modeling limitations observed in practice and reviews approaches for modeling uncertainty. It then introduces a Probabilistic Deliverability Assessment (PDA) framework designed to complement and extend existing procedures. The framework integrates scenario-based AC optimal power flow (AC OPF), corrective dispatch, and optional multi-temporal constraints. Together, these form a structured methodology for quantifying DER utilization, deliverability, and reliability under uncertainty in load, generation, and topology. Outputs include interpretable metrics with confidence intervals that inform siting decisions and evaluate compliance with reliability thresholds across sampled operating conditions. A case study on Puerto Rico’s publicly available bulk power system model demonstrates the framework’s application using minimal input data, consistent with current interconnection practice. Across staged fossil generation retirements, the PDA identifies high-value DER sites and regions requiring additional reactive power support. Results are presented through mean dispatch signals, reliability metrics, and geospatial visualizations, demonstrating how the framework provides transparent, data-driven siting recommendations. The framework’s modular design supports incremental adoption within existing workflows, encouraging broader use of AC OPF in interconnection and planning contexts.

14 SOLAR ENERGY↗

National Modeling of Geothermal District Energy Systems with Ambient-Temperature Loops Using dGeo: Preprint

Geothermal district energy systems (DES) with ambient-temperature loops, also known as thermal energy networks, are one option for decarbonizing space heating and cooling loads. Geothermal fifth-generation DES include an "ambient" temperature thermal loop that connects heat pumps at each building with thermal balancing sources such as geothermal borehole fields. Heating and cooling are provided via a water-source heat pump at each end-user. This project seeks to analyze the nationwide potential for ambient-temperature loop districts by creating a new module within the Distributed Geothermal Market Demand Model (dGeo). dGeo is an agent-based modeling tool for distributed geothermal resources; it can investigate potential on a nationwide or statewide scale using geospatial data for all 50 states and thermal demands for existing buildings. This process allows for high-level estimates of technical and economic potential for ambient-temperature loop districts across the United States. Using GHEDesigner, a lookup table was created to size borehole fields for different thermal loads and ground conditions experienced across the country. A cost and financing structure, along with incentives, were applied. Cost estimates include costs for the distribution network, borehole field installation and operation, and circulation pump operation, while savings are calculated based on agent energy bills. This newly developed module can be used for assessing which areas of the country have the highest potential for agent benefits from ambient-temperature loop installation and assess the impact of different costing and pricing future scenarios. While the code is still under development and nationwide simulations are ongoing, initial results for two states are provided. Future work includes expanding the module to consider mixed residential and commercial districts and considering multiple costing scenarios.

ambient temperature loop↗

National Modeling of Geothermal District Energy Systems with Ambient-Temperature Loops Using dGeo

Geothermal district energy systems (DES) with ambient-temperature loops, also known as thermal energy networks, are one option for decarbonizing space heating and cooling loads. Geothermal fifth-generation DES include an "ambient" temperature thermal loop that connects heat pumps at each building with thermal balancing sources such as geothermal borehole fields. Heating and cooling are provided via a water-source heat pump at each end-user. This project seeks to analyze the nationwide potential for ambient-temperature loop districts by creating a new module within the Distributed Geothermal Market Demand Model (dGeo). dGeo is an agent-based modeling tool for distributed geothermal resources; it can investigate potential on a nationwide or statewide scale using geospatial data for all 50 states and thermal demands for existing buildings. This process allows for high-level estimates of technical and economic potential for ambient-temperature loop districts across the United States. A lookup table was created using GHEDesigner to size borehole fields for different thermal loads and ground conditions experienced across the country. A cost and financing structure, along with incentives, were applied. Cost estimates include costs for the distribution network, borehole field installation and operation, and circulation pump operation, while savings are calculated based on energy bills for building owners (agents). This newly developed module can be used for assessing which areas of the country have the highest potential for agent benefits from ambient-temperature loop installation and assess the impact of future cost and price scenarios. Initial results for statewide analysis (for Vermont) and nationwide (for United States) are provided. Future work includes expanding the module to consider mixed residential and commercial districts as well as evaluating multiple cost scenarios.

ambient-temperature loop↗

Understanding the structural mechanics of ligated DNA crystals via molecular dynamics simulation

DNA self-assembly is a highly programmable method to construct arbitrary architectures based on sequence complementarity. Among various constructs, DNA crystals are macroscopic crystalline materials formed by assembling motifs via sticky end association. Due to their high structural integrity and size ranging from tens to hundreds of micrometers, DNA crystals offer unique opportunities to study the structural properties and deformation behaviors of DNA assemblies. For example, enzymatic ligation of sticky ends can selectively seal nicks resulting in more robust structures with enhanced mechanical properties. However, the research efforts have been mostly on experiments involving different motif designs, structural optimization, or new synthesis methods, while their mechanics are not yet fully understood. The complex properties of DNA crystals are difficult to study via experiments alone, and numerical simulation can complement and aid the experiments. The coarse-grained molecular dynamics (MD) simulation is a powerful tool that can probe the mechanics of DNA assemblies. Here, we investigate DNA crystals made of four different motif lengths with various ligation patterns (full ligation, major directions, connectors, and in-plane) using oxDNA, an open-source, coarse-grained MD platform. We found that several distinct deformation stages emerge in response to mechanical loading and that the number and the location of ligated nucleotides can significantly modulate structural behaviors. These findings should be useful for predicting crystal properties and thus improving the design.

DNA crystal↗

Restructuring of the Lewis Acid Sites in Y-Modified Dealuminated Beta-Zeolite by Hydrothermal Treatment

Yttrium-modified dealuminated Betazeolite (Y-BEA) represents a type of Lewis acid zeolite that has gained attention for its potential to efficiently catalyze the conversion of biomass-derived oxygenates. The structure of the Y active sites and their dynamics during biomass conversion reactions, which normally involve substantial amounts of water, necessitate thorough investigation for the rational design of more active and stable catalysts. Here, we conducted a study where a series of Y-BEA catalysts with different yttrium loadings (1–7 wt.%) were subjected to hydrothermal treatment (450 °C, 20% water) and investigated for their structural and catalytic activity changes through a combination of multiple characterizations and kinetic measurements. The number of acid sites of Y-BEA decreased without a change in acid strength following the hydrothermal treatment, which was confirmed by the results of acid site titration, infrared spectroscopy of probe molecules, and kinetic measurements for probe reactions (acetone aldol condensation). Structural analysis using X-ray diffraction (XRD), specific surface area measurement, X-ray absorption spectroscopy (XAS), and X-ray photoelectron spectroscopy (XPS) demonstrated that both the zeolite structure and the isolation status of the Y site remain intact after hydrothermal treatment. Further, the Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) spectra, thermogravimetric analysis (TGA), and operando 1 H and 29 Si magic-angle spinning (MAS) nuclear magnetic resonance (NMR) revealed the dehydroxylation of Y-BEA induced by hydration-rearrangement-condensation restructuring during the high-temperature steam treatment. Dehydroxylation affects the structure of Y sites by reducing their vicinal silanol sites. In conclusion, this conversion of Lewis acidic Y sites into nonacidic sites is the primary factor behind the change in acid site quantity and catalytic activity on Y-BEA.

36 MATERIALS SCIENCE↗

Countercurrent flow characteristics of next generation solvent in novel 3D printed columns for carbon capture

Solvent based absorption for carbon dioxide capture in a packed column is being considered as an efficient technology for the decarbonization process of point source. Significant efforts are underway to improve the design of packings with the cutting edge 3D printing technology for efficient carbon capture. Accordingly, multiphase flow studies were conducted to assess the performance of novel 3D printed columns with various triply periodic minimal surface (TPMS) designs. The effects of solvent properties, liquid and gas loads on the performance of TPMS columns are extensively explored. Hydrodynamics of the potential water-lean solvents (EEMPA) as well as aqueous monoethanolamine (MEA) solvent for carbon capture are evaluated and compared. The interfacial area and liquid holdup increase with increasing liquid loads (q L ) for TPMS columns. Schwarz column consistently shows the highest liquid holdup value. The EEMPA exhibits higher values for the interfacial area (10–15 %) and liquid holdup (~4 %) in comparison to the MEA. TPMS columns exhibit the intermediate value of dry pressure drop between the random and the structure packed columns. Among selected TPMS columns, the gyroid packing shows the lowest pressure drop. The gas load has marginal impact on the interfacial area at lower value while a higher gas load leads to column’s flooding. Prior to the flooding, the interfacial area in TMPS packings rises with increased gas load at a fixed liquid load except Schwarz packing where interfacial area is incentive to the gas load. Additionally, the liquid holdup and wet pressure drop rise as gas load increases in TPMS columns. Overall, Fisher Koch packing is more susceptible to flood as compared to other TPMS packings. Flow regimes: loading and flooding are also delineated in the TPMS packings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CoEx Electrode Structuring for High Energy and Fast Charging Lithium-Ion Batteries

This project was a collaboration between SRI International (SRI) and Oak Ridge National Laboratory (ORNL) focused on advancing SRI’s CoEx technology for printing of battery electrodes with structured porosity, specifically for improving fast charging performance. Prior work funded by the Vehicle Technologies Office (VTO) served as proof-of-concept for CoEx printing, with the scope limited to demonstrating that CoEx structuring in the cathode would improve discharge performance. In that work, a thick cathode was paired with an anode produced through conventional means (i.e. it had no structuring), and the baseline comparison was a cell with conventionally produced cathode and anode of similar loading, along with a lower loaded cell that was intended to represent cells of typical loading. The result of that work showed that the CoEx cells had higher energy density than the thin baseline cells, due to the thicker electrode layers, and had much higher power density than the thick baseline cells at higher discharge rates, because the CoEx cathode had higher performance than the conventional cathode. In this project, we proposed to extend the CoEx technology to structure both the anode and cathode of a lithium ion battery, resulting in at least a 20% increase in energy density under fast charging conditions, while reducing costs by 15% and cutting energy usage during production.

25 ENERGY STORAGE↗

Development of Predictive Model for Accurate Rupture Time from Multi-Axial Creep in Alloy 709 with Physics-Based Simulations

A physics-based model is developed to predict multiaxial creep behavior in Alloy 709 (A709), an advanced austenitic stainless steel intended for high-temperature applications such as Sodium Fast Reactors (SFRs). Compared to conventional stainless steels like 316H, A709 offers superior high-temperature performance; however, comprehensive data on its multiaxial creep response remain limited. To address this gap, a crystal plasticity finite element (CPFE) framework is used to simulate the deformation and failure mechanisms of A709 under multiaxial loading conditions. The model incorporates an extended Hu-Cocks dislocation creep formulation that accounts for precipitation effects, along with the Sham–Needleman model to capture grain boundary cavitation-driven failure. These advanced constitutive models enable a detailed understanding of the interplay between microstructural evolution and macroscopic creep response. Furthermore, the study evaluates the predictive accuracy of various effective stress measures in estimating creep rupture life, leveraging simulated multiaxial creep data. The findings provide critical insights into the applicability of different stress measures for engineering design and life prediction of A709 components operating under complex loading conditions. This work contributes to improving the reliability of high-temperature structural components by advancing predictive modeling capabilities for advanced austenitic steels.

Alloy 709↗

Modeling and Analysis of Wind Turbine Wake Vortex Evolution Due to Time-Constant Spatial Variations in Atmospheric Flow

Modern utility-scale wind turbines are evolving toward larger, lighter, and more flexible designs to meet the growing demand for renewable energy while minimizing logistical costs. However, these advancements in lightweight design result in heightened aeroelastic sensitivity, leading to complex interactions which affect the rotor’s capacity to withstand aerodynamic loading and the cascading effects that manifest in the wake’s vortex-structure evolution under variable atmospheric conditions. In this paper, we analyze the influence of stream-wise fluctuating atmospheric flow conditions on wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs’ Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex–wake interactions for a range of conditions with spatially variant atmospheric flow. CODEF solutions for turbine operation in wind conditions featuring only one parameter fluctuation are compared to wind conditions with several wind parameter variations in combination. By isolating individual inflow variations and comparing them to multi-parameter scenarios, we determine the contributions of each atmospheric factor to rotor dynamics, wake evolution, and downstream wind farm interactions. The purpose of this paper is to analyze the effects of spatial variations in atmospheric flow on the topological evolution of wind turbine vortex wakes, which constitutes a gap in the current understanding of wind turbine wake dynamics. The insights gained from this study are particularly valuable for the development of wind farm control strategies aimed at mitigating the adverse effects of wake interactions, enhancing energy capture, and improving the overall stability of wind farm operations. With these insights, we aim to contribute to the development of modeling and simulation tools to optimize utility-scale wind power plants operating in diverse atmospheric environments.

Farrell, Alayna (ORCID:000000023555720X)↗