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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Measurement of charged-current quasi elastic-like and inclusive muon (anti-) neutrino interactions using NuMI beam the ICARUS detector

The ICARUS experiment, utilizing Liquid Argon Time Projection Chamber (LArTPC) technology, has been successfully taking physics data at Fermilab since June 2022. The experiment's primary objective is to function as the far detector of the Short Baseline Neutrino program (SBN), searching for hints of physics beyond three-flavour PMNS neutrino oscillations. ICARUS also offers other diverse physics capabilities, including searches beyond the standard model and measurements of cross-sections. In addition to being exposed to the Booster Neutrino (BNB) beamline of the SBN experiment, ICARUS sits 795 m downstream and 5.75 degrees off-axis from the NuMI beam line. Due to the off-axis angle between NuMI and ICARUS, coupled with contributions from both pion and kaon decays to neutrino fluxes, interactions of NuMI neutrinos within ICARUS can be detected over a range of several GeV in energy. Measurements of these interactions present unique opportunities to infer neutrino interaction cross sections on an argon nuclear target within an energy range that overlaps both the SBN oscillation search and a significant portion of the DUNE spectrum. This poster will summarize the current status of muon-neutrino and muon-antineutrino charged current inclusive cross section measurements in ICARUS using the FHC and RHC NuMI sample respectively. Such inclusive measurements provide robust benchmarks for the overall interaction rate and muon kinematics, with reduced dependence on hadronic final-state modeling. The measurement of the muon-antineutrino Argon charged current inclusive cross section is particularly exciting and highly relevant for DUNE, given the scarcity of antineutrino-Argon cross section measurements in the literature. In addition, this poster will highlight ICARUS's first measurement of muon-neutrino Argon charged current mesonless final states using both transverse kinematic imbalance (TKI) variables and muon-proton kinematic variables. These measurements provide sensitivity to nuclear effects, final-state interactions, and nucleon correlations in argon, offering important constraints for improving neutrino interaction modeling for upcoming DUNE.

Roy, Promita [Fermilab; Virginia Tech.]↗
DOE OSTI2021

Differential Organic Carbon Mineralization Responses to Soil Moisture in Three Different Soil Orders Under Mixed Forested System

Soil microbial respiration is one of the largest sources of carbon (C) emissions to the atmosphere in terrestrial ecosystems, which is strongly dependent on multiple environmental variables including soil moisture. Soil moisture content is strongly dependent on soil texture, and the combined effects of texture and moisture on microbial respiration are complex and less explored. Therefore, this study examines the effects of soil moisture on the mineralization of soil organic C Soil organic carbon in three different soils, Ultisol, Alfisol and Vertisol, collected from mixed forests of Georgia, Missouri, and Texas, United States , respectively. A laboratory microcosm experiment was conducted for 90 days under different moisture regimes. Soil respiration was measured weekly, and destructive harvests were conducted at 1, 15, 60, and 90 days after incubation to determine extractable organic C (EOC), phospholipid fatty acid based microbial community, and C-acquiring hydrolytic extracellular enzyme activities (EEA). The highest cumulative respiration in Ultisol was observed at 50% water holding capacity (WHC), in Alfisol at 100% water holding capacity, and in Vertisol at 175% WHC. The trends in Extractable Organic Carbon were opposite to that of cumulative microbial respiration as the moisture levels showing the highest respiration showed the lowest EOC concentration in all soil types. Also, extracellular enzyme activities increased with increase in soil moisture in all soils, however, respiration and EEA showed a decoupled relationship in Ultisol and Alfisol soils. Soil moisture differences did not influence microbial community composition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Role of ripples in altering the electronic and chemical properties of graphene

Ripples of graphene are known to manipulate electronic and hydrogenation properties of graphitic materials. More detailed work is needed to elucidate the structure–property relationship of these systems. In this work, the density functional theory is used to compute the energy and electronic structure of the graphene models with respect to variable curvatures and hydrogen adsorption sites. The magnitude of finite bandgap opening depends on the orientation of ripples, and the hydrogen adsorption energy depends on the local curvature of graphene. An adsorbed hydrogen alters the local curvature, resulting in relatively weakened adsorption on the neighboring three sites, which gives a rationale to experimentally observed dynamic equilibrium stoichiometry (H:C = 1:4) of hydrogenated graphene. The surface diffusion transition state energy of adsorbed hydrogen is computed, which indicates that the Eley–Rideal surface recombination mechanism may be important to establish the dynamic equilibrium, instead of the commonly assumed Langmuir–Hinshelwood mechanism.

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

Tuning water dissociation at oxide–electrolyte interfaces with electric fields

Understanding how electric fields influence water dissociation at heterogeneous interfaces is crucial for controlling interfacial chemical reactions and advancing next-generation energy technologies. Herein, ab initio–based machine learning simulations show that even small electric field changes can significantly alter the water dissociation fraction at planar TiO 2 –electrolyte interfaces. The resulting free energy difference between undissociated and dissociated interfacial water exhibits a linear dependence on the field change with a slope of 1.97 eÅ, which far exceeds the dissociation-induced dipole change of a water molecule. Employing a machine-learned collective variable to investigate the reaction statistics of thousands of water dissociation/recombination events, we find that small electric field changes exert minor effects on individual reaction energy barriers but significantly influence the populations of local configurations associated with initial states that are most favorable for reactions. These findings elucidate the pronounced impact of electric fields on interfacial water dissociation and reveal a mechanism for electric-field-controlled chemical reactions.

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

Polarization-resolved core exciton dynamics in LiF using attosecond transient absorption spectroscopy

The ability to control absorption by modifying the polarization of light presents an exciting opportunity to experimentally determine the orbital alignment of absorption features. Here, attosecond extreme ultraviolet (XUV) transient absorption spectroscopy is used to investigate the polarization dependence of core exciton dynamics in LiF thin films at the Li + K edge. XUV pulses excite electrons from the Li 1s core level into the conduction band, allowing for the formation of a p-orbital-like core exciton, aligned along the XUV light polarization axis. A sub-5 fs near-infrared (NIR) probe pulse then arrives at variable time delays, perturbing the XUV-excited states and allowing the coherence decay of the core exciton to be mapped. The coherence lifetimes are found to be ≈ 2.4 ± 0.4 fs, which is attributed to a phonon-mediated dephasing mechanism as in previous core exciton studies. The differential absorption features are also shown to be sensitive to the relative polarization of the XUV and NIR fields. The parallel NIR probe induces couplings between the initial XUV-excited p-like bright exciton and s-like dark excitons. When crossed pump and probe polarizations are used, the coupling between the bright and dark states is no longer dipole-allowed, and the transient absorption signal associated with the coupling is suppressed by approximately 90%. This interpretation is supported by simulations of a few-level model system, as well as analysis of the calculated band structure. Here, the results indicate that laser polarization can serve as a powerful experimental tool for exploring the orbital alignment of core excitonic states in solid-state materials.

Attosecond laser spectroscopy↗
DOE OSTI2021

Measurement of the energy dependence of the e+e- → $ B\overline{B} $, $ B{\overline{B}}^{\ast } $ and $ {B}^{\ast }{\overline{B}}^{\ast } $ exclusive cross sections

We report the first measurement of the exclusive cross sections e + e - → $B\overline{B}$, e + e - → $B{\overline{B}}^{\ast }$, and e + e - → ${B}^{\ast }{\overline{B}}^{\ast }$ in the energy range from 10.63 GeV to 11.02 GeV. The B mesons are fully reconstructed in a large number of hadronic final states and the three channels are identified using a beam-constrained-mass variable. The shapes of the exclusive cross sections show oscillatory behavior with several maxima and minima. The results are obtained using data collected by the Belle experiment at the KEKB asymmetric-energy e + e - collider.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Measurements of ϒ states production in 𝑝 + 𝑝 collisions at $\sqrt{s}$ = 500 GeV with STAR: Cross sections, ratios, and multiplicity dependence

We report measurements of ϒ⁡(1⁢𝑆), ϒ⁡(2⁢𝑆) and ϒ⁡(3⁢𝑆) production in 𝑝 + 𝑝 collisions at $\sqrt{s}$ =500 GeV by the STAR experiment in year 2011, corresponding to an integrated luminosity ℒ int = 13 pb −1 . The results provide precise cross sections, transverse momentum (𝑝 T ) and rapidity (𝑦) spectra, as well as cross section ratios for 𝑝 T < 10 GeV/c and |𝑦| < 1. The dependence of the ϒ yield on charged particle multiplicity has also been measured, offering new insights into the mechanisms of quarkonium production. The data are compared to various theoretical models: the color evaporation model (CEM) accurately describes the ϒ⁡(1⁢𝑆) production, while the color glass condensate+nonrelativistic quantum chromodynamics (CGC+NRQCD) model overestimates the data, particularly at low 𝑝 T . Conversely, the color singlet model (CSM) underestimates the rapidity dependence. These discrepancies highlight the need for further development in understanding the production dynamics of heavy quarkonia in high-energy hadronic collisions. The trend in the multiplicity dependence is consistent with CGC/saturation and string percolation models or ϒ production happening in multiple parton interactions modeled by PYTHIA 8.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

The DOE E3SM version 2.1: overview and assessment of the impacts of parameterized ocean submesoscales

The U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) version 2.1 builds on E3SMv2 with several changes, with the most notable being the addition of the Fox-Kemper et al. (2011) mixed-layer eddy parameterization. This parameterization captures the effect of finite-amplitude, mixed-layer eddies as an overturning streamfunction and has the primary function of restratification. Herein, we outline the changes to the mean climate state of E3SM that were introduced by the addition of this parameterization. Overall, the presence of the submesoscale parameterization improves the fidelity of the v2.1 simulation by reducing the ocean surface biases in the North Atlantic present in v2, as illustrated by changes in the climatological sea surface temperature and salinity and the Arctic sea-ice extent. Other impacts include a slight shoaling of the mixed-layer depths in the North Atlantic and a small improvement in the Atlantic Meridional Overturning Circulation (AMOC). We note that the expected shoaling due to the parameterization is regionally dependent in our coupled configuration. In addition, we investigate why the parameterization and its impacts on mixed-layer depth have little impact on the simulated AMOC: despite increased dense-water formation in the Norwegian Sea, only a small fraction of the water formed makes its way south into the North Atlantic basin. Version 2.1 also exhibits small improvements in the atmospheric climatology, with smaller biases in many notable quantities and modes of variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

X-Ray Polarization of the Magnetar 1E 1841−045

We report on IXPE and NuSTAR observations beginning 40 days after the 2024 outburst onset of magnetar 1E 1841−045, marking the first IXPE observation of a magnetar in an enhanced state. Our spectropolarimetric analysis indicates that both a blackbody (BB) plus double power-law (PL) and a double blackbody plus power-law spectral model fit the phase-averaged intensity data well, with a hard PL tail (Γ = 1.19 and 1.35, respectively) dominating above ≈5 keV. For the former model, we find the soft PL (the dominant component at soft energies) exhibits a polarization degree (PD) of ≈30% while the hard PL displays a PD of ≈40%. Similarly, the cool BB of the 2BB+PL model possesses a PD of ≈15% and a hard PL PD of ≈57%. For both models, each component has a polarization angle (PA) compatible with celestial north. Model-independent polarization analysis supports these results, wherein the PD increases from ≈15% to ≈70% in the 2–3 keV and 6–8 keV ranges, respectively, while the PA remains nearly constant. We find marginal evidence for phase-dependent variability of the polarization properties, namely a higher PD at phases coinciding with the hard X-ray pulse peak. We compare the hard X-ray PL to the expectation from resonant inverse Compton scattering (RICS) and secondary pair cascade synchrotron radiation from primary high-energy RICS photons; both present reasonable spectropolarimetric agreement with the data, albeit the latter does so more naturally. We suggest that the soft PL X-ray component may originate from a Comptonized corona in the inner magnetosphere.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

FLOWERS AEP: An Analytical Model for Wind Farm Layout Optimization

Annual energy production (AEP) is commonly used in objective functions for wind farm layout optimization. AEP is proportional to wind farm power production integrated over an annual distribution of free-stream wind conditions. Physics-based estimates of wind farm power production typically rely on low-fidelity engineering wake models that approximate the steady-state wind farm flow field. AEP estimates are then obtained by performing independent simulations for discrete wind conditions and using rectangular quadrature to account for each condition's expected frequency of occurrence. Depending on the number of simulated discrete wind conditions, this numerical integral could be hampered by poor accuracy or high computational costs. The FLOWERS AEP model instead poses an analytical integral of the engineering wake model over the variable wind conditions, yielding a closed-form, analytical function for wind farm AEP. This paper derives the analytical functions for FLOWERS AEP and its derivatives with respect to turbine position, which are useful for gradient-based wind farm layout optimization, in nondimensional form. We then analyze the benefits of the FLOWERS AEP model over conventional reference models, focusing on its low cost, adequate wake loss predictions, and smooth design space. Although the FLOWERS approach is found to predict the exact value of AEP with some error relative to the reference model (within 14% on average), it dramatically reduces computation time by an order of magnitude, produces a qualitatively similar design space at relatively low resolution, and yields comparable optimal layouts. This significant speed improvement is critical in layout optimization applications, where determining an optimal layout in an efficient manner is more important than precise AEP prediction.

17 WIND ENERGY↗
DOE OSTI2020

Metal–Ligand Cooperativity via Exchange Coupling Promotes Iron- Catalyzed Electrochemical CO 2 Reduction at Low Overpotentials

Biological and heterogeneous catalysts for the electrochemical CO 2 reduction reaction (CO 2 RR) often exhibit a high degree of electronic delocalization that serves to minimize overpotential and maximize selectivity over the hydrogen evolution reaction (HER). Here, we report a molecular iron(II) system that captures this design concept in a homogeneous setting through the use of a redox non-innocent terpyridine-based pentapyridine ligand (tpyPY2Me). As a result of strong metal-ligand exchange coupling between the Fe(II) center and ligand, [Fe(tpyPY2Me)] 2+ exhibits redox behavior at potentials 640 mV more positive than the isostructural [Zn(tpyPY2Me)] 2+ analog containing the redox-inactive Zn(II) ion. This shift in redox potential is attributed to the requirement for both an open-shell metal ion and a redox non-innocent ligand. The metal-ligand cooperativity in [Fe(tpyPY2Me)] 2+ drives the electrochemical reduction of CO 2 to CO at low overpotentials with high selectivity for CO 2 RR (>90%) and turnover frequencies of 100,000 s -1 with no degradation over 20 h. The decrease in the thermodynamic barrier engendered by this coupling also enables homogeneous CO 2 reduction catalysis in water without compromising selectivity or rates. Synthesis of the two-electron reduction product, [Fe(tpyPY2Me)] o , and characterization by X-ray crystallography, Mössbauer spectroscopy, X-ray absorption spectroscopy (XAS), variable temperature NMR, and density functional theory (DFT) calculations, support assignment of an open-shell singlet electronic structure that maintains a formal Fe(II) oxidation state with a doubly reduced ligand system. Furthermore, this work provides a starting point for the design of systems that exploit metal-ligand cooperativity for electrocatalysis where the electrochemical potential of redox non-innocent ligands can be tuned through secondary metal-dependent interactions.

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

Investigating Particle Phase State Dependencies during a Historic Pacific Northwest Wildfire Event

The function and lifetime of an atmospheric particle are greatly dependent upon its phase state. Studying particle phase states from specific ambient source types is often challenging due to uncontrolled environmental conditions and multiple source contributions. However, a historic Pacific Northwest wildfire event occurred in September 2020, providing a rare opportunity to study a pseudo-single particle type ambient sample (i.e., wildfire) over time. Sampling was performed in Richland, Washington, capturing aged particles from shifting wildfire sources. In addition to source variability, temporal variation in wildfire particle phase state was observed from single particle analyses. Despite this, single particle elemental compositions were homogenous over time (=87% carbonaceous) with no significant temporal variation in organic functional group abundances within individual particles either (e.g., 4% relative standard deviation in alkene contributions). While particle composition is indeed known to affect phase state, water uptake appeared to be the most significant contributor to phase state variability amongst single particles here, as particle aspect ratios (related to phase state) linearly correlated with ambient relative humidity during sampling (R2 = 0.65). Therefore, while limited to a case study, meteorological considerations are found to convey greater comparative importance than particle composition for aged particle phase state predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Neutron star mass estimates from gamma-ray eclipses in spider millisecond pulsar binaries

Reliable neutron star mass measurements are key to determining the equation of state of cold nuclear matter, but such measurements are rare. Black widows and redbacks are compact binaries consisting of millisecond pulsars and semi-degenerate companion stars. Spectroscopy of the optically bright companions can determine their radial velocities, providing inclination-dependent pulsar mass estimates. Although inclinations can be inferred from subtle features in optical light curves, such estimates may be systematically biased due to incomplete heating models and poorly understood variability. Using data from the Fermi Large Area Telescope, we have searched for gamma-ray eclipses from 49 spider systems, discovering significant eclipses in 7 systems, including the prototypical black widow PSR B1957+20. Gamma-ray eclipses require direct occultation of the pulsar by the companion, and so the detection, or significant exclusion, of a gamma-ray eclipse strictly limits the binary inclination angle, providing new robust, model-independent pulsar mass constraints. For PSR B1957+20, the eclipse implies a much lighter pulsar (1.81 ± 0.07 solar masses) than inferred from optical light curve modelling.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Smart-PGSim: Using Neural Network to Accelerate AC-OPF Power Grid Simulation

In this work we address the problem of accelerating complex power-grid simulation through machine learning ( ML). Specifically, we develop a framework, Smart-PGSim,which generates multitask-learning (MTL) neural network (NN)models to predict the initial values of variables critical to the problem convergence. MTL models allow information sharing when predicting multiple dependent variables while including customized layers to predict individual variables. We show that,to achieve the required accuracy, it is paramount to embed domain-specific constraints derived from the specific power-grid components in the MTL model. Smart-PGSim then employs the predicted initial values as a high-quality initial condition for the power-grid numerical solver (warm start), resulting in both higher performance compared to state-of-the-art solutions while maintaining the required accuracy. Smart-PGSim brings 2.60×speedup on average (up to 3.28×) computed over 10,000 problems, without losing solution optimality.

machine learning, neural networks↗
DOE OSTI2024

Ensemble variational Fokker-Planck methods for data assimilation

Particle flow filters solve Bayesian inference problems by smoothly transforming a set of particles into samples from the posterior distribution. Particles move in state space under the flow of an McKean-Vlasov-Itˆo process. This work introduces the Variational Fokker-Planck (VFP) framework for data assimilation, a general approach that includes previously known particle flow filters as special cases. The McKean-Vlasov-Itˆo process that transforms particles is defined via an optimal drift that depends on the selected diffusion term. It is established that the underlying probability density - sampled by the ensemble of particles - converges to the Bayesian posterior probability density. For a finite number of particles the optimal drift contains a regularization term that nudges particles toward becoming independent random variables. Based on this analysis, we derive computationally-feasible approximate regularization approaches that penalize the mutual information between pairs of particles, and avoid particle collapse. Moreover, the diffusion plays a role akin to a particle rejuvenation approach that aims to alleviate particle collapse. The VFP framework is very flexible. Different assumptions on prior and intermediate probability distributions can be used to implement the optimal drift, and localization and covariance shrinkage can be applied to alleviate the curse of dimensionality. A robust implicit-explicit method is discussed for the efficient integration of stiff McKean- Vlasov-Itˆo processes. Here, the effectiveness of the VFP framework is demonstrated on three progressively more challenging test problems, namely the Lorenz ’63, Lorenz ’96 and the quasi-geostrophic equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Intensifying Renewable Energy Droughts in the Western U.S. Amid Evolving Infrastructure and Climate

If renewable energy resources continue to become a larger part of the generation mix in the United States (U.S.), so does the potential impact of prolonged periods of low wind and solar generation, known as variable renewable energy (VRE) droughts. In such a future, naturally occurring VRE droughts need to be evaluated for their potential impact on grid reliability. This study is the first of its kind to examine the impacts of compound VRE energy droughts in the Western U.S. across a range of potential future climate and infrastructure scenarios. We find that compound VRE drought severity may increase significantly in the future, primarily due to the dramatic increase in wind and solar generation needed in some future infrastructure scenarios. We find that in our future climate scenario, the variability of energy drought severity increases, which has implications for sizing energy storage necessary for mitigating drought events. We also examine the spatial patterns of compound VRE drought events that effect multiple regions of the grid simultaneously. These co-occurring events have distinct spatial patterns depending on the season. We observed overall fewer connected events in the future with the combined effect of potential climate and infrastructure changes, although in the fall we observe a climate-induced shift toward events which impact more regions simultaneously.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Artificial Intelligence-Driven Management of Sustainable Energy Resources: Visibility, Operation, and Control

The rapid global transition toward sustainable energy resources (SERs) is reshaping how modern power systems are observed, optimized, and controlled. While SERs have significantly advanced decarbonization, their weather dependence, variability, and inverter-dominated characteristics challenge traditional, centralized, and deterministic grid operation. At the same time, the proliferation of high-resolution data from inverters, smart meters, and sensors offers unprecedented visibility into system dynamics. Yet, it also exceeds the analytical capability of conventional model-based approaches. Artificial intelligence (AI) provides a new foundation for addressing these challenges by bridging physical laws with data-driven learning, enabling accurate state awareness, adaptive operation, and coordinated control across distributed assets. This article examines how AI transforms the management of SER-rich power systems along three critical dimensions: 1) enhancing visibility by inferring behind-the-meter (BTM) activities, assessing SER flexibility, and reconstructing system states from sparse or noisy measurements; 2) improving operation through AI-enhanced SER service provision, volt/var control (VVC), and dynamic operating envelopes (DOE) for efficiency and security; and 3) advancing control by embedding learning-based intelligence into inverter coordination, voltage and frequency regulation, and long-term dispatch. Together, these developments reveal how AI can convert the variability of SERs from an operational challenge into a source of flexibility, resilience, and intelligence, paving the way toward sustainable, adaptive, and self-optimizing power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Spatiotemporal Variability in Wind Turbine Blade Leading Edge Erosion

Wind turbine blade leading edge erosion (LEE) reduces energy production and increases wind energy operation and maintenance costs. Degradation of the blade coating and ultimately damage to the underlying blade structure are caused by collisions of falling hydrometeors with rotating blades. The selection of optimal methods to mitigate/reduce LEE are critically dependent on the rates of coating fatigue accumulation at a given location and the time variance in the accumulation of material stresses. However, no such assessment currently exists for the United States of America (USA). To address this research gap, blade coating lifetimes at 883 sites across the USA are generated based on high-frequency (5-min) estimates of material fatigue derived using a mechanistic model and robust meteorological measurements. Results indicate blade coating failure at some sites in as few as 4 years, and that the frequency and intensity of material stresses are both highly episodic and spatially varying. Time series analyses indicate that up to one-third of blade coating lifetime is exhausted in just 360 5-min periods in the Southern Great Plains (SGP). Conversely, sites in the Pacific Northwest (PNW) exhibit the same level of coating lifetime depletion in over three times as many time periods. Thus, it may be more cost-effective to use wind turbine deregulation (erosion-safe mode) for damage reduction and blade lifetime extension in the SGP, while the application of blade leading edge protective measures may be more appropriate in the PNW. Annual total precipitation and mean wind speed are shown to be poor predictors of blade coating lifetime, re-emphasizing the need for detailed modeling studies such as that presented herein.

Pryor, Sara C. (ORCID:0000000348473440)↗