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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Technology Case Study: Economic, Sustainability, and Deployment Considerations for Sustainable Aviation Fuels Produced via Lignocellulosic Sugar Catalysis

This report presents a technology case study reflecting one exemplary representative pathway for the conversion of lignocellulosic sugars to sustainable aviation fuels (SAF) via aqueous phase reforming (APR) catalysis, considered within a broader integrated biorefinery framework based on biochemical processing operations. While far from the only option for converting sugars to SAF, this pathway was selected as a case study here based on its relatively high technology maturity and simplistic processing approach (avoiding complex separations or other equipment scalability challenges), coupled with the potential for high fuel yields and favorable costs/carbon intensities with opportunities for further near-term optimization. The report considers key process integration and engineering design considerations for a modeled hypothetical, nth-plant commercial biorefinery, reflecting a number of processing options and parameters envisioned to be achievable as future goals. Resultant outputs from Aspen Plus process simulations are evaluated through techno-economic and life cycle analyses (TEA and LCA), including implications for marginal cost of CO2 abatement and inclusion of currently-applicable policy incentives. Moving beyond base case configurations, a number of alternative scenarios are also evaluated for their ability to further improve economics, greenhouse gas (GHG) emissions, and marginal cost of abatement, highlighting a path to achieve deep decarbonization goals of more than 70% GHG reduction for SAF (with the potential to reach net-negative carbon intensities in some cases) under reasonable fuel production costs. The report also highlights future opportunities and gaps for further research on this technology pathway.

09 BIOMASS FUELS↗
DOE OSTI2022

Performance Enhancement of APW+lo Calculations by Simplest Separation of Concerns

Full-potential linearized augmented plane wave (LAPW) and APW plus local orbital (APW+lo) codes differ widely in both their user interfaces and in capabilities for calculations and analysis beyond their common central task of all-electron solution of the Kohn–Sham equations. However, that common central task opens a possible route to performance enhancement, namely to offload the basic LAPW/APW+lo algorithms to a library optimized purely for that purpose. To explore that opportunity, we have interfaced the Exciting-Plus (“EP”) LAPW/APW+lo DFT code with the highly optimized SIRIUS multi-functional DFT package. This simplest realization of the separation of concerns approach yields substantial performance over the base EP code via additional task parallelism without significant change in the EP source code or user interface. We provide benchmarks of the interfaced code against the original EP using small bulk systems, and demonstrate performance on a spin-crossover molecule and magnetic molecule that are of size and complexity at the margins of the capability of the EP code itself.

Zhang, Long↗
DOE OSTI2023

Protein-based approach for high-purity Sc, Y, and grouped lanthanide separation

Rare earth elements (REEs: Sc, Y, La- Lu) are irreplaceable components in many clean energy and consumer technologies. However, the extraction and subsequent separation of individual REEs from ore-based feedstocks remains a significant economic and environmental challenge. Here in this work, we investigated the intra-REE separation potential of lanmodulin (LanM), a natural protein from Methylorubrum extorquens that has emerged as a sustainable potential alternative to conventional solvent extraction-based separation. By determining the intra-REE selectivity of immobilized LanM and systematically testing pH-based and small chelator-based (i.e., citrate and malonate) desorption processes, we established the framework and methodology for achieving select individual and grouped REE separations from a mixed REE feedstock. We show that Sc forms the tightest complex with LanM among REEs but can be readily and selectively desorbed using malonate to generate high-purity Sc (>99 % purity, >99 % yield) in a single adsorption/desorption cycle. We further show that the intrinsic REE selectivity of LanM is sufficient to achieve heavy REE (HREE) separation from light and middle REEs (L-MREEs), yielding an yttrium-enriched product. This separation effect is further magnified by pairing LanM’s unique M-LREE preference with a HREE-preferring chelator in the desorption process, which enriches HREE and MREE fractions relative to low value, abundant La/Ce. Finally, by combining pH- and citrate-based desorption processes in a two-cycle separation scheme, we demonstrate the generation of fractions highly enriched in Y, Gd-Lu, Pr-Eu, and La-Ce. Collectively, these data support the application of a LanM-based approach for achieving impactful REE separations from mixed REE feedstocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A fresh perspective on the role of band bending, and related contributors, in light-driven production of electricity and chemicals

It is widely known that semiconductor-based solar energy conversion could power our planet. This is in part because high-quality semiconductor structures are unrivalled in their ability to separate photogenerated electrons and holes. One effective approach to achieving this photoinduced charge separation relies on a phenomenon known as “band bending”. But details to justify why band bending results in photoinduced charge separation are more complex than often appreciated. This underappreciation is an impediment to the rational, hypothesis-driven design of next-generation approaches to solar energy conversion. Herein we show, by means of derivations rooted in physical chemistry, that several phenomena – not just band bending – can facilitate photoinduced charge separation, and that each is influenced by nonequilibrium species concentration and a parameter, such as diffusion coefficient or rate coefficient, that introduces dynamics. To help visualize the impact of each phenomenon, we introduce plots that depict their contributions as free energy, force, flux, force constant, and rate. We reveal that spatial dopant distributions that define band bending are predictors of initial photogenerated species transport rates. But charge separation alone does not guarantee high-efficiency operation. A photogenerated change in energy that is freely available to do useful work is also essential, and is strongly dependent on semiconductor optical properties and reaction kinetics. Notably, this information reveals that specificity of interfacial chemical reactions – even when they are not preceded by charge separation elsewhere – can result in efficient solar energy conversion. We expect that this tutorial will guide researchers in their pursuit to uncover new mechanisms for light to perform useful work.

14 SOLAR ENERGY↗
DOE OSTI2022

Using Separation-Enhanced Isotope Ratio Mass Spectrometry

Stable isotope ratio measurements using IRMS have been shown by LANL to be effective for tracking co-processed biogenic carbon, with results approaching that of AMS. The lower cost of an IRMS may enable deployment to refineries improving access and analysis turnaround times (≤ 2-hours), and by extension data that can allow process optimization to maximize renewable carbon in desired refinery products. This work will apply chemical separation approaches as part of the IRMS analyses, enabling biogenic carbon tracking in fuel product streams by boiling point range, by chemical class, or even by compound. This work will show IRMS to be at a minimum as reliable and comparable to AMS, by using separations to improve sensitivity at low blend ratios and enable refinery process optimization through onsite analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Separation, Recovery and Upgrading of 2,3-Butanediol from Fermentation Broth

2,3-Butanediol (BDO) is a bio-derived building block available from biomass through biochemical methods in high titers (>120 g L-1) making it an attractive target for production and further upgrading to chemical products and fuels such as sustainable aviation fuel. A key challenge to enable the adoption of BDO as a precursor is the effective separation and isolation of this molecule from the fermentation broth. 2,3-Butanediol has a boiling point higher than that of water (177 degrees C), and as a consequence, separation via distillation methods is an energy-intensive and therefore costly approach. We have improved the BDO separation through conversion to a 1,3-dioxolane directly in fermentation broth via reaction with bio-derived aldehydes catalyzed by a solid acid catalyst. The resulting dioxolane phase separates from the fermentation broth, allowing for easy decantation and isolation in >90% isolated yield. Isolated dioxolane can be used directly as a compression iginition fuel, trans-acetalized to recover high-purity BDO or used directly in a catalytic process as a BDO synthon to produce methyl ethyl ketone with aldehyde recovery in near quantitative yield.

aviation fuel↗
DOE OSTI2020

A Performance analysis of the Claridge-Culp-Liu dehumidification process: A novel approach for drying moist air based on membrane separation, vacuum compression and sub-atmospheric condensation

This article covers a basic model for analyzing the performance of the Claridge-Culp-Liu dehumidification process. The fundamental process efficiency limit for dehumidification is close to COP Carnot , but for the eight dehumidification cases examined, the limiting or ideal energy use required is 26% to 56% that of a Carnot condensing system as shown in an earlier paper. The model presented in this paper is used to show the membrane system performance reduction caused by finite membrane area, finite water vapor permeance, non-zero air permeance, non-zero system air pressure drop, non-ideal compressors, vacuum pumps, and condensers. The performance of a “conservative” membrane system based on the use of existing components is computed for eight specific conditions along with that of a “target” system that assumes expected component performance after additional future component development. The “conservative” membrane system would use 36% to 66% as much energy as a system with a COP=7 chiller to produce the same dehumidification for the eight cases examined while the “target” system would use 15% to 40% the energy of a system with a COP=7 chiller. In addition to the significant energy reduction over conventional technology, the membrane system offers the advantages of: 1) no HFC refrigerant use; 2) direct isothermal control over humidity ratio setpoint; 3) maximum capacity occurs at design conditions; and 4) system generates pure water extracted from air as a by-product.

42 ENGINEERING↗
DOE OSTI2026

Cosmogenic 3 He exposure dating in mafic rocks by “Virtual mineral separation” of pyroxene

We describe a “virtual mineral separation” method for measuring the cosmogenic 3 He concentration in pyroxene in mafic rocks that consist mainly of plagioclase and pyroxene, without physically separating the minerals. This approach is significantly faster and more cost-effective than the conventional method, which requires physical separation and purification of pyroxene grains by time-consuming and labor-intensive crushing, acid cleaning, magnetic separation, HF etching, and handpicking under a microscope. The premise of the method is that helium diffusivity is much higher in plagioclase than in pyroxene, so controlled preheating of a mixed whole-rock sample can degas 3 He from plagioclase while retaining all 3 He in pyroxene. A second heating step releases all 3 He from pyroxene for measurement. To then obtain a 3 He concentration in pyroxene rather than the whole rock, we determine the pyroxene weight fraction in the sample using X-ray computed tomography (CT). A comparison of 3 He concentrations in pyroxene measured using virtual mineral separation with those measured in the same samples by physical mineral separation in previous work shows no evidence of systematic bias between the methods. Virtual mineral separation greatly simplifies the workflow for 3 He exposure-dating of mafic rocks, reduces time, effort, and cost, and permits measurements on very small samples. This enables new emerging applications of exposure dating, such as quantifying stochastic surface processes, ecosystem studies, and potential subglacial bedrock exposure dating.

Geosciences↗
DOE OSTI2020

Multiscale investigations of europium(III) complexation with tetra- n -octyl diglycolamide confined in porous solid supports

The microscopic, short-range coordination environments and mesoscopic, long-range structures of Eu 3+ contacted with tetra-n-octyl diglycolamide (TODGA) confined on ordered mesoporous carbon (OMC) nanoparticles and Amberchrom CG 71 resin were probed using Eu L 3 -edge extended X ray absorption fine structure (EXAFS) as well as small-angle and wide-angle X ray scattering, SAXS and WAXS, respectively. A homoleptic Eu(TODGA) 3 3+ coordination complex typical of liquid-liquid extraction (LLE) chemistry is present under low Eu 3+ loading conditions on both solid supports. Deviations from this traditional structure motif appear at hyperstoichiometric Eu 3+ loadings, above the 1:3 Eu 3+ to TODGA mole ratio. Microcrystalline-like domains with multinuclear Eu speciation are templated by use of these high Eu 3+ loading conditions with the functionalized OMC materials, highlighting a major departure of liquid-solid extraction chromatography (EXC) from the coordination chemistry of LLE. No such long-range spatial coherence was observed for analogous polyacrylic resin materials. Furthermore, these results demonstrate both the similarities and differences between multiscale structures in LLE and EXC, underscoring the opportunities for improved separation techniques based on solid supports with long-range spatial coherence (e.g., OMC systems) and without it (e.g., resin materials). Since crystallization was the first approach to adjacent lanthanide separations, the prospect of templating microcrystalline TODGA-lanthanide complexes that are otherwise not prone to crystallization by use of OMC nanoparticles represents a new entry to addressing long-standing issues in purification by liquid-solid phase separation.

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

Toward Improved Charge Separation through Conformational Control in Copper Coordination Complexes

The continued development of solar energy as a renewable resource necessitates the design and study of new approaches to sustaining photodriven charge separation (CS). To this end, we present a bioinspired approach in which triggered conformational changes are used to control electron transfer (ET) events. We report, photo-induced conformational rearrangements of a ligand are translated into changes in the coordination geometry and environment about a bound metal ion. Taking advantage of the differential coordination properties of Cu I and Cu II , these dynamics facilitate intramolecular ET from Cu I to the ligand to create a CS state. The synthesis and photophysical characterization of CuCl(dpaa R ) (dpaa = dipicolylaminoacetophenone, with R = H and OMe) is presented. These ligands incorporate a fluorophore into their framework that gives rise to a twisted intramolecular charge transfer (TICT) excited state. Excited state ligand twisting provides a tetragonal coordination geometry capable of capturing Cu II in the CS state when an internal ortho-OMe binding site is present (as in dpaaOMe). We employ NMR, IR, EPR, and optical spectroscopies, X-ray diffraction, and electrochemical methods to establish the ground state properties of the Cu I and Cu II complexes. We then investigate the photophysical dynamics of these Cu I complexes via time-resolved photoluminescence (TR-PL), and optical transient absorption (OTA) spectroscopies. We show that relative to controls lacking a TICT-active ligand, the lifetime of the CS state is enhanced ~1000-fold. Further, the presence of the ortho-OMe substituent greatly enhances the lifetime of the TICT* state and biases the coordination environment toward Cu II . The presence of Cu I decreases photoinduced degradation from 14 to <2% but does not result in significant quenching via ET. Factors affecting CS in these systems are discussed, laying the groundwork for our strategy toward solar energy conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Paramagnetic Properties of Rare Earth Hydroxides, Oxalates, and Dibutyl Phosphates

Magnetic separations present a promising approach for the recovery of rare earth (RE) elements from mixtures, particularly when coupled with precipitation techniques that enhance process efficiency and selectivity. However, the magnetic properties of RE materials typically encountered in the separations industry are not well characterized. Here, we synthesized a series of RE materials, combining four REs – praseodymium (Pr), neodymium (Nd), terbium (Tb), and dysprosium (Dy) – with three precipitating agents – hydroxide, oxalate, and dibutyl phosphate. All materials showed typical paramagnetic behavior consistent with the Curie-Weiss law. At low temperatures, we observed weak antiferromagnetic correlations, which were more pronounced for the lighter RE ions (Pr, Nd). Particle morphology and crystallography analyses showed that the dibutyl phosphates were well-ordered metal-organic frameworks, the oxalates were crystals with mixed hydration states, and the hydroxides were mostly amorphous. Regardless of the degree of crystallinity, the effective magnetic moments aligned well with theoretical estimates based on Hund's rules and 4f electron configurations of the corresponding RE ions. For a given RE ion, the magnetophoretic response was thus determined by the size of the particles rather than specific metal-ligand coupling, with dibutyl phosphate promoting the formation of larger crystals that were the most strongly attracted to magnets.

Wang, Qingpu (ORCID:0000000156041571)↗
DOE OSTI2025

Gradient flow based phase-field modeling using separable neural networks

Allen–Cahn equation is a reaction–diffusion equation and is widely used for modeling phase separation. Machine learning methods for solving the Allen–Cahn equation in its strong form suffer from inaccuracies in collocation techniques, errors in computing higher-order spatial derivatives, and the large system size required by the space–time approach. To overcome these challenges, we propose solving the gradient flow of the Ginzburg–Landau free energy functional, which is equivalent to the Allen–Cahn equation, thereby avoiding the second-order spatial derivatives associated with the Allen–Cahn equation. A minimizing movement scheme is employed to solve the gradient flow problem, eliminating the complexities of a space–time approach. We utilize a separable neural network that efficiently represents the phase field through low-rank tensor decomposition. As we use the minimizing movement scheme to numerically solve the gradient flow problem, we thus, refer to the proposed method as the Separable Deep Minimizing Movement (SDMM) method. The evaluation of the functional in the minimizing movement scheme using the Gauss quadrature technique bypasses the inaccuracies associated with collocation techniques traditionally used to solve partial differential equations. A hyperbolic tangent transformation is introduced on the phase field prior to the evaluation of the functional to ensure that it remains strictly bounded within the values of the two phases. For this transformation, theoretical guarantee for energy stability of the minimizing movement scheme is established. Our results suggest that this transformation helps to improve the accuracy and efficiency significantly. The proposed method resolves the challenges faced by state-of-the-art machine learning techniques, outperforming them in both accuracy and efficiency. It is also the first machine learning method to achieve an order of magnitude speed improvement over the finite element method. In addition to its formulation and computational implementation, several case studies illustrate the applicability of the proposed method.

42 ENGINEERING↗
DOE OSTI2021

Quantitative analysis method for multi-color microscopy

We developed an analysis framework for quantitatively interpreting results from multi-color fluorescence microscopy data. When the emission signal from fluorescent probes (i.e. from biological microscopy or in single-particle microscopy) is spectrally separated before detection, the resulting signals contain information about the strengths of each probe. We built a model to deconvolve the raw data into quantitative descriptions of either of the wavelength of a single probe or the relative strengths among multiple probes. This approach requires only spectrally separating the image data into two or more channels, as opposed to fully resolving the spectral profile, thus allowing other microscopy techniques to be used simultaneously. Our analysis framework incorporates the response features of the optical and imaging elements used to produce the spectral separation, yielding highly quantitative interpretations of the underlying behaviors that give rise to the data.

Ryan, Duncan↗
DOE OSTI2022

Methodology for assessing the maximum potential impact of separations opportunities in industrial processes

Separation technologies currently used in U.S. manufacturing industries are estimated to account for more than 20% of plant energy consumption. However, accurately determining the impact of new separation technology solutions can sometimes be difficult, especially when evaluating a slate of new candidate separation technologies, each of which has its own separation performance, energy demand, and capital cost. In these cases, a typical approach is to assess each new separation technology by collecting performance and cost information and then using that information to develop a techno-economic analysis to identify overall benefits. While this approach is thorough, it can be time consuming and can hinder reaching a critical understanding of the potential of a given separation challenge, especially when there is no known solution. To address these issues, we developed an assessment methodology, using industrial screening processes, that can be used to better understand the potential impacts of addressing a given separation challenge. This paper presents an overview of our separation challenge stream assessment methodology. The methodology involves defining an “ideal” separator and deriving the associated minimum separation energy. The “ideal” separator represents the most optimistic outlook of a given opportunity so the maximum impact from existing and not-yet-developed solutions can be assessed. Using established biorefinery models, we applied the methodology to 10 different separation challenge streams from two different biomass conversion platforms to identify the type of information that can be obtained. Three of the ten challenge streams assessed had maximum possible cost savings predictions >20%, and associated reductions in process energy carbon intensity ranging from 0 to 54%. Two streams had cost and energy savings potential that were < 5%. Some of the opportunity drivers from the various assessments include higher product yields, reduction or elimination of downstream equipment, new co-products, and cost savings associated with raw materials and energy consumption. The information from these assessments can help guide the selection or development of new separation technology solutions based on the various potential factors that drive the projected benefits.

09 BIOMASS FUELS↗
DOE OSTI2020

Impact of particle arrays on phase separation composition patterns

We examine the symmetry-breaking effect of fixed constellations of particles on the surface-directed spinodal decomposition of binary blends in the presence of particles whose surfaces have a preferential affinity for one of the components. Our phase-field simulations indicate that the phase separation morphology in the presence of particle arrays can be tuned to have a continuous, droplet, lamellar, or hybrid morphology depending on the interparticle spacing, blend composition, and time. In particular, when the interparticle spacing is large compared to the spinodal wavelength, a transient target pattern composed of alternate rings of preferred and non-preferred phases emerges at early times, tending to adopt the symmetry of the particle configuration. We reveal that such target patterns stabilize for certain characteristic length, time, and composition scales characteristic of the pure phase-separating mixture. To illustrate the general range of phenomena exhibited by mixture-particle systems, we simulate the effects of single-particle, multi-particle, and cluster–particle systems having multiple geometrical configurations of the particle characteristic of pattern substrates on phase separation. Our simulations show that tailoring the particle configuration, or substrate pattern configuration, a relative fluid-particle composition should allow the desirable control of the phase separation morphology as in block copolymer materials, but where the scales accessible to this approach of organizing phase-separated fluids usually are significantly larger. Limited experiments confirm the trends observed in our simulations, which should provide some guidance in engineering patterned blend and other mixtures of technological interest.

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

Chemically Enhanced Electrodialysis (CEED) for Recovery of Rare Earth Elements

Rare-earth elements are crucial for numerous technologically relevant industries including energy, electronics, and aerospace; however, both the supply and separation of rare earths are pressing challenges. The long-term goal of the collaborative project is to develop a novel approach to existing extraction behaviors. To achieve this goal, a class of electrodialysis membranes with novel ion-gating functionality will be developed and paired with a conventional electrodialysis strategy. The hypothesis of the work is that incorporating sequestrants of suitable structures at the surface of the electrodialysis membrane will enhance extraction efficiency for ions of interest. Our ability to prepare sequestrants of diverse conformations and to adapt their molecular structure for binding lanthanides renders the proposed technology a versatile method for selective ion separation. Our approach will enable an entirely new technological approach to the separation of valuable rare-earth elements.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Extrapolation of the Rainflow-Counted Load Ranges for Fatigue Assessment of the Wind Turbine's Blades

Wind turbine design standards recommend the use of statistical modeling coupled with extrapolation of the short-term load data to long-term periods for fatigue reliability assessment. However, statistical error and computational expense can limit the accuracy of such approaches. In the case of wind turbine blades, the errors are more significant because of the high material fatigue exponent that makes the damage estimations more sensitive to variations. In addition, due to different excitation sources, the flapwise load range histogram is not unimodal, and thus its statistical modeling is complex. In the present work, we provide three methods for statistical modeling of the flapwise bending moment ranges including a novel approach based on frequency-based separation of the modes. The first two methods are simplified approaches for modeling the most crucial load ranges using unimodal distributions and the third method involves multimodal distribution fitting. The research is based on 3600 10-minute aeroelastic simulations of DTU 10MW case study wind turbine from which a benchmark damage equivalent load (DEL) is calculated. The DEL calculated by each of the three proposed methods is compared to this reference. The results show that the conventional approach based on using 6 seeds as well as using mixture models fitted on the limited data lead to under-conservative results with errors up to 23%. On the other hand, the simplified unimodal approaches provided in this work can provide conservative estimations of the fatigue damage with mean values 5% and 12% higher than the benchmark. However, the variability of the DEL estimates is higher when using unimodal extrapolation of the load ranges, and the data can be conservative by 17.5%. The proposed unimodal fits suggested for modeling and extrapolation of the blade's load ranges provide less errors relatively and most importantly conservative DEL estimations while maintaining computational efficiency.

blade fatigue↗