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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Influence of Hydrogen Isotopes on Vacancy Formation and Antisite Defect Diffusion in Palladium and Vanadium Metals

Density functional theory calculations are performed to study the interaction between hydrogen isotopes, vacancy, and antisite defects in Pd and V. Various defect configurations and defect-defect distances are systematically explored. Binding energies and migration energy barriers are calculated and tabulated. The study provides atomistic data for subsequent mesoscale simulations of tritium, vacancy, and antisite diffusion. In Pd, a strong binding is found between a vacancy and tritium (0.16 eV). This tritium binding increases the thermal concentration of vacancies by a factor of ~10 at 500 ?C. The increase in vacancy concentration enhances V antisite diffusion in Pd by a factor of ~6 at 500 ?C. The influence of tritium is even stronger in V, with a tritium and vacancy binding energy of 0.38 eV. Such a strong binding increases the thermal concentration of vacancies by a factor of ~300 at 500 ?C. The increase in vacancy concentration enhances Pd antisite diffusion in V by a factor of ~640 at 500 ?C. Vanadium and Pd exhibit a strong driving force to intermix with a formation energy of -1.57 eV for V antisite in Pd and -1.05 eV for Pd antisite in V. The results suggest vanadium diffusion into Pd is energetically stronger than the reverse. Zero-point-energy corrections are taken into account and calculations for hydrogen and tritium are presented.

Setyawan, Wahyu↗
DOE OSTI2021

Simulating low-energy neutrino interactions with MARLEY

Monte Carlo event generators are a critical tool for the interpretation of data obtained by neutrino experiments. Several modern event generators are available which are well-suited to the GeV energy scale used in studies of accelerator neutrinos. However, theoretical modeling differences make their immediate application to lower energies difficult. In this paper, I present a new event generator, MARLEY, which is designed to better address the simulation needs of the low-energy (tens of MeV and below) neutrino community. The code is written in C++14 with an optional interface to the popular ROOT data analysis framework. The current release of MARLEY (version 1.2.0) emphasizes simulations of the reaction 40 Ar ( ν e , e − ) 40 K ⁎ but is extensible to other channels with suitable user input. This paper provides detailed documentation of MARLEY's implementation and usage, including guidance on how generated events may be analyzed and how MARLEY may be interfaced with external codes such as Geant4. Further information about MARLEY is available on the official website at http://www.marleygen.org. Program title:MARLEY 1.2.0 CPC Library link to program files:https://doi.org/10.17632/4v7zxnc8j3.1 Developer's respository link:http://github.com/MARLEY-MC/marley Code Ocean capsule:https://codeocean.com/capsule/9868179 Licensing provisions: GNU General Public License 3.0 Programming language: C++14 External routines/libraries used: GNU Scientific Library [1,2] (required), ROOT [3,4] (optional) Nature of problem: Simulation of neutrino-nucleus scattering events at energies of tens-of-MeV and below Solution method: Initial two-to-two scattering kinematics are sampled using the allowed approximation differential cross section and tables of precomputed nuclear matrix elements. Subsequent de-excitations of the remnant nucleus are simulated using a Monte Carlo implementation of the Hauser-Feshbach statistical model and tabulated γ-ray decay schemes for discrete nuclear levels. Additional comments including restrictions and unusual features: Input data are provided with the code that are suitable for producing simulations of the charged-current reaction 40 Ar ( ν e , e − ) 40 K ⁎ , coherent elastic neutrino-nucleus scattering on spin-zero target nuclei, and neutrino-electron elastic scattering on any atomic target. Preparation of new reaction input files (whose format is documented in Appendix B) would enable other reaction channels and nuclear targets to be handled by the existing code framework. Although there is no maximum neutrino energy enforced by the code itself, realistic neutrino-nucleus scattering events may be generated up to roughly 50 MeV. Above this energy, the effects of forbidden nuclear transitions, which are neglected in the current treatment of the cross sections (see section 2.1), become increasingly important.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Thermo4PFM: Facilitating Phase-field simulations of alloys with thermodynamic driving forces

Phase-field modeling is a popular front-tracking approach used to model solidification. Its time-evolution equations are often coupled to alloy composition and/or thermal diffusion in high-resolution multiphysics approaches. Materials thermodynamic properties tabulated in CALPHAD databases can be used for phase-field modeling to parameterize bulk energies of alloys. In addition, they can be naturally integrated into models such as the Kim-Kim-Suzuki (KKS) model where driving forces depend on the differences between chemical potentials of co-existing phases. In that case, a small system of coupled nonlinear equations needs to be solved at every point in space where the phase-field order parameter is to be updated and evolved in time. Here we present Thermo4PFM, a solver for the KKS equations for binary and ternary alloys, with two or three phases, and parameterized with CALPHAD models. Thermo4PFM is open source, written in C++, and can take advantage of Graphics Processing Units (GPU) accelerators. Using OpenMP offload capabilities for C++ classes, an excellent performance is demonstrated on GPU using the LLVM compiler. CALPHAD data is read from simple JSON files using an open source parser from the boost library.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Explicit quantification of residence and flushing times in the Salish Sea using a sub-basin scale shoreline resolving model

The Salish Sea, located in the Pacific Northwest region of North America has complex currents and circulation features distributed over numerous interconnected deep basins with islands. Increased risk of exposure to oil spills and untreated wastewater from maritime emergencies and treatment plant failures have led to a need for quantifying residence and flushing characteristics at a sub-basin scale using a shoreline resolving hydrodynamic model. An unstructured grid model of the Salish Sea was developed using FVCOM with a ≈75-100m shoreline resolution. In addition to 7 tides and 23 salinity and temperature monitoring stations, an extensive currents data set from 135 stations collected over a span of three years was used for skill assessment and validation. Explicit forward computations were then conducted to define and quantify residence and flushing times in various sub-basins of interest using (a) Lagrangian particles and (b) Numerical/virtual dye experiments. The results in most basins show expected seasonal variability with longer flushing time associated with summer lower tides and lower freshwater inflows. However, contrary to expectation, flushing time is significantly longer in wintertime in large fjord-like basins such as Hood Canal (≈138 days), likely due to increased stratification and reduced mixing. The flushing time for the Puget Sound region of the Salish Sea is ≈115 days, while Georgia Basin is 240 days when analyzed as stand-alone basins with zero background concentrations. When examined as part of the flushing of the entire Puget Sound filled with virtual dye, the compounded flushing times for embedded sub-basins can be significantly longer in order of magnitudes and largely dictated by the flushing time of Puget Sound. The computed residence and flushing time scales tabulated over 36 sub-basins provide an improved understanding of water renewal in the system, informing pollution management actions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Daylight simulation workflows incorporating measured bidirectional scattering distribution functions

Daylight predictions of architectural spaces depend on good estimates of light transfer through skylights, windows and other fenestration systems. For clear glazing and painted surfaces, parametric transmission and reflection models have proven adequate, but there are many cases where light-scattering, semi-specular shading and daylighting materials defy simple characterization. Something as commonplace as fabric roller shades and venetian blinds may turn daylight prediction into guesswork, and numerous advanced systems on the market tuned specifically to enhance daylight are not sufficiently characterized to distinguish their performance. In this paper, we describe new tools available to handle novel and specialized fabrics, materials, and devices using data-driven modelling of bi-directional scattering distribution functions (BSDFs). These representations are usually tabulated at constant or adjustable angular resolution for efficient point-in-time and annual daylight simulations. We describe a variety of BSDF simulation workflows, including some of the tools and methods that make advanced analysis possible, and highlight some of the current challenges. We conclude with a discussion of future work and how such data might be created and shared worldwide.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Field validation of data-driven BSDF and peak extraction models for light-scattering fabric shades

Shading and daylighting systems affect cooling, heating, and lighting energy use by modulating solar radiation through the building façade. Characterizing shading systems holistically and accurately helps designers and engineers evaluate shading systems to achieve energy and non-energy performance goals. These complex fenestration systems can be modeled using Bidirectional Scattering Distribution Functions (BSDF), which map incident radiation to hemispherical distributions of outgoing radiation. Data-driven, tabulated BSDFs are derived from interpolated goniophotometer measured data, then sampled during the raytracing calculation. A peak extraction (PE) algorithm was developed to circumvent limits in BSDF angular resolution, where the specular peak is extracted during simulation by evaluating the BSDF in the through direction and surrounding region. The objective of this study was to validate this measurement and modeling workflow using field monitored data from a full scale testbed with eleven installed fabrics of different weaves, openness factors, and colors and assess the accuracy of the workflow under different adaptation and contrast conditions. Test conditions were limited to clear sky conditions with the sun in the field of view. Results showed that, for tensor tree datasets, vertical illuminance, solar luminance (2.5° apex), and daylight glare probability (DGP) were predicted to within a mean bias error (MBE) error of -456 lx (-12.3%), -3.46e5 (-38.4%), and -0.042 (-7.8%) when full PE occurred. With a binary classification of glare/ no glare, DGP was predicted accurately with a true positive rate of 0.98 and true negative rate of 1.0 using tensor tree data and less accurately with Klems BSDF data, particularly for cases of no glare. The workflow may be of insufficient accuracy to distinguish borderline performance between fabrics using the four-point glare scale, particularly under low adaptation, high contrast daylit conditions. Errors were due to reductions in peak shape and intensity across the BSDF interpolation and data reduction workflow. Future work is needed to better preserve measurement fidelity during interpolation and sampling, which in turn will improve PE performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Hydrothermal solution calorimetry in acidic aqueous solutions and revisiting the standard partial molal thermodynamic properties of Nd 3+ from 25 to 300 °C

The mobility of rare earth elements (REE) can be predicted in aqueous fluids using geochemical modeling but the accuracy of these models strongly depends on the availability of robust thermodynamic properties for the REE aqueous species. The REE 3+ aqua ions are important in the derivation of the formation constants of all the major REE complexes including the chloride, sulfate, and fluoride species which predominate in many hydrothermal-magmatic systems. However, the thermodynamic properties of the REE 3+ aqua ions are still commonly derived from the Helgeson-Kirkham-Flowers (HKF) equation of state parameters tabulated several decades ago. The standard state thermodynamic properties at reference conditions (25 °C and 1bar) and their extrapolations to high temperature need to be verified, if not revised, based on hydrothermal experiments. In this study, the enthalpy of solution was measured for synthetic Nd hydroxide from 25 to 150 ºC to retrieve the standard partial molal thermodynamic properties of Nd 3+ as a function of temperature. The experiments were conducted in aqueous perchloric acid based solutions with starting pH of 2 and varying ionic strength (0.01 to 0.09 mol/kg NaClO 4 ). The standard partial molal enthalpy of formation (Δ f H°) of Nd 3+ derived from the experimental study displays differences of up to 10 kJ/mol compared to the enthalpy values derived from the HKF equation of state in the studied temperature range. These inaccuracies are resolved by adjusting the standard partial molal Gibbs energy of formation (Δ f G°) of Nd 3+ at 25 °C and 1 bar from -672.0 to -679.7 kJ/mol. The heat capacity function (C p °) derived between 25 and 150 ºC can be described by: C p ° = a 0 + a 1 ·T + a 2 ·T -2 , with a 0 = 1256, a 1 = -2.68, a 2 = -55.56·10 6 and T in Kelvin. A set of recommended thermodynamic properties is provided for the Nd 3+ aqua ions and corrections are provided for the chloride and fluoride species to remain internally consistent with the experimentally derived properties. These results allow predicting accurately the solubility of monazite between 25 and 300 ºC. Before these corrections, the properties for the Nd 3+ aqua ions derived from the HKF parameters resulted in up to ~1.5 orders of magnitude lower monazite solubility than determined experimentally. Here, a revision of the REE +3 aqua ions properties is necessary to accurately predict the mobility of REE in hydrothermal acidic solutions.

58 GEOSCIENCES↗
DOE OSTI2023

Hard and semi-hard Fe-based magnetic materials

Iron (Fe) is the most important ferromagnetic element, not only for its high magnetic moment and high Curie temperature but for its abundance as well. Fe-based magnetic materials are therefore widely applied in technologies and industries, with most of the applications for soft magnetic materials, because of the low magnetocrystalline anisotropy (MCA) of Fe. However, it is possible to realize magnetic hardening in Fe-based materials as we have learned from the early carbon steel permanent magnets although their coercivity was modest. Recent efforts to search for rare-earth-free hard magnetic materials have shown more promising evidences for achieving high MCA in Fe-based materials. In this paper, we review the history and the recent developments of Fe-based hard and semi-hard magnetic materials with a focus on mechanisms of high MCA in Fe-based phases and the related crystal and electronic structures. Here, we have tabulated and discussed the structures and the magnetic properties of the Fe-based binary or ternary systems containing p-block and d-block elements, with many of them showing considerable MCA. Furthermore, it is important to know and to understand that the MCA in Fe-based magnetic materials can be tailored/enhanced through chemical and/or structural modifications that will lead to “artificially engineered” hard and semi-hard magnetic materials for advanced permanent magnets in the future.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space

In this work, we introduce a data-driven approach to building reduced dynamical models through manifold learning; the reduced latent space is discovered using Diffusion Maps (a manifold learning technique) on time series data. A second round of Diffusion Maps on those latent coordinates allows the approximation of the reduced dynamical models. This second round enables mapping the latent space coordinates back to the full ambient space (what is called lifting); it also enables the approximation of full state functions of interest in terms of the reduced coordinates. In our work, we develop and test three different reduced numerical simulation methodologies, either through pre-tabulation in the latent space and integration on the fly or by going back and forth between the ambient space and the latent space. The data-driven latent space simulation results, based on the three different approaches, are validated through (a) the latent space observation of the full simulation through the Nyström Extension formula, or through (b) lifting the reduced trajectory back to the full ambient space, via Latent Harmonics. Latent space modeling often involves additional regularization to favor certain properties of the space over others, and the mapping back to the ambient space is then constructed mostly independently from these properties; here, we use the same data-driven approach to construct the latent space and then map back to the ambient space.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The low-temperature heat capacity and thermodynamic properties of greigite (Fe 3 S 4 )

Heat capacity measurements provide important insights into the energetic, thermodynamic, and magnetic properties of materials. Herein we report the heat capacity of greigite (Fe 3 S 4 ) from 1.8 to 300 K. Greigite is a magnetic spinel mineral and through a ferromagnetic magnon term, C fsw = B fsw T 3/2 , ferrimagnetic ordering is observed in the low-temperature heat capacity. Using a set of theoretical fits of the experimental data, we calculate the thermodynamic functions, including the standard entropy ($Δ_{0}^{T}$S m °). Greigite is important in iron sulfide formation and reaction pathways in environmental, ore-forming, and technological settings and previous work has measured enthalpies $ΔH_{r}°$ of formation and decomposition to neighboring phases. In this work, the stability of greigite relative to the elements is demonstrated with a negative Gibbs energy ($ΔG_{r}°$) of formation and the stability relative to decomposition products of pyrrhotite (FeS 1.092 ) and pyrite (FeS 2 ) is demonstrated with a positive Gibbs energy ($ΔG_{r}°$) of decomposition. Values of the standard thermodynamic functions C p,m °, $Δ_{0}^{T}$S m °, $Δ_{0}^{T}$H m °, and Φ m ° are tabulated.

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

Projected network performance for next-generation xenon monitoring systems

Next-generation radioxenon monitoring systems are reaching maturity and are expected to improve certain aspects of performance in verifying the absence of nuclear tests. To predict the improvement in detecting and locating nuclear releases, thousands of releases all over the globe were simulated and the global detection probability was calculated. This was done for the International Monitoring System network of noble gas samplers as it currently exists (25 certified stations), and how it would be for potential future network sizes of 39 and 79 stations. The probability of detection was calculated for releases ranging from 10 10 Bq to 10 16 Bq of 133 Xe and presented as coverage maps and global integrals for both current and next-generation monitoring systems. Similarly, the number of detecting stations and the number of detecting samples were tabulated to elucidate the possibilities for enhanced location capability. Improvements in global detection coverage are maximized at different release sizes in a way that depends on the station density. For example, for releases of 3×10 14 Bq and 39 stations, the detection probability would rise from 60% to 70% with next-generation systems, while for releases of 10 13 Bq and 79 stations, it would rise from 37% to 52%. Achieving an average of two detecting stations requires a 1015 Bq release for a 39-station network and a 10 14 Bq release for a 79-station network. The largest impact of using next-generation systems may be the confidence, failure tolerance, and location capability that arise from obtaining multiple samples associated with a single release event.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Memory-efficient emulation of physical tabular data using quadtree decomposition

Computationally expensive functions are sometimes replaced in simulations with an emulator that approx-imates the true function (e.g., equations of state, wavelength-dependent opacity, or composition-dependent materials properties). For functions that have a constrained domain of interest, this can be done by discretizing the domain and performing a local interpolation on the tabulated function values of each local domain. For these so-called tabular data methods, the method of discretizing the domain and mapping the input space to each subdomain can drastically influence the memory and computational costs of the emulator. This is especially true for functions that vary drastically in different regions. We present a method for domain discretization and mapping that utilizes quadtrees, which results in significant reductions in the size of the emulator with minimal increases to computational costs or loss of global accuracy. We apply our method to the electron-positron Helmholtz free energy equation of state and show over an order of magnitude reduction in memory costs for reasonable levels of numerical accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Thermal expansion of 4H and 6H SiC from 5 K to 340 K

The first thermal expansion measurements of the 4H and 6H polytypes of SiC below room temperature are reported. The measurements were carried out on single-crystal specimens using high-resolution capacitive-based dilatometry. For both polytypes, the thermal expansion coefficient is below 2.4 × 10 -6 1/K near room temperature. No phase transitions are observed over the 5 K to 340 K temperature range of the measurements. The thermal expansion coefficient α of 4H SiC is slightly anisotropic for measurements parallel and perpendicular to the crystallographic c axis with α ∥ about 2.2 × 10 -7 1/K larger than α ⟂ near room temperature. For 6H SiC no discernible anisotropy is observed. The differences in anisotropy can be understood by considering the ratio of hexagonal to cubic bonds of each polytype. Narrow regions with negative thermal expansion that are within the limits of our resolution (~ 1 x 10 -8 ) are observed in the vicinity of 30 K for both specimens. In conclusion, tabulated data, polynomial fits, fit parameters, and comparison to data based on lattice-parameter measurements are provided.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Beyond green with synthetic chlorophylls – Connecting structural features with spectral properties

The distinct features of chlorophylls in photosynthesis have led to the formation of numerous derivatives for applications encompassing solar energy conversion, molecular photonics, photodynamic therapy, and molecular imaging. Synthetic chlorins created de novo and bearing a geminal dimethyl group in the reduced ring have proved invaluable for fundamental studies. Four decades of research have led to accumulation of tabulated spectra for > 400 such synthetic chlorins with distinct structural frameworks (17-oxochlorins, 13 1 -oxophorbines, chlorinimides) and substituents (alkyl, aryl, ethynyl, phenylethynyl, acetyl, formyl) located at specific (meso, β) positions. In this review, spectral traces (324 absorption, 247 fluorescence) are assembled along with photophysical data including the molar absorption coefficient (ε), fluorescence quantum yield (Φ f ) and singlet excited-state lifetime (τ s ). The review uses the accumulated spectral data derived from chlorins all containing a uniform molecular scaffold to (1) highlight the effects of molecular structure on spectral features, and (2) identify trends including how ε, Φ f and τ s vary with wavelength and other features. Use of a common geminal-dimethyl-substituted chlorin scaffold – beginning with no substituents, to one substituent at designated sites, and to 2 or more substituents – provides a systematic Aufbau approach for understanding the absorption spectra of chlorins on a path to and beyond the native chlorophylls. Finally, the review provides insights concerning the rational design of potent analogues of Nature’s preeminent red-region absorbers for potential utilization in diverse applications and is aimed at multiple audiences: those interested in spectral properties, tetrapyrrole photophysics, and the molecular design of new chromophores.

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

Stopping Force Analysis of 235 U Elemental Fission Product Yields for $E_n$ = 0.11–92.4 MeV

We report most evaluated elemental fission product yield distributions are not experimentally measured. Instead, the majority of evaluated distributions are based on analytic expressions of the Zp-model for relevant cumulative yields. Here we report independent elemental fission product yield distributions of a 235 U target for incident neutron energies ranging from 0.11 MeV through 92.4 MeV. Atomic numbers are calculated by an approach that combines a 2E analysis with a stopping force analysis method, developed within this paper. These analyses are applied to more than 6.1 × 10 6 fission fragment ionization tracks captured within the NIFFTE (Neutron Induced Fission Fragment Tracking Experiment) collaboration fission time projection chamber (fissionTPC). A 3-Z resolution was obtained with the fissionTPC spatial and energy resolutions. Tabulated results are presented for the atomic yield and experimentally derived Zp values as a function of pre-neutron-emission fragment masses for the complete range of incident neutron energies. The stopping-force-derived Zp values tend to support the unchanged charge distribution theory within uncertainty.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Direct local parametrization of nuclear state densities using the back-shifted Bethe formula

Level densities are often parametrized using the back-shifted Bethe formula (BBF) for nuclei that possess experimental data for s-wave neutron resonance average spacings and a complete discrete level sequence at low excitation energies. However, these parametrizations require the additional modeling of the dependence of the spin-cutoff parameter on excitation energy. Here, in this work, we avoid the need to model the spin distribution of level densities by using the experimental data to parametrize directly the state densities, for which the BBF does not depend on the spin-cutoff parameter. This approach allows for a local parameterization of state densities that is independent of the spin-cutoff parameter. We provide these parameters in a tabulated form for applications in nuclear reaction calculations and for testing microscopic approaches to state densities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Rotor blade imbalance fault detection for variable-speed marine current turbines via generator power signal analysis

Marine hydrokinetic (MHK) turbines extract renewable energy from oceanic environments. However, due to the harsh conditions that these turbines operate in, system performance naturally degrades over time. Thus, ensuring efficient condition-based maintenance is imperative towards guaranteeing reliable operation and reduced costs for marine hydrokinetic power. This work proposes a novel framework aimed at identifying and classifying the severity of rotor blade pitch imbalance faults experienced by marine current turbines (MCTs). In the framework, a Continuous Morlet Wavelet Transform (CMWT) is first utilized to acquire the wavelet coefficients encompassed within the 1P frequency range of the turbine's rotor shaft. From these coefficients, several statistical indices are tabulated into a six-dimensional feature space. Next, Principle Component Analysis (PCA) is employed on the resulting feature space for dimensionality reduction, and then the application of a K-Nearest Neighbor (KNN) machine learning algorithm is utilized for fault detection and severity classification. The effectiveness of the proposed framework is validated using a high-fidelity MCT numerical simulation platform, where results demonstrate that the presence of a pitch imbalance fault can be accurately detected 100% of the time and correctly classified based upon severity more than 97% of the time.

42 ENGINEERING↗