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At least 523 records · Page 29

Real-Time Wave Energy Converter Control Using Instantaneous Frequency

Wave Energy Converters (WECs) rely on effective Power Take-Off (PTO) control strategies to maximize energy absorption under dynamic sea conditions. Traditional hydrodynamic modeling techniques may require computationally intensive convolution calculations, making real-time control implementation challenging. This paper presents an alternative approach by leveraging instantaneous frequency estimation to dynamically adjust PTO damping in response to varying wave frequencies. Two real-time frequency estimation methods are explored: the Hilbert Transform (HT) and Phase-Locked Loop (PLL). The Hilbert Transform method provides accurate frequency tracking but introduces a delayed response due to its dependence on causal data. Conversely, the PLL approach demonstrates strong potential in frequency tracking but requires careful gain tuning, particularly in complex sea states. Comparative evaluations across multiple test cases—including sinusoidal variations, amplitude steps, frequency step changes, and real-world JONSWAP spectrum waves—highlight the strengths and limitations of each method. The two different PTO control techniques across the various frequency estimation methods were tested under real-sea states using a state-space model of a point-absorbing Wave Energy Converter. The Capture Width Ratio (CWR) is used as a performance metric, with results showing that the HT achieves a 10.6% improvement, while the PLL estimation yields a 0.9% improvement relative to the fixed parameter control baseline. These results highlight the effectiveness of real-time frequency estimation in improving energy absorption compared to static control parameters.

WEC control↗

Twisted holography on AdS$_3 \times S^3 \times$ K3 & the planar chiral algebra

In this work, we revisit and elaborate on twisted holography for AdS _3 × S^3 × X 3 × S 3 × X with X= T^4 X = T 4 , K3, with a particular focus on K3. We describe the twist of supergravity, identify the corresponding (generalization of) BCOV theory, and enumerate twisted supergravity states. We use this knowledge, and the technique of Koszul duality, to obtain the N → ∞ N → ∞ , or planar, limit of the chiral algebra of the dual CFT. The resulting symmetries are strong enough to fix planar 2 and 3-point functions in the twisted theory or, equivalently, in a 1/4-BPS subsector of the original duality. This technique can in principle be used to compute corrections to the chiral algebra perturbatively in 1/N 1 / N .

Fernández, Víctor E.↗

Advanced EXAFS analysis techniques applied to the L -edges of the lanthanide oxides

The unique properties of the lanthanide (Ln) elements make them critical components of modern technologies, such as lasers, anti-corrosive films and catalysts. Thus, there is significant interest in establishing structure–property relationships for Ln-containing materials to advance these technologies. Extended X-ray absorption fine structure (EXAFS) is an excellent technique for this task considering its ability to determine the average local structure around the Ln atoms for both crystalline and amorphous materials. However, the limited availability of EXAFS reference spectra of the Ln oxides and challenges in the EXAFS analysis have hindered the application of this technique to these elements. The challenges include the limited k-range available for the analysis due to the superposition of L-edges on the EXAFS, multielectron excitations (MEEs) creating erroneous peaks in the EXAFS and the presence of inequivalent absorption sites. Herein, we removed MEEs to model the local atomic environment more accurately for light Ln oxides. Further, we investigated the use of cubic and non-cubic lattice expansion to minimize the fitting parameters needed and connect the fitting parameters to physically meaningful crystal parameters. The cubic expansion reduced the number of fitting parameters but resulted in a statistically worse fit. The non-cubic expansion resulted in a similar quality fit and showed non-isotropic expansion in the crystal lattice of Nd 2 O 3 . In total, the EXAFS spectra and the fits for the entire set of Ln oxides (excluding promethium) are included. The knowledge developed here can assist in the structural determination of a wide variety of Ln compounds and can further studies on their structure–property relationships.

36 MATERIALS SCIENCE↗

Metal–Organic Framework-Based Microfluidic Impedance Sensor Platform for Ultrasensitive Detection of Perfluorooctanesulfonate

The growing global concerns to public health from human exposure to perfluorooctanesulfonate (PFOS) requires rapid, sensitive, in-situ detection where current, state-of-the-art techniques are yet to adequately meet sensitivity and selectivity standards of the real-world. This work presents, for the first time, a synergistic approach for the targeted affinity-based capture of PFOS using a porous sorbent probe that enhances detection sensitivity by embedding it on a microfluidic conductive platform. This novel sorbent-containing platform functions as an electrochemical sensor to directly measure PFOS concentration through a proportional change in electrical response (increase in impedance). The extremely high surface area and pore volume of mesoporous metal-organic framework (MOF) Cr-MIL-101 is used as the probe for targeted PFOS capture based on the affinity of the chromium center towards both the fluorine tail groups as well as the sulfonate functionalities as demonstrated by spectroscopic (NMR and XPS) and microscopic (TEM) studies. Answering the need for an ultrasensitive PFOS detection technique, we are embedding these MOF capture probes inside a microfluidic channel, sandwiched between interdigitated microelectrodes (IDµE). The nanoporous geometry increases the signal to noise ratio of interdigitated microelectrodes tremendously increasing sensitivity; this in combination with the ability of the capture probes to interact with the PFOS at the molecular level and effectively transduce that response electrochemically has allowed us achieve a PFOS detection limit of 0.5 ng/L, which is unprecedented for in-situ analytical PFOS sensors and even comparable to quantification limits achieved using state-of-the-art ex situ techniques.

36 MATERIALS SCIENCE↗

Simultaneous bright- and dark-field X-ray microscopy at X-ray free electron lasers

Abstract The structures, strain fields, and defect distributions in solid materials underlie the mechanical and physical properties across numerous applications. Many modern microstructural microscopy tools characterize crystal grains, domains and defects required to map lattice distortions or deformation, but are limited to studies of the (near) surface. Generally speaking, such tools cannot probe the structural dynamics in a way that is representative of bulk behavior. Synchrotron X-ray diffraction based imaging has long mapped the deeply embedded structural elements, and with enhanced resolution, dark field X-ray microscopy (DFXM) can now map those features with the requisite nm-resolution. However, these techniques still suffer from the required integration times due to limitations from the source and optics. This work extends DFXM to X-ray free electron lasers, showing how the $$10^{12}$$ 10 12 photons per pulse available at these sources offer structural characterization down to 100 fs resolution (orders of magnitude faster than current synchrotron images). We introduce the XFEL DFXM setup with simultaneous bright field microscopy to probe density changes within the same volume. This work presents a comprehensive guide to the multi-modal ultrafast high-resolution X-ray microscope that we constructed and tested at two XFELs, and shows initial data demonstrating two timing strategies to study associated reversible or irreversible lattice dynamics.

47 OTHER INSTRUMENTATION↗

Johnson-noise-limited cancellation-free microwave impedance microscopy with monolithic silicon cantilever probes

Abstract Microwave impedance microscopy (MIM) is an emerging scanning probe technique for nanoscale complex permittivity mapping and has made significant impacts in diverse fields. To date, the most significant hurdles that limit its widespread use are the requirements of specialized microwave probes and high-precision cancellation circuits. Here, we show that forgoing both elements not only is feasible but also enhances performance. Using monolithic silicon cantilever probes and a cancellation-free architecture, we demonstrate Johnson-noise-limited, drift-free MIM operation with 15 nm spatial resolution, minimal topography crosstalk, and an unprecedented sensitivity of 0.26 zF/ √ Hz. We accomplish this by taking advantage of the high mechanical resonant frequency and spatial resolution of silicon probes, the inherent common-mode phase noise rejection of self-referenced homodyne detection, and the exceptional stability of the streamlined architecture. Our approach makes MIM drastically more accessible and paves the way for advanced operation modes as well as integration with complementary techniques.

47 OTHER INSTRUMENTATION↗

Quantitative Modeling of High-Energy Electron Scattering in Thick Samples Using Monte Carlo Techniques

Cryo-electron microscopy (cryo-EM) is a powerful tool for imaging biological samples but is typically limited by sample thickness, which is restricted to a few hundred nanometers depending on the electron energy. However, there is a growing need for imaging techniques capable of studying biological samples up to 10 µm in thickness while maintaining nanoscale resolution. This need motivates the use of mega-electron-volt scanning transmission electron microscopy (MeV-STEM), which leverages the high penetration power of MeV electrons to generate high-resolution images of thicker samples. In this study, we employ Monte Carlo simulations to model electron–sample interactions and explore the signal decay of imaging electrons through thick specimens. By incorporating material properties, interaction cross-sections for energy loss, and experimental parameters, we investigate the relationship between the incident and transmitted beam intensities. Key factors such as detector collection angle, convergence semi-angle, and the material properties of samples were analyzed. Our results demonstrate that the relationship between incident and transmitted beam intensities follows the Beer–Lambert law over thicknesses ranging from a few microns to several tens of microns, depending on material composition, electron energy, and collection angles. The linear depth of silicon dioxide reaches 3.9 µm at 3 MeV, about 6 times higher than that at 300 keV. Meanwhile, the linear depth of amorphous ice reaches 17.9 µm at 3 MeV, approximately 11.5 times higher than that at 300 keV. These findings are crucial for advancing the study of thick biological and semiconductor samples using MeV-STEM.

36 MATERIALS SCIENCE↗

Phase-sensitive optomechanical amplifier for quantum noise reduction in laser interferometers

The sensitivity of future gravitational wave interferometers is expected to be limited throughout the detection band by quantum vacuum fluctuations, which can be reduced by applying quantum optics techniques such as squeezed vacuum injection. However, decoherence caused by optical losses in the readout chain will severely limit the effectiveness of such schemes. It was proposed that effect of losses in the final stage of detection can be mitigated by a phase-sensitive amplifier placed in between the output port of the interferometer and the photodetector. In this paper we propose to implement such amplification using an optomechanical device, study some of its practical limitations, and finally, discuss its applicability to next-generation gravitational-wave detectors.

79 ASTRONOMY AND ASTROPHYSICS↗

Hydro-chemo-mechanical phase field formulation for corrosion induced cracking in reinforced concrete

Steel corrosion induced cracking in reinforced concrete structures is often caused by volumetric straining at the steel-concrete interface. This volumetric strain is mainly controlled by the rate of generation of corrosion product, which depends on the diffusion of Cl{sup −} and dissolved O{sub 2} as well as the chemical reaction at the steel-concrete interface. While many numerical modeling techniques have been proposed to tackle this complex phenomenon, most have been limited to using staggered solution schemes, where the diffusion, chemical reaction, mechanical strain, and crack fields are solved for separately. Unfortunately, such approaches introduce numerical errors that can lead to unrealistic predictions. Therefore, a coupled solution, is needed to remove the formulation induced errors and understand this complex phenomenon. To provide a unifying solution framework for corrosion induced cracking in reinforced concrete, a phase field formulation is presented and implemented with FEM algorithms. The governing equations are derived from the system's free energy and Fick's law of diffusion. The proposed formulation was first validated in 1D by comparing the modeling results with the semi-analytical solution approximated via Laurent series to avoid singularities in the complex domain. 2D plane strain solutions to the embedded rebar undergoing corrosion induced cracking with pre-cracks are also presented and compared with the approximated solutions from linear elastic fracture mechanics theory (LEFM). The modeling of crack propagation enabled by the proposed formulation is also presented along with parametric studies to reveal the roles of the fracture toughness and permeability of the concrete on the corrosion induced cracking. A case study was also conducted on H-pile steel with concrete jackets to demonstrate the feasibility of modeling corrosion induced fracture in reinforced concrete structures with complex steel-concrete interfaces.

36 MATERIALS SCIENCE↗

Comparison of machine learning techniques to optimize the analysis of plutonium surrogate material via a portable LIBS device

The utilization of machine learning techniques has become commonplace in the analysis of optical emission spectra. These methods are often limited to variants of principal components analysis (PCA), partial-least squares (PLS), and artificial neural networks (ANNs). A plethora of other techniques exist and are well established in the world of data science, yet are seldom investigated for their use in spectroscopic problems. In this study, machine learning techniques were used to analyze optical emission spectra of laser-induced plasma from ceria pellets doped with silicon in order to predict silicon content. Additionally, a boosted regression ensemble model was created, and its predictive accuracy was compared to that of traditional PCA, PLS, and ANN regression models. Boosted regression tree ensembles yielded fits with R-squared (R2) values as high as 0.964 and mean-squared errors of prediction (MSEPs) as low as 0.074, providing the most accurate predictive model. Neural networks performed with slightly lower R2 values and higher MSEPs compared to the ensemble methods, thus indicating susceptibility to overfitting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Occupant-Centric Demand Response for Thermostatically-Controlled Home Loads

Efficiently managing energy usage to balance supply and demand on the electric grid is crucial, especially with the widespread deployment of distributed variable renewable electricity generation. This paper introduces two duty-cycle control methods for heating systems, adjusting thermostat setpoints to limit and shift electricity demand. The control approaches employ innovative techniques, such as adaptive duty cycling, to prioritize household thermal comfort while reducing peak demand. These control methods can respond to signals from the electric grid, including demand targets and time-of-use tariffs, and were tested physically on an electric furnace and heat pump in a test home during winter conditions in 2021 and 2022. The results are given as average demand reductions and energy use impacts with respect to the average indoor-outdoor temperature difference during the control period. For heat pumps, demand limiting control reduced power by 18.5% and 23.3% for indoor-outdoor temperature differences of 30°F and 40°F. Preheating-based demand shifting achieved reductions of 34.8% and 33.2% for the same temperature differences. Electric furnace tests showed demand reductions of 33.8% and 25.3% for demand limiting, and 56.1% and 45.7% for preheating-based demand shifting. These findings highlight the potential for innovative control methods to enhance grid efficiency and reduce energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Artificial Intelligence Techniques in Smart Grid: A Survey

The smart grid is enabling the collection of massive amounts of high-dimensional and multi-type data about the electric power grid operations, by integrating advanced metering infrastructure, control technologies, and communication technologies. However, the traditional modeling, optimization, and control technologies have many limitations in processing the data; thus, the applications of artificial intelligence (AI) techniques in the smart grid are becoming more apparent. This survey presents a structured review of the existing research into some common AI techniques applied to load forecasting, power grid stability assessment, faults detection, and security problems in the smart grid and power systems. It also provides further research challenges for applying AI technologies to realize truly smart grid systems. Finally, this survey presents opportunities of applying AI to smart grid problems. The paper concludes that the applications of AI techniques can enhance and improve the reliability and resilience of smart grid systems.

energy systems↗

Bridging Experiment and Theory to Reveal Compounds in K–Zn(Cd)–Bi Systems

This study investigates the facile hydride synthesis method guided by theoretical predictions to explore the K–T–Bi (T = Zn, Cd) phase spaces. Using an adaptive genetic algorithm (AGA) and density functional theory (DFT), candidate compositions are identified for experimental validation via a facile hydrides route, permitting experimental screening of K–Zn–Bi and “empty” K–Cd–Bi systems. The previously reported KZnBi and KZn 2 Bi 2 are synthesized alongside newly discovered KCdBi and KCd 2 Bi 2 . While the AGA and DFT predict the stability of these compounds, structural predictions align with the experiment only for KZnBi and KZn 2 Bi 2 . Single-crystal X-ray structure refinements confirm that KZnBi and KZn 2 Bi 2 adopt the hexagonal ZrBeSi- and tetragonal ThCr 2 Si 2 -structure types, respectively. KCdBi has tetragonal PbClF-structure type and KCd 2 Bi 2 belongs to the ThCr 2 Si 2 -structure type. A trend based on the ratio of the metal ionic radii allows to rationalize variation in the structure types within the ATBi family (A = Li–Cs), correctly identifying KCdBi as isostructural to NaZnBi. Thermal stability studied by high-temperature powder X-ray diffraction reveals that Zn-containing compounds melt at higher temperatures (821 K for KZn 2 Bi 2 ) than Cd-containing KCd 2 Bi 2 (635 K). This study highlights the efficacy of combining rapid synthesis techniques with predictive modeling, though structural predictions show some limitations in accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solid Phase Processing of Mg-Al-Mn-Ca for High Strength and Ductility

While rare-earth Mg alloys have remarkable properties for high strength applications, lower cost alternatives are necessary for the widespread industry use of Mg. Ca added Mg alloys have shown promise as an alternative to rare-earth alloys. Ca-based precipitates can reduce basal texture, reduce casting porosity, and increase mechanical strength. However, the accumulation of Ca-based precipitates along inter-dendritic regions can severely limit ductility. Here, we apply two solid phase processing techniques, friction stir processing and shear assisted processing and extrusion, to produce wrought microstructure sheet and extruded tubes from a cast Mg-Al-Mn-Ca alloy. Ductility of the alloy is enhanced by densification under applied force and elevated temperature, grain refinement, and refinement of (Al,Mg)-Ca based precipitate.

Garcia, David↗

N-jettiness beam functions at N3LO

We present the first complete calculation for the quark and gluon N -jettiness ( $$ {\mathcal{T}}_N $$ T N ) beam functions at next-to-next-to-next-to-leading order (N 3 LO) in perturbative QCD. Our calculation is based on an expansion of the differential Higgs boson and Drell-Yan production cross sections about their collinear limit. This method allows us to employ cutting edge techniques for the computation of cross sections to extract the universal building blocks in question. The class of functions appearing in the matching coefficents for all channels includes iterated integrals with non-rational kernels, thus going beyond the one of harmonic polylogarithms. Our results are a key step in extending the $$ {\mathcal{T}}_N $$ T N subtraction methods to N 3 LO, and to resum $$ {\mathcal{T}}_N $$ T N distributions at N 3 LL' accuracy both for quark as well as for gluon initiated processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ultrafast Laser Welding and Terahertz Time-domain Spectroscopy of Soda Lime Silicate Glass

Joining and welding techniques of similar and dissimilar materials have reached their limits due to the inflexibility of adapting dielectric materials, e.g., glasses and ceramics, reproducibility for transparent materials, and cycle process time. The ability to join pieces of glasses using laser irradiation allows rapid processing of vacuum insulating glass (VIG) for a widening range of commercial energy-efficient applications. We have used a 1064-nm laser wavelength with 15 picoseconds pulse width and a 155-kHz repetition rate to weld commercial plate glass pieces. The welded samples were characterized via x-ray fluorescence (XRF), time-of-flight secondary ion mass spectrometry (TOF–SIMS), polarimetry, and terahertz time-domain spectroscopy (THz-TDS) to determine the integrity of the weld and chemical changes in the welded areas. Our data shows no significant changes in glass chemistry and structure on average over nano- to micro-scales occurred from the welding process within the limits of the characterization tools. Our results demonstrate successful welding of glass plates without significant changes in the glass chemistry, structure, or properties in the laser-modified region or strains in the bulk glass.

Matthies, Kathleen [ORNL] (ORCID:0009000213135441)↗

Entropy–Preserving and Entropy–Stable Relaxation IMEX and Multirate Time–Stepping Methods

In this work, we propose entropy-preserving and entropy-stable partitioned Runge–Kutta (RK) methods. In particular, we extend the explicit relaxation Runge–Kutta methods to IMEX–RK methods and a class of explicit second-order multirate methods for stiff problems arising from scale-separable or grid-induced stiffness in a system. The proposed approaches not only mitigate system stiffness but also fully support entropy-preserving and entropy-stability properties at a discrete level. The key idea of the relaxation approach is to adjust the step completion with a relaxation parameter so that the time-adjusted solution satisfies the entropy condition at a discrete level. The relaxation parameter is computed by solving a scalar nonlinear equation at each timestep in general; however, as for a quadratic entropy function, we theoretically derive the explicit form of the relaxation parameter and numerically confirm that the relaxation parameter works the Burgers equation. Several numerical results for ordinary differential equations and the Burgers equation are presented to demonstrate the entropy-conserving/stable behavior of these methods. We also compare the relaxation approach and the incremental direction technique for the Burgers equation with and without a limiter in the presence of shocks.

97 MATHEMATICS AND COMPUTING↗