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At least 1,477 records · Page 82

Bayesian inference for plasmonic nanometrology

Here, we introduce a Bayesian method for the characterization of plasmonic nanoparticles, which is applicable to both near- and far-field problems. Designed to combine data generated from any photon-plasmon interaction experiment with physically motivated theoretical models, our approach leverages state-of-the-art Markov chain Monte Carlo sampling techniques and returns parameter estimates on nanometric scales. Simulated spectral data sets, describing resonant scattering of photons from ellipsoidal and toroidal nanoparticles, are explored as concrete examples of our approach, with the resulting Bayesian estimates showing excellent agreement with the ground truth, even under conditions of high statistical noise. By incorporating Bayes factors into the method as well, we reveal how model selection can determine which one of competing geometric shapes better explains the observed data. Our comprehensive nanometrology procedure can be tailored to a variety of light-particle interaction models, and its reliance on Bayesian inference furnishes automatic uncertainty quantification. In addition to applicability to a host of plasmonic configurations such as nanoparticle dimers, trimers, and array studies, it is proposed that the presented analysis can be extended to the quantum regime, where nonclassical photon statistics may provide additional insight for inference of scatterer properties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Solving nuclear structure problems with the adaptive variational quantum algorithm

Here we use the Lipkin-Meshkov-Glick (LMG) model and the valence-space nuclear shell model to examine the likely performance of variational quantum eigensolvers in nuclear-structure theory. The LMG model exhibits both a phase transition and spontaneous symmetry breaking at the mean-field level in one of the phases, features that characterize collective dynamics in medium-mass and heavy nuclei. We show that with appropriate modifications, the ADAPT-VQE algorithm, a particularly flexible and accurate variational approach, is not troubled by these complications. We treat up to 12 particles and show that the number of quantum operations needed to approach the ground-state energy scales linearly with the number of qubits. We find similar scaling when the algorithm is applied to the nuclear shell model with realistic interactions in the sd and pf shells. Although most of these simulations contain no noise, we use a noise model from real IBM hardware to show that for the LMG model with four particles, weak noise has no effect on the efficiency of the algorithm.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Hubble WFC3 Spectroscopy of the Habitable-zone Super-Earth LHS 1140 b

Atmospheric characterization of temperate, rocky planets is the holy grail of exoplanet studies. These worlds are at the limits of our capabilities with current instrumentation in transmission spectroscopy and challenge our state-of-the-art statistical techniques. Here we present the transmission spectrum of the temperate super-Earth LHS 1140b using the Hubble Space Telescope (HST). The Wide Field Camera 3 (WFC3) G141 grism data of this habitable-zone (T {sub eq} = 235 K) super-Earth (R = 1.7 R {sub ⊕}) shows tentative evidence of water. However, the signal-to-noise ratio, and thus the significance of the detection, is low and stellar contamination models can cause modulation over the spectral band probed. We attempt to correct for contamination using these models and find that, while many still lead to evidence for water, some could provide reasonable fits to the data without the need for molecular absorption although most of these cause features in the visible ground-based data which are nonphysical. Future observations with the James Webb Space Telescope would be capable of confirming, or refuting, this atmospheric detection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Aerodynamic Design of Complex Configurations Using Cartesian Methods and CAD Geometry

The objective for this paper is to present the development of an optimization capability for the Cartesian inviscid-flow analysis package of Aftosmis et al. We evaluate and characterize the following modules within the new optimization framework: (1) A component-based geometry parameterization approach using a CAD solid representation and the CAPRI interface. (2) The use of Cartesian methods in the development Optimization techniques using a genetic algorithm. The discussion and investigations focus on several real world problems of the optimization process. We examine the architectural issues associated with the deployment of a CAD-based design approach in a heterogeneous parallel computing environment that contains both CAD workstations and dedicated compute nodes. In addition, we study the influence of noise on the performance of optimization techniques, and the overall efficiency of the optimization process for aerodynamic design of complex three-dimensional configurations. of automated optimization tools. rithm and a gradient-based algorithm.

Nemec, Marian↗

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

Rai, Man Mohan↗

A Program to Detect and Characterize Extra-Solar Giant Planets

The upgrade to the AFOE spectrograph at the 1.5-m Tillinghast telescope at FLWO Observatory, described in detail in the previous progress report, was completed. Work included installing a new CCD detector (using SA0 internal funds) to replace the previous detector, which had failed after many thermal cyclings during the previous nearly ten years of operation. The new detector (a back-illuminated Marconi 2K x 2K detector) shows excellent quantum efficiency, and employs dual readout channels to keep the readout time as short as 20 seconds. Tests of the attainable radial velocity precision of the upgraded spectrograph with the new detector show an improvement in radial velocity detection efficiency by a factor of about 10 over the previous AFOE configuration, allowing us to push the photon-noise-limited doppler precision of 7 m/s to correspondingly fainter stars. This work was carried out by Co-investigator Sylvain Korzennik, along with the late Peter Nisenson.

Lindstrim, David↗

Quantifying dislocation-type defects in post irradiation examination via transfer learning

The quantitative analysis of dislocation-type defects in irradiated materials is critical to materials characterization in the nuclear energy industry. The conventional approach of an instrument scientist manually identifying any dislocation defects is both time-consuming and subjective, thereby potentially introducing inconsistencies in the quantification. This work approaches dislocation-type defect identification and segmentation using a standard open-source computer vision model, YOLO11, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on two alloys not represented in the training set. Inference of dislocation defects using transmission electron microscopy on three different irradiated alloys relevant to the nuclear energy industry are examined in this work with widely varying pixel noise levels and with completely unrelated composition and dislocation formations for practical post irradiation examination analysis. Code and models are available at https://github.com/idaholab/PANDA.

36 MATERIALS SCIENCE↗

Measurement and Characterization of Space Shuttle Solid Rocket Motor Plume Acoustics

Lift-off acoustic environments generated by the future Ares I launch vehicle are assessed by the NASA Marshall Space Flight Center (MSFC) acoustics team using several prediction tools. This acoustic environment is directly caused by the Ares I First Stage booster, powered by the five-segment Reusable Solid Rocket Motor (RSRMV). The RSRMV is a larger-thrust derivative design from the currently used Space Shuttle solid rocket motor, the Reusable Solid Rocket Motor (RSRM). Lift-off acoustics is an integral part of the composite launch vibration environment affecting the Ares launch vehicle and must be assessed to help generate hardware qualification levels and ensure structural integrity of the vehicle during launch and lift-off. Available prediction tools that use free field noise source spectrums as a starting point for generation of lift-off acoustic environments are described in the monograph NASA SP-8072: "Acoustic Loads Generated by the Propulsion System." This monograph uses a reference database for free field noise source spectrums which consist of subscale rocket motor firings, oriented in horizontal static configurations. The phrase "subscale" is appropriate, since the thrust levels of rockets in the reference database are orders of magnitude lower than the current design thrust for the Ares launch family. Thus, extrapolation is needed to extend the various reference curves to match Ares-scale acoustic levels. This extrapolation process yields a subsequent amount of uncertainty added upon the acoustic environment predictions. As the Ares launch vehicle design schedule progresses, it is important to take every opportunity to lower prediction uncertainty and subsequently increase prediction accuracy. Never before in NASA s history has plume acoustics been measured for large scale solid rocket motors. Approximately twice a year, the RSRM prime vendor, ATK Launch Systems, static fires an assembled RSRM motor in a horizontal configuration at their test facility in Utah. The remaining RSRM static firings will take place on elevated terrain, with the nozzle exit plume being mostly undeflected and the landscape allowing placement of microphones within direct line of sight to the exhaust plume. These measurements will help assess the current extrapolation process by direct comparison between subscale and full scale solid rocket motor data.

Kenny, Jeremy↗

Synthetic data-driven deep learning for label-free autonomous atomic force microscopy

Atomic force microscopy (AFM) is a widely used tool for nanoscale characterization across materials science, energy research, and biology. However, its adoption in high-throughput materials discovery and statistically driven studies remains limited by a strong dependence on expert operator input and by the scarcity of annotated experimental AFM datasets needed to enable data-driven automation. Here, we introduce SimuScan, a synthetic-data–driven framework that enables reliable AFM feature identification, segmentation, and targeted imaging without requiring large manually labeled experimental datasets. SimuScan generates tunable, high-fidelity synthetic AFM images of defined morphologies while incorporating realistic experimental artifacts, including tip–sample convolution, noise, flattening distortions, and surface debris. These datasets are shown to support scalable, label-free training of modern deep learning models for AFM analysis. When integrated into data-driven AFM workflows, SimuScan-trained models can locate and analyze nanoscale structures across large datasets and guide targeted follow-up imaging. We validate this approach on nanostructured surfaces, DNA assemblies, and bacterial cells, demonstrating robust generalization across diverse sample types with minimal operator intervention. More broadly, this work establishes a general strategy for generating explicitly conditioned, task-relevant synthetic data to improve the reliability of downstream models in autonomous microscopy.

Millan-Solsona, Ruben [Oak Ridge National Laborato↗

Dark energy survey year 3 results: weak lensing shape catalogue

ABSTRACT We present and characterize the galaxy shape catalogue from the first 3 yr of Dark Energy Survey (DES) observations, over an effective area of 4143 deg2 of the southern sky. We describe our data analysis process and our self-calibrating shear measurement pipeline metacalibration, which builds and improves upon the pipeline used in the DES Year 1 analysis in several aspects. The DES Year 3 weak-lensing shape catalogue consists of 100 204 026 galaxies, measured in the riz bands, resulting in a weighted source number density of neff = 5.59 gal arcmin−2 and corresponding shape noise σe = 0.261. We perform a battery of internal null tests on the catalogue, including tests on systematics related to the point spread function (PSF) modelling, spurious catalogue B-mode signals, catalogue contamination, and galaxy properties.

79 ASTRONOMY AND ASTROPHYSICS↗

Automated Extraction of Absorption Bands from Reflectance Special

A multiple high order derivative spectroscopy technique has been developed for deriving wavelength positions, half widths, and heights of absorption bands in reflectance spectra. The technique is applicable to laboratory spectra as well as medium resolution (100-200/cm) telescope or spacecraft spectra with moderate (few percent) noise. The technique permits absorption band positions to be detected with an accuracy of better than 3%, and often better than 1%. The high complexity of radiative transfer processes in diffusely reflected spectra can complicate the determination of absorption band positions. Continuum reflections, random illumination geometries within the material, phase angle effects, composite overlapping bands, and calibration uncertainties can shift apparent band positions by 20% from their actual positions or mask them beyond detection. Using multiple high order derivative analysis, effects of scattering continua, phase angle, and calibration (smooth features) are suppressed. Inflection points that characterize the positions and half widths of constituent bands are enhanced by the process and directly detected with relatively high sensitivity.

Huguenin, R. L.↗

Controlled Parametric Forcing During Directional Solidification of a Bulk Organic Alloy Under Microgravity

The response of dendritic microstructures to step-like pulling velocity conditions is investigated using microgravity directional solidification experiments conducted on DECLIC-DSI combined with phase-field simulations. Under a constant pulling velocity of 1.5 µm/s, the evolution toward steady-state growth is characterized in terms of primary spacing, dendrite drift, and tip dynamics. For the first time, side-view observations enabled direct measurement of tip radius and sidebranching frequency. When step-like oscillations of the pulling velocity are imposed, the dendritic array exhibits a strongly period-dependent response: short periods lead to rapid tip adaptation, whereas longer periods induce a phase lag between tip position and morphology, resulting in progressive tip flattening and, above a critical period, interface destabilization and dendrite splitting. Quantitative phase-field simulations, including a realistic thermal field and stochastic noise, reproduce the experimental observations and provide insight into the governing mechanisms, highlighting the role of characteristic relaxation times, sequence-dependent effects, and the irreversible reorganization of the microstructure following splitting.

Microgravity↗

Characterization of NTD germanium and ion-implanted Si bolometers at 0.3K and 0.1K

Bolometer elements were built and tested using NTD germanium and ion-implanted Si thermometer elements. The thermal links were made using aluminum wires and NbC(x)N(y) coated carbon fibers. The temperature dependence of the detector resistance, lead thermal conductivity, and heat capacity were measured. The dependence of the detector resistance on applied electric field was also measured. This, combined with the current-voltage curve for the detector, allowed the calculation of the detector responsivity. Known amounts of energy were deposited into the detector by allowing X-rays from the decay of Fe-55 to be thermalized in the detector. In the best-measured case, the predicted pulse height/measured height was 1.04 + or - .05. The noise at frequencies above 25 Hz in the NTD Ge was near that predicted by thermodynamics. The noise below 25 Hz has a 1/f character and may be in the carbon fiber/bolometer junction. The implanted detectors show some 1/f noise which depends on the total thermometer volume. Comparison between noise measurements and theory will be presented.

Moseley, H.↗

Performance Characterization of the Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP) CCD Cameras

The Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP) is a sounding rocket instrument currently being developed by NASA's Marshall Space Flight Center (MSFC), the National Astronomical Observatory of Japan (NAOJ), and other partners. The goal of this instrument is to observe and detect the Hanle effect in the scattered Lyman-Alpha UV (121.6nm) light emitted by the Sun's chromosphere. The polarized spectrum imaged by the CCD cameras will capture information about the local magnetic field, allowing for measurements of magnetic strength and structure. In order to make accurate measurements of this effect, the performance characteristics of the three on- board charge-coupled devices (CCDs) must meet certain requirements. These characteristics include: quantum efficiency, gain, dark current, read noise, and linearity. Each of these must meet predetermined requirements in order to achieve satisfactory performance for the mission. The cameras must be able to operate with a gain of 2.0+/- 0.5 e--/DN, a read noise level less than 25e-, a dark current level which is less than 10e-/pixel/s, and a residual non- linearity of less than 1%. Determining these characteristics involves performing a series of tests with each of the cameras in a high vacuum environment. Here we present the methods and results of each of these performance tests for the CLASP flight cameras.

solar↗

Performance and wake flow characterization of a 1:8.7-scale reference USDOE MHKF1 hydrokinetic turbine to establish a verification and validation test database

As hydrokinetic turbine technologies continue to advance towards commercialization, public datasets on the performance characteristics for these devices and their flow field effects are invaluable to advance our understanding of these technologies and to validate analytical and numerical models. The Applied Research Laboratory at The Pennsylvania State University (ARL Penn State) collaborated with Sandia National Laboratories and the University of California at Davis to design, fabricate (at a 1:8.7 scale), and experimentally test a novel hydrokinetic turbine rotor design to provide an open platform and dataset for further study and development. The water tunnel test of this three-bladed, horizontal-axis rotor recorded power production, blade loading, the near-wake flow, cavitation effects, and noise generation. These state-of-the-art measurements demonstrate much of the complex physics associated with the flow through an unducted, horizontal-axis turbine, and they elucidate the performance characteristics and flow field effects at an unprecedented fidelity, accuracy and resolution. Measurements of powering coefficients (power, torque and thrust) as a function of tip-speed-ratio were performed. The dataset also includes unsteady measurements of driveshaft loading, blade strain, tower pressures, and radiated noise. Detailed flow mapping using laser Doppler velocimetry, and planar and stereo particle image velocimetry includes measurements of mean velocity and Reynolds stresses. Although the wake measurements are limited to less than half a diameter, they reveal the complex flow patterns in the near-wake structure of the rotor. The full database, available at the United States Department of Energy’s marine and hydrokinetic data repository, includes tunnel and model Computer Aided Design geometry files and inflow data sufficient for a “Model-the-Test” computational Verification and Validation study.

13 HYDRO ENERGY↗

Characterization of a centrifugal pump in He II

As part of an effort to determine the feasibility of helium transfer in space, a centrifugal pump was tested in He II at a variety of flow rates, pump speeds, and fluid temperatures. The pump, which has a straight bladed impeller 6.86 cm in diameter, generated a maximum pressure rise of 15 kPa and a maximum flow rate of 22 g/s for the conditions of the test. Pump performance seems to be independent of fluid temperature and is in good agreement with the values predicted by the manufacturer. Over the range of flow coefficients, the measured maximum efficiency is around 50 percent. Cavitation is observed in the pump and is thought to be highly dependent on the local heating of the helium in the pump. Preliminary measurements of the noise spectra of the pump suggest a possible mechanism to predict the onset of cavitation.

Weisend, J. G., II↗

Approaching the Lower Temporal Limit of Laser‐Produced Plasma Sources for Table‐Top Soft X‐Ray NEXAFS Measurements

Abstract The increasing popularity of time‐resolved X‐ray absorption measurements for understanding dynamics in molecular and material systems has led to many advances in table‐top sources for pulsed X‐rays. We report on a table‐top laser‐produced plasma (LPP) source that can perform soft X‐ray (SXR), near‐edge X‐ray absorption fine structure (NEXAFS) measurements using a laser source with 23 ps pulse duration. The spectrometer's key specifications, such as brilliance, resolution, and stability, are characterized against the more commonly used longer‐pulse‐duration LPP sources. The 23 ps laser produced approximately an order of magnitude weaker SXR flux than the 8 ns laser for a higher power density due to the smaller total energy absorbed by the plasma. The increased repetition rate, as well as the use of a high line‐density X‐grating, and a self‐referencing scheme still allowed for NEXAFS measurements of Si 3 N 4 and TiO 2 thin films with 2.5 minute acquisition times, a resolving power of E/ΔE=424, and a signal‐to‐noise ratio of 100. It was observed that degradation of the gas jet nozzle led to long‐term instability of the source, which can be remediated using alternative nozzle designs. This work demonstrates the feasibility of achieving higher temporal resolution in future time‐resolved X‐ray absorption measurements using table‐top LPP sources.

Nimlos, Danika [Division of Chemistry and Chemical↗

Coherent structures - Reality and myth

Large-scale coherent structures (CS) in turbulent shear flows are characterized, reviewing recent theoretical and experimental investigations. The use of computers as a research tool and the flow-visualization experimental technique are introduced, CS are defined, the history of their discovery is traced, and their main characteristics are listed. Topics discussed and illustrated include the initial condition of the free shear layer, triple and double decomposition, topological features of CS, detection and eduction of CS, phase alignment via cross correlation, induced versus natural structures, the bursting phenomenon, turbulent spot, streaks, bursting frequency, the axisymmetric mixing layer, vortex pairing in an axisymmetric jet, CS and jet noise, broadband noise amplification via pure-tone excitation, CS interaction in a plane-jet near field, the Taylor hypothesis applied to CS, negative production, and the validity of the Reynolds-number similarity hypothesis. It is found that the coherent Reynolds stress, vorticity, and production are not much greater than the time-averaged values for fully developed flows with significant incoherent turbulence, suggesting that the importance of CS may have been exaggerated in some recent studies.

Hussain, A. K. M. F.↗