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At least 1,117 records · Page 62

An experimental mapping of the flow field behind a glaze ice shape on a NACA 0012 airfoil

The flow field about a NACA 0012 airfoil with a simulated glaze ice shape was studied. Split hot-film anemometry was used to measure the streamwise velocity component in the upper and lower separation bubbles aft of the glaze ice horns. Velocity profiles were presented as well as the boundary layer momentum and displacement thickness distributions through the bubbles. Data were presented at angles of attack of 0, 2 and 4 deg and clearly showed the large region of reverse flow. A detailed discussion of split hot-film acquisition and data reduction, and possible sources of error has been included.

Spring, Samuel A.↗

Measurement of the Positive Muon Anomalous Magnetic Moment to 0.20 ppm

We present a new measurement of the positive muon magnetic anomaly, a μ ≡ ( g μ - 2 ) / 2 , from the Fermilab Muon g - 2 Experiment using data collected in 2019 and 2020. We have analyzed more than 4 times the number of positrons from muon decay than in our previous result from 2018 data. The systematic error is reduced by more than a factor of 2 due to better running conditions, a more stable beam, and improved knowledge of the magnetic field weighted by the muon distribution, ω ˜ p ′ , and of the anomalous precession frequency corrected for beam dynamics effects, ω a . From the ratio ω a / ω ˜ p ′ , together with precisely determined external parameters, we determine a μ = 116 592 057 ( 25 ) × 10 - 11 (0.21 ppm). Combining this result with our previous result from the 2018 data, we obtain a μ ( FNAL ) = 116 592 055 ( 24 ) × 10 - 11 (0.20 ppm). The new experimental world average is a μ ( exp ) = 116 592 059 ( 22 ) × 10 - 11 (0.19 ppm), which represents a factor of 2 improvement in precision.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Chatbots can guide experimentalists to avoid many common mistakes in measuring fluorescence spectra

The concepts of fluorescence spectroscopy are well established, yet the experimental collection of a spectrum is susceptible to a range of errors. A recent study showed that chatbots – derived from substantial advances in artificial intelligence – can provide practical assistance to the experimentalist during collection of absorption spectra and thereby achieve improved quality. Fluorescence, while the complement of absorption, is prone to a far richer array of experimental errors encompassing environmental factors, instrumental settings, and experimentalist mistakes. Here, 10 chatbots (ChatGPT 5, Gemini 2.5 Pro, Microsoft Copilot, Meta AI Llama 4, Claude Sonnet 4.5, X.ai Grok 4, Perplexity Pro, DeepSeek V3.1, Z.ai GLM-4.6, and KIMI K2) have been evaluated for the suitability in providing quality-improvement advice to the experimentalist during acquisition of fluorescence spectra. Significant opportunities for practical assistance are noted, although intervention by a domain expert is often required. Here, if combined with image recognition and/or signal processing, chatbots embedded in instruments may enable real-time guidance during fluorescence data acquisition.

Artificial intelligence↗

Fully elliptic incompressible flow calculations on regular grid by a new pressure substitution method

A new method is presented for the solution of incompressible flow in generalized coordinates. This method is based on the substitution of the pressure weighted form of the momentum equations into the continuity equation. The algorithm is rigorously derived and a Fourier analysis is used to assess its suitability to act as an error smoother. Linear stability analysis results indicate that the performance of the new pressure substitution method (PSM) and the pressure correction method (PCM) is about the same at low Reynolds numbers, with no significant pressure gradient. At high Reynolds numbers the PSM shows much faster convergence. Likewise prediction of various flows indicate that the PSM has better accuracy for high Reynolds number flows with significant pressure gradients. Since most practical aerodynamic flows have significant pressure gradients, the PSM seems to be attractive for such flows. Solutions for both laminar and turbulent flow are compared with the experimental data. A two-equation low Reynolds number turbulence model is used to resolve the turbulent flowfield.

Hobson, G. V.↗

Comparison of analysis and experiment for dynamics of low-contact-ratio spur gears

Low-contact-ratio spur gears were tested in NASA gear-noise-rig to study gear dynamics including dynamic load, tooth bending stress, vibration, and noise. The experimental results were compared with a NASA gear dynamics code to validate the code as a design tool for predicting transmission vibration and noise. Analytical predictions and experimental data for gear-tooth dynamic loads and tooth-root bending stress were compared at 28 operating conditions. Strain gage data were used to compute the normal load between meshing teeth and the bending stress at the tooth root for direct comparison with the analysis. The computed and measured waveforms for dynamic load and stress were compared for several test conditions. These are very similar in shape, which means the analysis successfully simulates the physical behavior of the test gears. The predicted peak value of the dynamic load agrees with the measurement results within an average error of 4.9 percent except at low-torque, high-speed conditions. Predictions of peak dynamic root stress are generally within 10 to 15 percent of the measured values.

Oswald, Fred B.↗

Cabauw Experimental Results from the Project for Intercomparison of Land-Surface Parameterization Schemes

In the Project for Intercomparison of Land-Surface Parameterization Schemes phase 2a experiment, meteorological data for the year 1987 from Cabauw, the Netherlands, were used as inputs to 23 land-surface flux schemes designed for use in climate and weather models. Schemes were evaluated by comparing their outputs with long-term measurements of surface sensible heat fluxes into the atmosphere and the ground, and of upward longwave radiation and total net radiative fluxes, and also comparing them with latent heat fluxes derived from a surface energy balance. Tuning of schemes by use of the observed flux data was not permitted. On an annual basis, the predicted surface radiative temperature exhibits a range of 2 K across schemes, consistent with the range of about 10 W/m in predicted surface net radiation. Most modeled values of monthly net radiation differ from the observations by less than the estimated maximum monthly observational error (+/- 10 W/sq m). However, modeled radiative surface temperature appears to have a systematic positive bias in most schemes; this might be explained by an error in assumed emissivity and by models' neglect of canopy thermal heterogeneity. Annual means of sensible and latent heat fluxes, into which net radiation is partitioned, have ranges across schemes of 30 W/sq m and 25 W/sq m, respectively. Annual totals of evapotranspiration and runoff, into which the precipitation is partitioned, both have ranges of 315 mm. These ranges in annual heat and water fluxes were approximately halved upon exclusion of the three schemes that have no stomatal resistance under non-water-stressed conditions. Many schemes tend to underestimate latent heat flux and overestimate sensible heat flux in summer, with a reverse tendency in winter. For six schemes, root-mean-square deviations of predictions from monthly observations are less than the estimated upper bounds on observation errors (5 W/m for sensible beat flux and 10 W/m for latent heat flux). Actual runoff at the site is believed to be dominated by vertical drainage to ground water, but several schemes produced significant amounts of runoff as overland flow or interflow. There is a range across schemes of 184 mm (40% of total pore volume) in the simulated annual mean root-zone soil moisture. Unfortunately, no measurements of soil moisture were available for model evaluation. A theoretical analysis suggested that differences in boundary conditions used in various schemes are not sufficient to explain the large variance in soil moisture. However, many of the extreme values of soil moisture could be explained in terms of the particulars of experimental setup or excessive evapotranspiration.

Chen, Tian Hong↗

Effects of cluster expansion on the locations of phase transition boundary as a first step to quantify uncertainty in first principles statistical mechanics framework

Predicting phase diagrams from first principle calculations eliminates the need of tedious experimental trials and errors. Fully automating first principle phase diagram calculations without any sort of human intervention has been a long daunting task and troubling scientific communities for decades. This grand problem remains not fully resolved, largely due to the vastly high-dimensional parameter space associated with density functional theory, cluster expansion, lattice Monte Carlo, and the substantial uncertainty propagating through a set of complex simulations. As a first step to tackle this grand problem, we reported a first demonstration of how sensitive phase boundary locations can be to various cluster expansion fittings and input DFT training data. To the best knowledge of the authors, this study reported the first ever attempt to quantify uncertainty in first principles statistical mechanics framework. In addition, a semi-automated phase transition detection algorithm has been devised in this paper to deal with the associated statistical errors and uncertainties from Monte Carlo method and its predecessor DFT calculations and cluster expansions. This algorithm has been applied in a classical cluster expansion Mg-Cd binary alloy system to detect phase transitions at various locations of phase diagram using different cluster expansions to demonstrate its predictive power and quantify uncertainties. The results suggested that using Chebyshev basis function shifted the transition locations toward the dilute solid solution phase and expanded the phase stability of concentrated ordered phases to wider composition range. The addition of perturbed defect configurations into training data set lowered the order-disorder transition temperature to be away from true transition temperature, suggesting the transition nature is indeed configurational disorder dominated rather than defect assisted. Finally, we found that the weighting has negligible effect on the transition locations, except for the case of using Chebyshev basis function to fit all non-weighted configurations that can be susceptible to Monte Carlo sampling hysteresis.

36 MATERIALS SCIENCE↗

Ames S-32 O-16 O-18 Line List for High-Resolution Experimental IR Analysis

By comparing to the most recent experimental data and spectra of the SO2 628 ν1/ν3 bands (see Ulenikov et al., JQSRT 168 (2016) 29-39), this study illustrates the reliability and accuracy of the Ames-296K SO2 line list, which is accurate enough to facilitate such high-resolution spectroscopic analysis. The SO2 628 IR line list is computed on a recently improved potential energy surface (PES) refinement, denoted Ames-Pre2, and the published purely ab initio CCSD(T)/aug-cc-pVQZ dipole moment surface. Progress has been made in both energy level convergence and rovibrational quantum number assignments agreeing with laboratory analysis models. The accuracy of the computed 628 energy levels and line list is similar to what has been achieved and reported for SO2 626 and 646, i.e. 0.01-0.03 cm(exp −1) for bands up to 5500 cm(exp −1). During the comparison, we found some discrepancies in addition to overall good agreements. The three-IR-list based feature-by-feature analysis in a 0.25 cm(exp −1) spectral window clearly demonstrates the power of the current Ames line lists with new assignments, correction of some errors, and intensity contributions from varied sources including other isotopologues. We are inclined to attribute part of detected discrepancies to an incomplete experimental analysis and missing intensity in the model. With complete line position, intensity, and rovibrational quantum numbers determined at 296 K, spectroscopic analysis is significantly facilitated especially for a spectral range exhibiting such an unusually high density of lines. The computed 628 rovibrational levels and line list are accurate enough to provide alternatives for the missing bands or suspicious assignments, as well as helpful to identify these isotopologues in various celestial environments. The next step will be to revisit the SO2 828 and 646 spectral analyses.

Sulfur dioxide↗

Systematic exploration of the thermochemistry for a set of peroxy hydroperoxy-alkyl radicals

Here, the thermochemistry of peroxy hydroperoxy-alkyl ($\overline{O}$OQOOH) radicals has a significant influence on the reactivity of fuels and on the formation of highly oxygenated molecules (HOMs) in the atmosphere. Theoretical characterization of these radicals can be arduous due to their molecular size and complex fundamental interactions, such as hydrogen-bonding and torsional anharmonicity, and difficult to validate in the absence of any direct experimental thermochemical data. In this work, we systematically explore the thermochemistry of a set of $\overline{O}$OQOOH radicals with five increasingly affordable approaches with considerations for these interactions. In doing so, we present a novel conformer selection approach suited to predict properties at combustion temperatures. As a corollary, we also highlight the shortcomings in the standard choice of the ground conformer as the reference. The set of molecules is comprised of 149 C 2 -C 8 $\overline{O}$OQOOH radicals, selected to encompass a wide variety of branching and substitution patterns. Comparisons amongst the approaches help quantify the errors arising from various simplifying assumptions. For the largest of these radicals, and with the most affordable approach, final predictions of Gibbs energies are assigned a 2 σ uncertainty of 4 kcal mol -1 in the negative temperature coefficient region.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Calibration of energy density functionals with deformed nuclei

Nuclear density functional theory is the prevalent theoretical framework for accurately describing nuclear properties at the scale of the entire chart of nuclides. Given an energy functional and a many-body scheme (e.g., single- or multireference level), the predictive power of the theory depends strongly on how the parameters of the energy functionals have been calibrated with experimental data. Expanded algorithms and computing power have enabled recent optimization protocols to include data in deformed nuclei in order to optimize the coupling constants of the energy functional. The primary motivation of this work is to test the robustness of such protocols with respect to some of the technical and numerical details of the underlying calculations, especially when the calibration explores a large parameter space. To this end, we quantify the effect of these uncertainties on both the optimization and statistical emulation of composite objective functions. We also emphasize that Bayesian calibration can provide better estimates of the theoretical errors used to define objective functions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Kinetic equilibrium reconstruction and the impact on stability analysis of KSTAR plasmas

High fidelity kinetic plasma equilibrium reconstructions are an essential requirement for accurate stability and disruption prediction analyses to support continuous operation of high beta tokamak plasmas. The present kinetic equilibrium reconstructions of plasmas in the KSTAR device include plasma density and temperature profiles from Thomson scattering and ion temperature from charge exchange spectroscopy diagnostics, and allowance for fast particle pressure. In addition, up to 25 channels of motional Stark effect diagnostic data are used to constrain the magnetic field pitch angle profile in the plasma to produce a reliable computation of the safety factor, q, profile. In this work, H-mode plasmas exhibit clear pedestal characteristics in the reconstructed pressure profile compared to internal transport barrier or L-mode plasmas. The plasma configuration and vertical position of inner strike points are validated by CCD and infrared camera images. Ideal and resistive magnetohydrodynamic (MHD) stability analyses using the DCON and resistive DCON codes utilize these kinetic equilibrium reconstructions to compare to experimental plasma stability. Equilibria with sufficiently low convergence error can provide reliable computation of ideal and resistive MHD stability analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

EFFECTS OF HIGH G CONDITIONS ON PILOT PERFORMANCE

The general development trend in space vehicle design suggests the desirability of maximally using the occupant to both control capsule attitude and to monitor vehicle systems during the boost (and reentry) acceleration phases, as well as during orbital flight. Consequently, much more information is needed concerning man's ability to perform certain control functions under conditions in which he is exposed to accelerations which approach not only his physiological tolerance limits, but also his performance tolerance limits. In addition to the need for more data concerning the acceleration stress that man can endure and still retain the ability to perform control functions, there is a need to know specifically the nature of performance errors which can arise, not only as the direct result of acceleration, but also as secondary effects of acceleration inter acting with other conditions such as the type of control task, the type of control device, the damping and stability parameters, and the pilot's physiological endurance8 . Current concern over the performance capabilities of the human pilot immersed in certain acceleration environments is well founded since there are very few experimental reports describing the effects of these conditions on performance. The present paper attempts to summarize some of the results of recent studies conducted at the Aviation Medical Acceleration Laboratory (AMAL) in which specific pilot performance capabilities were studied under several conditions of acceleration stress.

Gravity↗

Space marching calculations about hypersonic configurations using a solution-adaptive mesh algorithm

A solution-adaptive marching algorithm is developed and applied to a three-dimensional parabolized Navier-Stokes equation solver. The resulting algorithm obtains accurate solutions by using a spatial-marching/adaptive grid procedure. The adaptation step redistributes grid points line by line in both crossflow directions, with grid point motion controlled by forces analogous to tensional and torsional spring forces with the tensional force proportional to the error measure or weighting functions. The solution-adaptive marching procedure is applied to the hypersonic flow about two generic aircraft configurations. The first of these is an all-body-type geometry with elliptical cross sections and is studied at angles of attack of 0.5, and 15 deg. The second geometry is a generic blended-wing-body design. Results are presented that demonstrate the improvements in flowfield resolution obtainable with the solution-adaptive marching procedure over conventional fixed grid techniques. Computed pitot pressure profiles obtained using the solution-adaptive algorithm show improved agreement with experimental data compared to predictions obtained using a fixed grid.

Harvey, Albert D.↗

High‐Asymmetry Metasurface: A New Solution for Terahertz Resonance via Active Learning‐Augmented Diffusion Model

Terahertz (THz) metamaterials with high‐figure‐of‐merit (high‐FoM) performance resonance are essential for advancing sensors, detectors, and imagers. Conventional designs focus on symmetric or low‐asymmetry geometric structures, leaving high‐asymmetry designs largely unexplored due to the inefficiency of trial‐and‐error‐based rational design. Recent deep learning techniques offer automation and acceleration but are constrained by the need for large datasets inherent to their data‐driven nature. Here, a novel prior knowledge‐guided generative model augmented by a physics‐constrained active learning mechanism to design high‐asymmetry metamaterials. An advanced diffusion model learns features from a small set of classical structures with high‐FoM THz resonance and generates new high‐asymmetry structures. To mitigate the limited number of classical structures, the generated high‐asymmetry structures are actively selected and integrated into the initial training dataset based on their physical characteristics. Experimental results demonstrate the superior resonance performance of the generated high‐asymmetry metamaterials over classical designs, exhibiting improvements exceeding 30% in key resonance metrics. Remarkably, this performance is attained using only 68 classical structures as the initial training dataset, significantly reducing the data requirements for deep learning‐based metamaterial design. The proposed scheme for generating high‐asymmetry structures provides a new effective and efficient solution for high‐FoM resonance, expanding applications in high‐sensitivity THz metadevices.

diffusion model↗

Bottomonium suppression and elliptic flow using Heavy Quarkonium Quantum Dynamics

We introduce a framework called Heavy Quarkonium Quantum Dynamics (HQQD) which can be used to compute the dynamical suppression of heavy quarkonia propagating in the quark-gluon plasma using real-time in-medium quantum evolution. Using HQQD we compute large sets of real-time solutions to the Schrödinger equation using a realistic in-medium complex-valued potential. We sample 2 million quarkonia wave packet trajectories and evolve them through the QGP using HQQD to obtain their survival probabilities. The computation is performed using three different HQQD model parameter sets in order to estimate our systematic uncertainty. After taking into account final state feed down we compare our results to existing experimental data for the suppression and elliptic flow of bottomonium states and find that HQQD predictions are good agreement with available data for R AA as a function of N part and p T collected at \( \sqrt{s_{\mathrm{NN}}} \) = 5 . 02 TeV. In the case of v 2 for the various states, we find that the path-length dependence of ϒ(1 s ) suppression results in quite small v 2 for ϒ(1 s ). Our prediction for the integrated elliptic flow for ϒ(1 s ) in the 10 – 90% centrality class, which now includes an estimate of the systematic error, is v 2 [ϒ(1 s )] = 0 . 003 ± 0 . 0007 ± \( {}_{0.0013}^{0.0006} \) . We also find that, due to their increased suppression, excited bottomonium states have a larger elliptic flow. Based on this observation we make predictions for v 2 [ϒ(2 s )] and v 2 [ϒ(3 s )] as a function of centrality and transverse momentum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Carbonyl Identification and Quantification Uncertainties for Oxidative Polymer Degradation

The most revealing indicator for oxidative processes or state of degraded plastics is usually carbonyl formation, a key step in materials degradation as part of the carbon cycle for man-made materials. Hence, the identification and quantification of carbonyl species with infrared spectroscopy have been the method of choice for generations, thanks to their strong absorbance and being an essential intermediate in carbon oxidation pathways. Despite their importance, precise identification and quantification can be challenging and rigorous fully traceable data are surprisingly rare in the existing literature. An overview of the complexity of carbonyl quantification is presented by the screening of reference compounds in solution with transmission and polymer films with ATR IR spectroscopy, and systematic data analyses. Significant variances in existing data and their past use have been recognized. Guidance is offered how better measurements and data reporting could be accomplished. Experimental variances depend on the combination of uncertainty in exact carbonyl species, extinction coefficient, contributions from neighboring convoluting peaks, matrix interaction phenomena and instrumental variations in primary IR spectral acquisition (refractive index and penetration depth for ATR measurements). In addition, diverging sources for relevant extinction coefficients may exist, based on original spectral acquisition. For common polymer degradation challenges, a relative comparison of carbonyl yields for a material is easily accessible, but quantification for other purposes, such as degradation rates and spatially dependent interpretation, requires thorough experimental validation. All variables featured in this overview demonstrate the significant error margins in carbonyl quantification, with exact carbonyl species and extinction coefficients already being major contributors on their own.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aeroacoustic Simulations of a Nose Landing Gear Using FUN3D on Pointwise Unstructured Grids

Numerical simulations have been performed for a partially-dressed, cavity-closed (PDCC) nose landing gear configuration that was tested in the University of Florida's open-jet acoustic facility known as the UFAFF. The unstructured-grid flow solver FUN3D is used to compute the unsteady flow field for this configuration. Mixed-element grids generated using the Pointwise(TradeMark) grid generation software are used for these simulations. Particular care is taken to ensure quality cells and proper resolution in critical areas of interest in an effort to minimize errors introduced by numerical artifacts. A hybrid Reynolds-averaged Navier-Stokes/large eddy simulation (RANS/LES) turbulence model is used for these simulations. Solutions are also presented for a wall function model coupled to the standard turbulence model. Time-averaged and instantaneous solutions obtained on these Pointwise grids are compared with the measured data and previous numerical solutions. The resulting CFD solutions are used as input to a Ffowcs Williams-Hawkings noise propagation code to compute the farfield noise levels in the flyover and sideline directions. The computed noise levels compare well with previous CFD solutions and experimental data.

Vatsa, Veer N.↗

A DATA EFFICIENT SPARSE MODELING FRAMEWORK FOR POWER ESTIMATION IN WATER TREATMENT SENSING OPERATIONS

With increasing freshwater scarcity, advanced process design mechanisms such as Closed-Circuit Reverse Osmosis (CCRO) and Digital/Physical Twin systems are gaining traction in water treatment and reuse operations. While digital and physical twin models enable improved system insight and control, their development is often expensive and computationally intensive, requiring large volumes of synthetic or experimental data to characterize underlying process dynamics. This work introduces a sparse surrogate modeling framework to estimate power consumption from measured flow and pressure variables, along with their nonlinear polynomial and interaction expansions. To ensure model reliability and reduce overfitting, a two-stage pipeline is proposed. First, a dynamic data filtering algorithm is employed to remove uninformative observations and transient operational states. Second, a sparse penalized regression technique is applied to select a minimal set of parsimonious features. The proposed model achieves high sparsity, retaining only 7 out of 34 candidate features (≈79.41% sparsity) while delivering a root mean square error (RMSE) of 0.072 on the test dataset.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗