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At least 703 records · Page 39

Experimental investigations of Critical Heat Flux re-occurrence on post-CHF surfaces

Under the extreme environments of light water reactors, the cladding materials demonstrate evolutionary transformations in terms of material compositions, surface morphologies, and thermal-physical properties. This study investigates how the temperature overshooting of Critical Heat Flux (CHF) affects the re-occurrence of CHF on the post-CHF surfaces. Experimental results reveal that the CHF difference between as-received and post-CHF surfaces can be significant, which depends on materials. CHF is enhanced on post-CHF Stainless Steel (SS 316) specimens while it deteriorates on post-CHF Inconel-600 specimens. In comparison with the as-received surfaces, the post-CHF surface of SS 316 is more hydrophobic, while Inconel 600 is more hydrophilic. The scanning electron microscope micrographs of post-CHF surfaces show that surface morphologies that are structured by oxide crystals are formed on SS 316 samples but not on Inconel 600 samples. The physical rationale behind the CHF difference could be boiling heat transfer conjugated with thermal-physical proprieties of investigated surface materials and surface morphologies features. In conclusion, the results imply that it is indispensable to bookkeep the evolutionary changes of cladding surface materials, especially for cladding candidates of Accident Tolerant Fuel since operation histories can leave footprints on cladding surfaces, thus resulting in CHF re-occurrence differences.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Designing a decentralized fault-tolerant software framework for smart grids and its applications

The vision of the ‘Smart Grid’ anticipates a distributed real-time embedded system that implements various monitoring and control functions. As the reliability of the power grid is critical to modern society, the software supporting the grid must support fault tolerance and resilience of the resulting cyber-physical system. This paper describes the fault-tolerance features of a software framework called Resilient Information Architecture Platform for Smart Grid (RIAPS). The framework supports various mechanisms for fault detection and mitigation and works in concert with the applications that implement the grid-specific functions. The paper discusses the design philosophy for and the implementation of the fault tolerance features and presents an application example to show how it can be used to build highly resilient systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Numerical Mixing Suppresses Submesoscale Baroclinic Instabilities Over Sloping Bathymetry

Abstract The impacts of spurious numerical salinity mixing on the larger‐scale flow and tracer fields are characterized using idealized simulations. The idealized model is motivated by realistic simulations of the Texas‐Louisiana shelf and features oscillatory near‐inertial wind forcing. can exceed the physical mixing from the turbulence closure in frontal zones and within the mixed layer. This suggests that simulated mixing processes in frontal zones are driven largely by . Near‐inertial alongshore wind stress amplitude is varied to identify a base case that maximizes the ratio of to in simulations with no prescribed horizontal mixing. We then test the sensitivity of the base case with three tracer advection schemes (MPDATA, U3HC4, and HSIMT) and conduct ensemble runs with perturbed bathymetry. Instability growth is evaluated using the volume‐integrated eddy kinetic energy and available potential energy . While all schemes have similar total mixing, the HSIMT simulations have over double the volume‐integrated and 20% less relative to other schemes, which suppresses the release of and reduces the by roughly 25%. This results in reduced isohaline variability and steeper isopycnals, evidence that enhanced suppresses instability growth. Differences in and between the MPDATA and U3HC4 simulations are marginal. However, the U3HC4 simulations have 25% more . Experiments with variable horizontal viscosity and diffusivity coefficients show that small amounts of prescribed horizontal mixing improve the representation of the ocean state for all advection schemes by reducing the and increasing the .

54 ENVIRONMENTAL SCIENCES↗

Elucidation of the physical factors that control activated transport of penetrants in chemically complex glass-forming liquids

Understanding the activated transport of penetrant or tracer atoms and molecules in condensed phases is a challenging problem in chemistry, materials science, physics, and biophysics. Many angstrom- and nanometer-scale features enter due to the highly variable shape, size, interaction, and conformational flexibility of the penetrant and matrix species, leading to a dramatic diversity of penetrant dynamics. Based on a minimalist model of a spherical penetrant in equilibrated dense matrices of hard spheres, a recent microscopic theory that relates hopping transport to local structure has predicted a novel correlation between penetrant diffusivity and the matrix thermodynamic dimensionless compressibility, S 0 ( T ) (which also quantifies the amplitude of long wavelength density fluctuations), as a consequence of a fundamental statistical mechanical relationship between structure and thermodynamics. Moreover, the penetrant activation barrier is predicted to have a factorized/multiplicative form, scaling as the product of an inverse power law of S 0 ( T ) and a linear/logarithmic function of the penetrant-to-matrix size ratio. This implies an enormous reduction in chemical complexity that is verified based solely on experimental data for diverse classes of chemically complex penetrants dissolved in molecular and polymeric liquids over a wide range of temperatures down to the kinetic glass transition. The predicted corollary that the penetrant diffusion constant decreases exponentially with inverse temperature raised to an exponent determined solely by how S 0 ( T ) decreases with cooling is also verified experimentally. Our findings are relevant to fundamental questions in glassy dynamics, self-averaging of angstrom-scale chemical features, and applications such as membrane separations, barrier coatings, drug delivery, and self-healing.

Science & Technology - Other Topics↗

On the use of neural networks for energy reconstruction in high-granularity calorimeters

We contrasted the performance of deep neural networks — Convolutional Neural Network (CNN) and Graph Neural Network (GNN) — to current state of the art energy regression methods in a finely 3D-segmented calorimeter simulated by GEANT4. This comparative benchmark gives us some insight to assess the particular latent signals neural network methods exploit to achieve superior resolution. A CNN trained solely on a pure sample of pions achieved substantial improvement in the energy resolution for both single pions and jets over the conventional approaches. It maintained good performance for electron and photon reconstruction. We also used the Graph Neural Network (GNN) with edge convolution to assess the importance of timing information in the shower development for improved energy reconstruction. We implement a simple simulation based correction to the energy sum derived from the fraction of energy deposited in the electromagnetic shower component. This serves as an approximate dual-readout analogue for our benchmark comparison. Although this study does not include the simulation of detector effects, such as electronic noise, the margin of improvement seems robust enough to suggest these benefits will endure in real-world application. We also find reason to infer that the CNN/GNN methods leverage latent features that concur with our current understanding of the physics of calorimeter measurement.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Magnetic properties of a staggered S = 1 chain with an alternating single-ion anisotropy direction

Materials composed of spin-1 antiferromagnetic (AFM) chains are known to adopt complex ground states that are sensitive to the single-ion-anisotropy (SIA) energy ( D ), and intrachain ( J 0 ) and interchain ( J 1 , 2 ′ ) exchange energy scales. While theoretical and experimental studies have extended this model to include various other energy scales, the effect of the lack of a common SIA axis is not well explored. Here we investigate the magnetic properties of Ni ( pyrimidine ) ( H 2 O ) 2 ( NO 3 ) 2 , a chain compound where the tilting of Ni octahedra leads to a twofold alternation of the easy-axis directions along the chain. Muon-spin relaxation measurements indicate a transition to long-range order at T N = 2.3 K and the magnetic structure is initially determined to be antiferromagnetic and collinear using elastic neutron diffraction experiments. Inelastic neutron scattering measurements were used to find J 0 = 5.107 ( 7 ) K , D = 2.79 ( 1 ) K , J 1 ′ = 0.00 ( 5 ) K , J 2 ′ = 0.18 ( 3 ) K , and a rhombic anisotropy energy E = 0.19 ( 9 ) K . Mean-field modeling reveals that the ground state structure hosts spin canting of ϕ ≈ 6 . 5 ∘ , which is not detectable above the noise floor of the elastic neutron diffraction data. Monte Carlo simulation of the powder-averaged magnetization, M ( H ) , is then used to confirm these Hamiltonian parameters, while single-crystal M ( H ) simulations provide insight into features observed in the data. Published by the American Physical Society 2025

Vaidya, S. (ORCID:000000033975497X)↗

Measurement of the depth of maximum of air-shower profiles with energies between 10 18.5 and 10 20 eV using the surface detector of the Pierre Auger Observatory and deep learning

We report an investigation of the mass composition of cosmic rays with energies from 3 to 100 EeV ( 1 EeV = 10 18 eV ) using the distributions of the depth of shower maximum X max . The analysis relies on ∼ 50 , 000 events recorded by the surface detector of the Pierre Auger Observatory and a deep-learning-based reconstruction algorithm. Above energies of 5 EeV, the dataset offers a 10-fold increase in statistics with respect to fluorescence measurements at the Observatory. After cross-calibration using the fluorescence detector, this enables the first measurement of the evolution of the mean and the standard deviation of the X max distributions up to 100 EeV. Our findings are threefold: (i) The evolution of the mean logarithmic mass toward a heavier composition with increasing energy can be confirmed and is extended to 100 EeV. (ii) The evolution of the fluctuations of X max toward a heavier and purer composition with increasing energy can be confirmed with high statistics. We report a rather heavy composition and small fluctuations in X max at the highest energies. (iii) We find indications for a characteristic structure beyond a constant change in the mean logarithmic mass, featuring three breaks that are observed in proximity to the ankle, instep, and suppression features in the energy spectrum. Published by the American Physical Society 2025

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Model-Free Measurement of Local Entropy Production and Extractable Work in Active Matter

Time-reversal symmetry breaking and entropy production are universal features of nonequilibrium phenomena. Despite its importance in the physics of active and living systems, the entropy production of systems with many degrees of freedom has remained of little practical significance because the high dimensionality of their state space makes it difficult to measure. Here, in this work, we introduce a local measure of entropy production and a numerical protocol to estimate it. We establish a connection between the entropy production and extractability of work in a given region of the system and show how this quantity depends crucially on the degrees of freedom being tracked. We validate our approach in theory, simulation, and experiments by considering systems of active Brownian particles undergoing motility-induced phase separation, as well as active Brownian particles and E.coli in a rectifying device in which the time-reversal asymmetry of the particle dynamics couples to spatial asymmetry to reveal its effects on a macroscopic scale.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Heat conduction in magnetic insulators via hybridization of acoustic phonons and spin-flip excitations

We present a comprehensive study on the longitudinal magnetothermal transport in a paramagnetic effective spin-1/2 magnetic insulator CsYbSe 2 , by introducing a minimal model requiring only Zeeman splitting and magnetoelastic coupling. We use it to argue that hybridized excitations—formed from acoustic phonons and localized spin-flip-excitations across the Zeeman gap of the crystal electric field ground doublet—are responsible for a nonmonotonic field dependence of longitudinal thermal conductivity. Beyond highlighting a starring role for phonons, our results raise the prospect of universal magnetothermal transport phenomena in paramagnetic insulators that originate from simple features shared across many systems. Published by the American Physical Society 2025

Pocs, Christopher A.↗

Vibrational spectroscopy analysis of silica and silicate glass networks

Vibrational spectroscopy has been widely used to investigate various structural aspects of the glass network, and there are a plethora of papers reporting subtle but consistent changes in infrared and Raman spectral features of glass upon alterations of glass compositions, thermal histories, mechanical stresses, or surface treatments. However, interpretations of such spectral features are still obscured due to the lack of well-established physical principles accurately describing vibrational modes of the non-crystalline glass network. Due to the non-equilibrium nature of the glass network, three-dimensionally connected without any long-range orders, vibrational spectral features of glass cannot be interpreted using the analogy with those of isolated molecular moieties or crystalline counterparts. Here, this feature article explains why such comparisons are outdated and describes the recent advances made from theoretical calculations of vibrational spectral features of amorphous networks or comparisons of computational results with experimental data. For the interpretation of vibrational spectral features of silica and silicate glasses, the following empirical relationships are suggested: (i) the intensity-weighted peak position of the Si-O-Si stretch mode negatively correlates with the weighted average of the Si-O bond length distribution, and (ii) the broad band of the Si-O-Si bending mode negatively correlates with the Si-O-Si bond angle distribution. Selected examples of vibrational spectroscopic imaging of surface defects are discussed to deliberate the implication of these findings in the structure-property relationship of silica and silicate glass materials. Unanswered questions and continuing research challenges are identified.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Gyrokinetic understanding of the edge pedestal transport driven by resonant magnetic perturbations in a realistic divertor geometry

Self-consistent simulations of neoclassical and electrostatic turbulent transport in a DIII-D H-mode edge plasma under resonant magnetic perturbations (RMPs) have been performed using the global total-f gyrokinetic particle-in-cell code XGC, in order to study density-pump out and electron heat confinement.The RMP field is imported from the extended magneto-hydrodynamics (MHD) code M3D-C1, taking into account the linear two-fluid plasma response.With both neoclassical and turbulence physics considered together, the XGC simulation reproduces two key features of experimentally observed edge transport under RMPs: increased radial particle transport in the pedestal region that is sufficient to account for the experimental pump-out rate, and suppression of the electron heat flux in the steepest part of the edge pedestal.In the simulation, the density fluctuation amplitude of modes moving in the electron diamagnetic direction increases due to interaction with RMPs in the pedestal shoulder and outward, while the electron temperature fluctuation amplitude decreases.

DIII-D↗

ModuleOT

ModuleOT is an open hardware security platform which provides all features necessary for securing remote energy resources. The platform consists of a physical bump in-the wire device which runs a custom-built application built with Go and Python and leverages AES-NI Instruction set available on modern hardware for cryptographic acceleration. By combining these features, ModuleOT acts as an all-in-one low-cost solution to enable cryptographically secured communications to any critical remote servers or devices. Because the software application has been built using Golang, this source can be easily compiled for different hardware platforms. The module is designed to provide the following core features: (1) encrypted communications across an untrusted network, (2) certificate-based authentication with secure storage, (3) hardware cryptographic acceleration, (4) IP-based whitelisting, (5) local firewall management, and (6) legacy (RS485) device support.

Hasandka, Adarsh↗

AIACHNE's contribution for Nuclear Energy Agency Working Party on International Nuclear Data Evaluation Co-operation Subgroup 50

The AIACHNE (AI/ML Informed cAlifornium CHi Nuclear data Experiment) project aims at designing an experiment for the 252 Cf Prompt Fission Neutron Spectrum (PFNS) that explores systematic biases in an experimental database retrieved from the EXFOR databases. To that end, machine learning (ML) methods were applied to pint-point measurement features likely related to bias. From that information, we selected a feature that should be explored by the AIACHNE experiment. Measurement features are metadata encapsulating all pertinent information about the physical measurement and analysis techniques. Examples are, for instance, what neutron and fission detectors were used for the physical metadata, and what background reduction techniques were employed for analysis techniques. Such metadata were retrieved both from EXFOR entries as well as the literature of data sets described in detail in Reference 2 (at the end of the article).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Machine learning guided selection of broad-spectrum epitope-specific functional antibodies for "Disease X"

Our project established and demonstrated a transfer learning framework that enables prediction of antibody–antigen interactions across related viruses. The approach focused on three major activities: 1. Conserved region and epitope identification – We compared viral protein structures and sequences to identify shared receptor-binding domains and neutralizing epitope regions across variants and related viruses. These conserved features formed the foundation for discovering broadly functional antibodies. 2. Machine learning model development – We built neural network–based models that integrate epitope features with antibody sequence information. Instead of relying solely on structural or physical properties, the models learned transferable patterns that describe antibody binding potential across different viral families. 3. Transfer learning and validation – Using SARS-CoV-2 and Ebola as source systems, we successfully transferred learned epitope features to predict antibody interactions for SARS CoV-1 and Marburg virus. Iterative cycles of dataset generation, retraining, and evaluation improved generalization and predictive power, ensuring the framework can adapt to new threats.

59 BASIC BIOLOGICAL SCIENCES↗

Machine Learning Using Rapidity-Mass Matrices for Event Classification Problems in HEP

In this work, supervised artificial neural networks (ANN) with rapidity–mass matrix (RMM) inputs are studied using several Monte Carlo event samples for various pp collision processes. The study shows the usability of this approach for general event classification problems. The proposed standardization of the ANN feature space can simplify searches for signatures of new physics at the Large Hadron Collider (LHC) when using machine learning techniques. In particular, we illustrate how to improve signal-over-background ratios in the search for new physics, how to filter out Standard Model events for model-agnostic searches, and how to separate gluon and quark jets for Standard Model measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Physical effects in cavitating flows

The microscopic and macroscopic aspects of the physical effects of cavitating flows are discussed. The microscopic features are related to the properties of nuclei in liquids and to the moderate tensile strengths which are usually encountered in flows. The macroscopic features are concerned with the growth of vapor or gaseous cavities from a small initial size and with their eventual collapse. Mathematical models are developed to analyze the characteristics of: (1) tensile strength in liquids, (2) growth of vapor bubbles, and (3) collapse of vapor bubbles.

Plesset, M. S.↗

Galactic civilizations: Population dynamics and interstellar diffusion

The interstellar diffusion of galactic civilizations is reexamined by potential theory; both numerical and analytical solutions are derived for the nonlinear partial differential equations which specify a range of relevant models, drawn from blast wave physics, soil science, and, especially, population biology. An essential feature of these models is that, for all civilizations, population growth must be limited by the carrying capacity of the environment. Dispersal is fundamentally a diffusion process; a density-dependent diffusivity describes interstellar emigration. Two models are considered: the first describing zero population growth (ZPG), and the second which also includes local growth and saturation of a planetary population, and for which an asymptotic traveling wave solution is found.

Newman, W. I.↗

Upper limits of narrow annihilation lines in gamma-ray bursts

The SMM gamma-ray experiment has observed 60 gamma-ray bursts from March 1980 to August 1982. Details of one burst are illustrated. There is weak evidence for a broadened spectral feature early in the burst, which was also detected by the Konus experiment. The present detailed search is limitd to narrow lines (less than 70 keV FWHM) near 500 keV; none is found in any of the bursts. This absence contrasts with the reported detection of several broader features (Mazets et al., 1981). The implications for the physical conditions in the annihilation region are discussed.

Nolan, P. L.↗