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At least 19 records

Velocity- and pressure-based metrics for estimating strike injuries during fish passage through hydro turbines

Hydropower is a crucial source of clean and reliable energy worldwide, and its importance will continue to grow. To enhance the environmental sustainability of hydropower development and operations, it is essential to predict the strike injury rates of fish passing through turbines accurately and cost-effectively. However, conventional experiments involving a large number of live fish are still commonly conducted in practice, and previous attempts mainly focused on the dose-response relationships at an individual level or relative comparisons of biological characterization between different conditions. Thus, this study proposes two novel strike metrics based on velocity and pressure (M V and M P ) measured by the cutting-edge Sensor Fish (SF) technology, designed to quantify the biological effects of strikes and collisions between fish and rigid hydraulic structures. SF measurements and 48-hour survival rates of live fish from a study conducted at the Ice Harbor Dam on the Snake River were used to establish thresholds for the two proposed metrics. These metrics and thresholds were then applied to three additional SF studies conducted at hydropower facilities featuring Kaplan turbines within the Columbia River basin. Results from the application of the strike metrics indicate that the estimated survival rates derived from both metrics agree well with previously reported live fish survival rates. Furthermore, the study identified specific passage regions with elevated risks of fish mortality due to strikes and collisions. Overall, the proposed strike metrics present a reliable and cost-effective approach to reducing reliance on live fish and lowering costs in fish passage studies.

Biological characterization

Matrix-based Omnidirectional Pressure Integratio

This software enables the calculation of the pressure field based on experimental velocity measurements utilizing the matrix-based omnidirectional pressure integration algorithm developed by Dr. John Charonko and Dr. Fernando Zigunov, which is several orders of magnitude faster than the current state of the art.

Zigunov, Fernando

Pressure-Gradient-Based RANS Model for Predicting Separation in Transitional and Turbulent Flows

Predicting flow separation poses a significant challenge for RANS models, particularly in transitional flows over airfoils. We propose a novel improvement to RANS models to predict incipient separation in both transitional and fully turbulent flows. Our approach modifies the eddy viscosity model in regions indicated by a pressure-gradient criterion that accounts for intermittency - determining whether the boundary layer is laminar or turbulent. This model demonstrates robust generalization across various airfoil shapes and Reynolds numbers. Applied to the NREL Phase VI wind turbine rotor, our model shows improved aerodynamic performance predictions compared to the baseline RANS model.

k-omega SST

Using Apptainer in a Pilot-based Distributed Workload

GlideinWMS is a pilot and pressure-based workload manager for distributed scientific computing. Many experiments like CMS and Fermilab’s Neutrino experiments use it to provision elastic clusters for their analysis and simulations, split into close to a million concurrent jobs. Most user jobs require containers, and the pilots use Apptainer to set up the desired platform. For the pilots that run as regular batch jobs, Apptainer is safer, lighter, and easier to use than other containerization solutions. Many images used by the pilots are expanded SIF images distributed via the CernVM-FS: this combination is very efficient. At Fermilab, for example, we store on GitHub Dockerfiles that mimic the platform in the worker nodes of local clusters. GitHub workflows build and push the images to Docker Hub, and a service periodically pulls and converts them to the expanded SIF images in the CernVM-FS, so the scientists can find a familiar environment everywhere. Apptainer has also been used to run services inside the pilot jobs, like benchmarks that characterize the worker node being used, or a Triton Inference Server that allows sharing a GPU with all the jobs that run in parallel on a node.

Mambelli, Marco [Fermilab] (ORCID:0000000294892681

Melting and transport properties of Al 2⁢ O 3 at extreme conditions

The high-pressure, temperature phase diagram and transport properties of materials are of broad interest to planetary sciences and high-energy-density sciences and applications. Alumina (Al 2 O 3 ) or its various forms (e.g., solutions with other oxides or silicates) are important constituents in Earth’s and super-Earths’ mantles, common window materials in dynamic compression experiments, and standard pressure calibrators in diamond-anvil-cell experiments. Its structures and transport properties are of particular importance but have not been well studied at above 100 GPa pressures. Based on extensive first-principles molecular dynamics calculations, we obtain atomic level insights on structural differences and accurate results on electrical conductivity (σ dc ), thermal conductivity (κ), and reflectivity of Al 2 O 3 in several phases at pressures of ~130–1300 GPa and temperatures of 4000–20,000 K. We find the solid-to-liquid state changes of Al 2 O 3 are accompanied by an insulator-to-semimetal transition with enhanced σ dc and κ, which is similar to other silicates and oxides and can facilitate magnetic field generation in deep interiors of rocky planets. We also find the solid-to-solid transition (from Rh 2 O 3 (II) to CaIrO 3 ) is accompanied by negligible changes in σ dc and κ at 160 GPa, contrary to previous expectations, whereas another higher pressure phase transition (CaIrO 3 to U 2 S 3 at 450 GPa) is associated with increases in σ dc and κ. Furthermore, we show the transport properties can be enhanced by oxygen vacancy in Al 2 O 3 , but are not significantly affected by forming solutions with MgSiO 3 , particularly when in the solid states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Exploring the Effects of Varying Pre-Chamber Geometry in a Heavy-Duty Natural Gas Optical Engine under Dilution Conditions

Pre-chamber combustion is an advanced ignition strategy that has been shown to enhance spark ignition (SI) combustion stability in natural gas (NG) engines by providing distributed ignition sites from turbulent jets and enhancing main-chamber turbulence. Pre-chamber combustion has been proven especially advantageous compared to SI in ultra-lean and dilute operating conditions. This work involves experimental investigation of the effects of varying passive pre-chamber nozzle configuration on pre-chamber and main chamber combustion under simulated exhaust gas recirculation (EGR) dilution (0 and 20%) conditions in a heavy-duty, single-cylinder, optically accessible NG engine at stoichiometric fuel-air ratio. Pre-chamber nozzle configurations include four pre-chambers with constant nozzle area to pre-chamber volume ratio (A/V) with different nozzle sizes and orientations and one configuration with larger nozzles. The optical engine is operated in a skip-fire sequence consisting of 18 motored cycles followed by two consecutive fired cycles to elucidate the effect of combustion residuals (internal EGR) on combustion evolution. Pressure-based diagnostics are used to monitor pre-chamber and subsequent main chamber combustion, and optical diagnostics include high-speed OH* chemiluminescence to visualize the development of pre-chamber jets and the resulting ignition of the main chamber charge. Heat release analysis of the in-cylinder pressure data indicates that a faster pre-chamber pressure rise does not always translate into faster main-chamber combustion. The pre-chamber with the smallest nozzle diameter produced the highest pre-chamber pressure rise and fastest combustion under non-diluted conditions. However, dilution delays the main chamber ignition for smaller nozzles despite a comparable rise in pre-chamber pressure compared to configurations with larger nozzles. This effect is more pronounced for cycles with in-cylinder combustion residuals in addition to external dilution. Additionally, it was observed that pre-chambers with swirling nozzles have a faster pressure rise in the pre-chamber and main chamber under dilute conditions. Optical diagnostics suggest that the main reason for the delay between the pre-chamber pressure rise and main-chamber combustion lies in jet quenching and delayed re-ignition, which can even lead to misfire if jets emitted from small nozzles combined with dilution fail to re-ignite.

Dhotre, Akash [University Of Minnesota-Twin Cities

Automation of Nanoparticle Synthesis Processes in a Plasma Environment Using LabVIEW

This work presents an automated control system for the synthesis of nanomaterials by plasma-enhanced chemical vapor deposition (PECVD), implemented using the LabVIEW software environment. The main objective of the study is to develop an integrated hardware-software platform that enables sequential control of the key stages of the PECVD process, including vacuum chamber preparation, pressure monitoring, working gas supply, plasma ignition, power matching, cyclic nanomaterial growth, and optical monitoring of nanoparticles in the plasma environment. The use of LabVIEW made it possible to integrate actuator control, experimental parameter acquisition, and realtime process visualization within a single automated system. The automated cycle begins with evacuation of the reaction chamber to a predefined base pressure. Transition to the next stage is permitted only after the specified pressure threshold has been reached, ensuring reproducible initial conditions for each experiment. The program then controls the supply of the working gas through mass flow controllers (MFCs). In this work, two gas-flow control modes were considered: analog control using a 0-5 V voltage signal and digital communication via RS-232 interface. It was shown that the analog approach requires accurate scaling of the control voltage, since applying 5 V corresponds to full-scale opening of the controller and results in the maximum gas flow. In contrast, the RS232 interface enables the gas flow rate to be specified directly in sccm, improving the accuracy, flexibility, and convenience of gas-environment control. After pressure stabilization, LabVIEW initiates RF plasma ignition and executes the RF matching algorithm aimed at minimizing reflected power and improving the stability of the plasma process. A separate software module implements the cyclic nanomaterial growth mode, in which the plasma-on time, plasma duration, and total number of synthesis cycles are predefined. This approach makes it possible to control material accumulation on the substrate and to correlate the process parameters with the morphological characteristics of the resulting nanostructures. The final module of the system is designed for optical monitoring of the nanoparticle cloud density in dusty plasma. For this purpose, the change in the intensity of laser radiation passing through the plasma region is recorded using a photodetector and a Keithley 2401 measuring unit connected to LabVIEW via RS-232 interface. The difference between the initial and modified optical signal intensity is used as a diagnostic parameter characterizing the formation and temporal evolution of nanoparticles. The developed system demonstrates that LabVIEW can be effectively applied not only for the automation of individual instruments, but also for the implementation of a complete digital control cycle for PECVD-based nanomaterial synthesis.

PECVD

SAM Code Enhancements for Fission Product Tracking of Noble Gases and Metals in MSRs

This report documents fiscal year 2026 enhancements to the System Analysis Module (SAM) for modeling fission product transport in liquid-fueled molten salt reactors (MSRs). The work advances three principal areas: noble gas transport, noble metal deposition, and user interface improvements. The noble gas transport capability integrates drift-flux gas transport, Henry’s law two-film interphase mass transfer with pressure-based nucleation suppression, Knudsen-regime pore diffusion into porous graphite with a conjugate salt-graphite interface constraint, built-in material properties, five Sherwood-number mass transfer correlations including three derived from high-fidelity NekRS simulations, and xenon-135 reactivity feedback through SAM’s point-kinetics model. This work also presents a comprehensive verification test suite, including new analytically verified cases for pressure-dependent onset of interphase gas transfer in a stagnant vertical pipe, a postulated FLiBe-graphite Xe extraction permeator, a gravity riser with a fission-product source, and a descending pipe with gas redissolution driven by hydrostatic pressure. A machine learning framework for bubble rise velocity prediction in molten salt systems is developed and benchmarked on molten-salt and diverse aqueous bubble datasets. The best-performing fine-tuned transfer-learning networks achieve an 82% reduction in RMSE relative to the Clift correlation, and is implemented directly in SAM. The noble metal transport capability is developed, including a liquid-wall deposition model and a gas-surface flotation mechanism that transfers insoluble particles entrained by sparging gas to wetted structures. Verification tests and demonstration cases cover the surface deposition, flotation efflux, and flotation shedding. Finally, a new [SpeciesTransport] input structure replaces positional global vectors with selfcontained, order-independent, named species blocks, simplifies the specification of multiphase species and decay chains, and remains fully compatible with existing SAM input files. Together, these developments improve the physical fidelity, verification basis, and usability of SAM for system-level analyses of fissionproduct behavior in MSRs.

Mui, Travis (ORCID:0000000303736470)

Suppression of Collisionless Magnetic Reconnection in the High Ion β, Strong Guide Field Limit

Abstract In magnetic reconnection, the ion bulk outflow speed and ion heating have been shown to be set by the available reconnecting magnetic energy, i.e., the energy stored in the reconnecting magnetic field ( B r ). However, recent simulations, observations, and theoretical works have shown that the released magnetic energy is inhibited by upstream ion plasma beta β i —the relative ion thermal pressure normalized to magnetic pressure based on the reconnecting field—for antiparallel magnetic field configurations. Using kinetic theory and hybrid particle-in-cell simulations, we investigate the effects of β i on guide field reconnection. While previous works have suggested that guide field reconnection is uninfluenced by β i , we demonstrate that the reconnection process is modified and the outflow is reduced for sufficiently large β i > ( B r 2 + B g 2 ) / B r 2 . We develop a theoretical framework that shows that this reduction is consistent with an enhanced exhaust pressure gradient, which reduces the outflow speed as v out ∝ 1 / β i . These results apply to systems in which guide field reconnection is embedded in hot plasmas, such as reconnection at the boundary of eddies in fully developed turbulence like the solar wind or the magnetosheath as well as downstream of shocks such as the heliosheath or the mergers of galaxy clusters.

Giai, Carlos A.

Electrified vapour deposition at ultrahigh temperature and atmospheric pressure for nanomaterials synthesis

Vapour-phase synthesis methods have shown promise for the scalable synthesis of nanomaterials and coatings. However, the vaporization of different precursors for the synthesis of a broad nanomaterial space, particularly at atmospheric pressure, while maintaining compositional and structural control of the final product is challenging. Here we report the generation of an ultrahigh-temperature atomic vapour at atmospheric pressure based on electrified heating, for the growth of multi-elemental nanomaterials and thin films. This process relies on a reactor design whereby solid-state precursors are vaporized within a semi-confined space beneath an electrified heater that can reach ~3,000 K. The proximity of the heater rapidly breaks down the bonds of metal salt precursors and decomposes them into an atomic vapour that expands into a high-temperature (>2,000 K), highly reactive and high-flux vapour (10 21 –10 22 atoms per cm 2 per second) that travels upwards in a directional flow. When mixed with entrained ambient gases, the highly reactive atomic species rapidly nucleate and grow into the desired final products, including alloys, oxides, sulfides and thin films, which can be deposited on a low-temperature substrate. This EVD approach can synthesize a broad range of functional nanomaterials at atmospheric pressure, including single-phase multi-elemental nanomaterials formed under thermodynamically non-equilibrium conditions.

36 MATERIALS SCIENCE

Absorber Clamp for Microcalorimeter Decay Energy Spectrometry

Microcalorimeter Decay Energy Spectrometry (DES) is of interest to nuclear safeguards due to its ability to provide high precision isotopic compositions of nanogram-to microgram-scale samples of Pu and U and related daughter products. The DES method is able to record decay energy of each alpha-decay event in a sample that is embedded in a metal matrix (absorber) and thermally linked to a microcalorimeter detector. This work optimizes the DES technique used to thermally link the absorber and microcalorimeter detector element to allow for more rapid assembly and to increase detector performance and operating life. Optimized attachment methods are crucial for enhancing the viability of DES in high-sample-throughput facilities, such as those that support international nuclear safeguards measurements. Here, in this study, we designed and implemented a pressure-based absorber clamp and evaluated the performance of this new attachment method relative to pressed indium bond attachment. Results using the absorber clamp demonstrate a streamlined detector assembly procedure that minimizes accidental damage to detectors, as well as increasing detector pulse speeds by 57%. Spectral comparison shows the clamp preserves detector performance relative to indium attachment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

Enhancement of antiferromagnetic spin fluctuations in UTe2 under pressure revealed by 125 Te NMR

Characterizing magnetic fluctuations is one of the keys to understanding the origin of superconductivity in the spin-triplet superconductor UTe 2 , which exhibits two superconducting (SC) phases (SC1 and SC2) under pressure: SC1 where the superconducting transition temperature of 𝑇c decreases with pressure, whereas 𝑇c of SC2 rises with pressure. Previously, D. Ambika et al. [Phys. Rev. B 105, L220403 (2022)] reported the possible coexistence of ferromagnetic (FM) and antiferromagnetic (AFM) spin fluctuations in UTe2 under pressure from their nuclear magnetic resonance (NMR) measurements. To delve into the relationship between the magnetic fluctuations and the two SC phases, we have carried out detailed 125 Te NMR measurements on a single crystal of UTe2 with 𝑇c=1.6K at various pressures ranging from 0 to 2.05 GPa. By comparing the temperature 𝑇 dependence of nuclear spin-lattice relaxation rates divided by temperature 1/𝑇1⁢𝑇 with that of the Knight shift 𝐾 for magnetic fields along the 𝑎, 𝑏, and 𝑐 directions, we evidence the enhancement of AFM spin fluctuations with increasing pressure. Based on the results, we suggest that FM spin fluctuations are more favorable for SC1 and AFM spin fluctuations are crucial for SC2. Our work will inspire further study on this material to understand the peculiar SC phases in detail.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Generalizing synthetic data-trained acoustic predictive models to real-world measurements

Acoustic Resonance Spectroscopy (ARS) is highly sensitive to structural properties such as material, geometry, and environmental conditions; as a consequence, it can noninvasively measure internal properties that are unobservable by most other methods. Because of its sensing capabilities and low implementation cost and complexity, ARS has potential as a paradigm shift in noninvasive sensing, characterization, and monitoring applications. However, extracting specific properties from ARS measurements, comprising the vibration spectrum of a test object, is challenging due to the sensitivity of the spectra to other structural changes not being measured, e.g. manufacturing tolerances, component coupling, environmental variation, etc. Neural Networks are promising tools for identifying trends in ARS measurements, but their training typically requires large datasets, which are often impractical to obtain for real-world systems. Synthetic data can be simulated efficiently, but discrepancies between synthetic and real-world data frequently lead to poor generalization when testing on the real-world data. We propose a novel ARS model training framework that enables networks trained exclusively on synthetic ARS data to generalize effectively to real-world measurements. Our approach leverages the Correlation Alignment (CORAL) technique to enforce the extraction of features common to both synthetic and real-world domains. As a case study, we demonstrate noninvasive ARS-based pressure measurements in sealed systems. Finite element method (FEM) simulations were used to generate synthetic training data across diverse vessel configurations and pressure conditions, and model performance was then tested on real-world measurements. We demonstrate that robust machine learning models for ARS can be developed without large real-world datasets, significantly broadening the applicability of ARS for noninvasive sensing. Moreover, the approach is extensible to other sensing modalities where synthetic data are abundant but real-world data are limited.

36 MATERIALS SCIENCE

Microstructure-based modeling of inner oxygen pressure in solid oxide electrolysis cells: Analysis of electrode delamination and mitigation

One major degradation mechanism during long-term operation of solid oxide electrolysis cells (SOECs) is delamination of oxygen electrodes (OEs). The driving force for the electrode delamination could be the generated high inner oxygen pressure near the electrode-electrolyte interface during operation. However, the effects of transport properties and electrode thickness on the inner oxygen partial pressure are not well understood. Here a microstructure-based electrochemical model, which includes the conduction of electrons and oxygen ions coupled with Butler-Volmer-type chemical reactions at triple-phase-boundaries (TPBs), is employed to investigate the oxygen pressure in lanthanum strontium manganate (LSM)-based SOECs. The model is applied to both two-dimensional (2D) prototype microstructures and three-dimensional (3D) realistic microstructures, and the oxygen pressure is analyzed as a function of transport properties and electrode thickness under both potentiostatic and galvanostatic operations. The simulation results suggest strategies to suppress electrode delamination. The simulation results are compared to an analytical solution, and the discrepancies are attributed to the Butler-Volmer-type kinetics included in the microstructure-based model.

25 ENERGY STORAGE

Microstructure-Based Modeling of Inner Oxygen Pressure in Solid Oxide Electrolysis Cells

One major degradation mechanism during long-term operation of solid oxide electrolysis cells (SOECs) is delamination of oxygen electrodes (OEs). The driving force for the electrode delamination could be the generated high inner oxygen pressure near the electrode-electrolyte interface during operation. However, the effects of transport properties and electrode thickness on the inner oxygen partial pressure are not well understood. Here, a microstructure-based electrochemical model which includes the conduction of electrons and oxygen ions coupled with Butler-Volmer-type chemical reactions at triple-phase-boundaries (TPBs), is employed to investigate the oxygen pressure in lanthanum strontium manganate (LSM)-based SOECs. The model is applied to both two-dimensional (2D) prototype microstructures and three-dimensional (3D) realistic microstructures, and the oxygen pressure is analyzed as a function of transport properties and electrode thickness under both potentiostatic and galvanostatic operations. The simulation results suggest strategies to suppress electrode delamination. The simulation results are compared to an analytical solution, and the discrepancies are attributed to the Butler-Volmer-type kinetics included in the microstructure-based model.

Xue, Fei

Use of Fisher's Ratio assisted multivariate curve resolution- alternating least squares for discovery-based analysis using ultrahigh pressure liquid chromatography-high resolution mass spectrometry

Non-targeted analysis of complex chemical mixtures can be difficult considering the convoluted nature of the matrix and the potential unknown chemical differences between samples or classes of samples. Ultrahigh pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) is an ideal technique to probe chemical differences for a wide variety of samples. While UHPLC-QTOF can discover minute chemical differences down to low part per billion (ppb) concentrations with a high degree of confidence, the application of high-resolution mass spectrometry can yield massive amounts of information (∼ 10 gb per sample) that cannot be analyzed manually. Therefore, the application of chemometric techniques is mandatory for the interrogation of complex samples. Fisher's ratio (FR) assisted multivariate curve resolution-alternating least squares (MCR-ALS) was used to the discover and identify the chemical differences between two classes of materials: 1) a pond water matrix and 2) the matrix spiked with a pharmaceutical standard mix containing 17 compounds. Thirteen of the seventeen spiked compounds were discovered using FR analysis, and then five were successfully deconvoluted using MCR-ALS wherein the number of curves chosen were automatically determined using singular value decomposition (SVD). In conclusion, the use of an automated FR assisted MCR-ALS will aid in discovering trace levels of chemical components without the need for the researcher to provide potentially biased input which will aid in non-targeted workflow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

The Surface Chemistry of Methanol on TiO 2 (110): Effects of Pressure and Temperature on the Stability of C–O and C–H Bonds

Synchrotron-based ambient pressure X-ray photoelectron spectroscopy (AP-XPS) was used to study the surface chemistry of methanol on TiO 2 (110), examining the effects of methanol pressure, oxide temperature, and coadsorption with H 2 . At 300 K, the adsorption of methanol on TiO 2 (110) leads to the formation of CH 3 O on the surface with a minor amount of CH 3 OH present. The easy cleavage of the O–H bond in the alcohol agrees with the predictions of theoretical calculations, and most of the adsorbed CH 3 O was not associated with the presence of Ti 3+ sites in the oxide substrate. The adsorbed CH 3 O was removed from the TiO 2 (110) surface by heating to 600 K without the deposition of CH x fragments or C on the oxide. The results of temperature-programmed desorption (TPD) showed the evolution of methanol and formaldehyde at 360 and 490 K as a result of a disproportionation reaction: 2CH 3 O → CH 3 OH + CH 2 O. This surface chemistry, where there is no rupture of the C–O bond, and only selective cleavage of O–H and C–H bonds, is very different from that found on metals used in catalysts for methanol reforming, where massive conversion of the alcohol into CO, CH x and C species is seen. Furthermore, the TPD data indicate that any CH 3 O formed on the oxide surface can be hydrogenated and desorbed as CH 3 OH at temperatures below 550 K. In this respect, titania is an ideal support for catalysts employed to achieve methanol synthesis through CO 2 hydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

LiPF 6 under pressure: a symmetry-mode-based structural analysis

The lithium salt LiPF 6 is a key component in commercial lithium-ion battery (LIB) electrolytes. However, its structural properties under pressure remain unexplored, despite increasing interest in the effect of pressure on electrolyte behaviour, and a growing interest in high pressure synthesis of new Li-hexafluoride cathode materials. Here, we present the first high pressure neutron diffraction study of solid LiPF 6 up to 7.4 GPa. Refinements reveal that the ambient rhombohedral structure (space group R$\overline{3}$) remains stable throughout, with pressure accommodated primarily by tilting of the corner-shared LiF 6 and PF 6 octahedra and contraction of the LiF 6 units. In conclusion, this study establishes a foundation for understanding the phase behaviour of Li-based hexafluorides under extreme conditions.

25 ENERGY STORAGE