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At least 109 records · Page 6

Distribution System Resilience Assessment Considering PV Vulnerabilities for Hurricane Events

Distribution networks are increasingly vulnerable to damage and outages from extreme weather events. The integration of solar photovoltaics (PVs) further complicates resilience analysis due to its weather-dependent nature. However, limited research has examined the impacts of weather on PVs under severe events like hurricanes. This paper proposes a probabilistic framework to assess distribution system resilience considering PV vulnerabilities during hurricanes. The framework incorporates (i) a spatiotemporal fragility model to evaluate failure probabilities for distribution lines and PVs, and (ii) resilience indices at both system and component levels. The approach offers valuable insights into the resilience of modern distribution grids under extreme weather conditions. Numerical results on the unbalanced IEEE 123-bus test system validate the effectiveness of the framework.

Vahedi, Soroush [University of Connecticut, Storrs

Detecting outbreaks using a spatial latent field

In this paper, we present a method for estimating the infection-rate of a disease as a spatial-temporal field. Our data comprises time-series case-counts of symptomatic patients in various areal units of a region. We extend an epidemiological model, originally designed for a single areal unit, to accommodate multiple units. The field estimation is framed within a Bayesian context, utilizing a parameterized Gaussian random field as a spatial prior. We apply an adaptive Markov chain Monte Carlo method to sample the posterior distribution of the model parameters condition on COVID-19 case-count data from three adjacent counties in New Mexico, USA. Our results suggest that the correlation between epidemiological dynamics in neighboring regions helps regularize estimations in areas with high variance (i.e., poor quality) data. Using the calibrated epidemic model, we forecast the infection-rate over each areal unit and develop a simple anomaly detector to signal new epidemic waves. Our findings show that anomaly detector based on estimated infection-rates outperforms a conventional algorithm that relies solely on case-counts.

Safta, Cosmin [Sandia National Laboratories (SNL-C

Evaluation of UKESM aerosol size and composition using ATom measurements indicates missing marine aerosol formation mechanisms

Atmospheric aerosols influence climate through their interactions with radiation and clouds, yet large uncertainties remain in their simulation by global models. This study evaluates the United Kingdom Earth System Model version 1.1 (UKESM1.1) using global-scale aircraft observations from the Atmospheric Tomography (ATom) mission, focusing on aerosol lifecycle processes in the remote marine atmosphere. We assess model performance in simulating aerosol precursor vapours, number size distributions, chemical composition, and environmental conditions. Several process improvements are tested, including sulfuric acid-ammonia nucleation, ammonium nitrate scheme, methanesulfonic acid condensation, and low-temperature isoprene-derived secondary organic aerosol formation. Model biases differ significantly between the upper troposphere (UT) and the marine boundary layer (MBL). In the UT, UKESM1.1 overestimates nucleation and Aitken mode particles while underestimating accumulation mode, indicating insufficient growth. In the MBL, the model overestimates primary aerosols (e.g. seasalt) and precursor gases but underestimates nucleation and Aitken mode particles, even after incorporating updated nucleation and ammonium nitrate scheme. The persistence of low aerosol number concentrations, despite overestimated precursors, suggests missing formation pathways likely involving other species such as iodine, amines, and organic vapours. These limitations result in an unbalanced cloud condensation nuclei budget that over-relies on primary emissions. Sensitivity tests reveal that model outputs are strongly influenced by dimethyl sulfide emissions and vapour condensation schemes. Our results highlight the need for future model development to prioritise mechanistic representation of currently missing aerosol sources, rather than relying on empirical tuning, to improve aerosol-climate interaction estimates.

He, Xu-Cheng [Univ. of Cambridge (United Kingdom);

Emittance Measurements with Wire Scanners in the Fermilab Side-coupled Linac

The Fermilab Side-Coupled Linac accelerates H-beam from 116 MeV to 400 MeV through seven 805 MHz modules. Twelve wire scanners are present in the Side Coupled Linac and four are present in the transfer line between the Linac and the Booster synchrotron ring. These wire scanners act as important diagnostic instruments to directly collect information on the beam's transverse distribution. The manipulation of the conditions of wire scanner data collection enables further characterization of the beamline, such as calculating emittance and the Twiss parameters of the beam at select regions, which we present here.

43 PARTICLE ACCELERATORS

Rehydration of metastudtite in the alteration kinetics of α– and β–U 3 O 8 in dilute aqueous solutions of hydrogen peroxide

The formation of alteration phases on uranium ore concentrates and used nuclear fuels under oxidizing conditions is key to understanding the potential mobility of radionuclides in the environment and designing optimal storage conditions of materials. However, the time-dependent distribution of alteration phases on α– and β–U 3 O 8 under oxidizing conditions has yet to be explored. Here, in this study, crystalline powders of α– and β–U 3 O 8 were submerged in aqueous solutions of hydrogen peroxide (1.6 × 10 −1 to 5.4 × 10 −5 M) with aliquots of solution and solid removed for analysis at 1, 8, 15, 22, 29, 36, 46, 58, 71, and 83 days. Within one day there is significant alteration of U 3 O 8 to the uranyl peroxide metastudtite, [(UO 2 )(O 2 )(H 2 O) 2 ], that is replaced by studtite, [(UO 2 )(O 2 )(H 2 O) 2 ]·2H 2 O, within a week regardless of the polymorph of U 3 O 8 or the initial concentration of H 2 O 2 in solution, as determined by partial least squares regression (PLSR) of Raman spectra collected from the solids. A dissolution/reprecipitation mechanism is proposed for both the alteration of U 3 O 8 to metastudtite and the subsequent alteration of both U 3 O 8 and metastudtite to studtite. The two polymorphs of U 3 O 8 exhibit similar rates and extents of alteration over time. The rehydration of metastudtite to studtite has not been previously reported and highlights the need for future work to determine the mechanism by which metastudtite is converted to studtite and what other conditions facilitate this rehydration.

Alteration of U3O8

Probing gluon saturation with forward di-hadron correlations in proton-nucleus collisions

We present a detailed numerical investigation of semi-inclusive forward di-hadron production in proton–nucleus collisions employing the Color Glass Condensate effective theory. We focus on the regime where di-hadrons are produced nearly back-to-back in the transverse plane, thereby justifying a transverse-momentum-dependent factorization approach in terms of small-x gluon distributions. Our computation integrates several key elements: i) non-linear rapidity evolution via the Balitsky–Kovchegov equation with running coupling, ii) both perturbative and non-perturbative Sudakov resummation, and iii) a phenomenologically constrained model for the initial conditions for small-x gluon distributions. We compare this phenomenological framework to experimental data from the STAR Collaboration on azimuthal correlations in forward di-pion production in both proton–proton and proton–gold collisions. We analyze the systematic theoretical uncertainties associated with the saturation scales of nuclei at the initial scale for rapidity evolution and with those associated with the hadronization process. Finally, we make predictions for the kinematics anticipated to be covered by the ALICE Forward Calorimeter (FoCal) upgrade at the Large Hadron Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Approximating the particle distribution in rotating and tandem mirror traps

Steady-state distribution functions can be used to calculate stability conditions for modes, radiation energy losses and particle loss rates. Heuristic analytic approximations to these distributions can capture key behaviors of the true distributions such as the relative speeds of different transport processes while possessing computational advantages over their numerical counterparts. In this paper, we motivate and present a closed-form ana- lytic model for a distribution of particles in a centrifugal or tandem mirror. We find that our model outperforms other known models in approximating numerical steady- state simulations outside of a narrow range of low confining potentials. We demonstrate the model’s suitability in the high confining potential regime for applications such as loss-cone stability thresholds, fusion yields and available energy.

Li, G.X.

Approximating the particle distribution in rotating and tandem mirror traps

Steady-state distribution functions can be used to calculate stability conditions for modes, radiation energy losses and particle loss rates. Heuristic analytic approximations to these distributions can capture key behaviors of the true distributions such as the relative speeds of different transport processes while possessing computational advantages over their numerical counterparts. In this paper, we motivate and present a closed-form analytic model for a distribution of particles in a centrifugal or tandem mirror. We find that our model outperforms other known models in approximating numerical steady-state simulations outside of a narrow range of low confining potentials. We demonstrate the model’s suitability in the high confining potential regime for applications such as loss-cone stability thresholds, fusion yields and available energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Expansion dynamics of femtosecond laser-induced plasmas: Influence of thermophysical plasma properties

This study investigates the expansion dynamics of femtosecond laser-induced plasmas, emphasizing the impact of plasma thermophysical properties and ambient gas composition. Through shadowgraphy experiments and multiphase computational fluid dynamics (CFD) simulations, the influence of parameters such as heat capacity, molecular weight, and thermal conductivity on plume morphology, shockwave evolution, and energy dissipation mechanisms is examined. A mixture multiphase model is implemented to capture the interaction between the plasma and the surrounding gas. Simulation results reveal that plasma expansion is strongly inertia-driven. Results show that differences in plasma properties and ambient conditions affect the shape and temperature distribution of the expanding plume. The early-stage dynamics are primarily dictated by pressure forces, whereas thermal and viscous effects play a growing role in the plume's behavior during later stages of expansion. The CFD findings show the necessity of accurate initial condition characterization, including crater geometry and plasma pressure and temperature, for reliable modeling of plasma evolution in laser ablation processes.

CFD modeling

Statistical Uncertainty of Inhalation Dose Coefficients: Impact of Particle Deposition in ICRP 66 Human Respiratory Tract Model

Inhaled radioactive materials can pose a long-term health concern, as the material can be incorporated into the body’s metabolic pathways and remain in organs and tissues for extended durations. During the retention period, the radioactive material may localize in a source organ and irradiate adjacent target organs and tissues. Distribution of these materials changes over time, requiring biokinetic modeling to evaluate their movement through various tissues and organs. The evolving distribution depends on multiple inputs characterizing the inhaled material, such as particle size and size distribution, particle density, aspect ratio, specific radionuclide, the chemical form, and solubility. In addition, biological parameters such as breathing rate, breathing type (nasal or nasal/oral), respiratory system morphometry, tidal volume, functional residual capacity, and anatomical dead space all influence material transport. These aerosol properties and physiological characteristics of the respiratory tract jointly define a range of initial conditions that influence the time-dependent distribution of radioactive material. To evaluate both uncertainty in the initial conditions of inhalation exposure and the final output (committed effective dose) from biokinetic models, a Python-based software tool, Radiological Exposure Dose Calculator (REDCAL), was developed to propagate uncertainty within the human respiratory tract model. Focusing on deposition fraction uncertainty, the primary objective was to characterize the initial activity distribution across respiratory regions as a function of anticipated particle sizes and distributions. The impact of the deposition fraction uncertainty was propagated to committed effective dose coefficients for selected radionuclides in a companion publication. For each particle size, a lognormal distribution, characterized by its geometric mean as defined within ICRP Publication 66, serves as the basis for introducing uncertainty into the physical processes governing deposition in various lung regions. Finally, this study addresses the deposition process and examines how uncertainty in deposition mechanisms affects activity distribution in the airways, ultimately presenting the expected range and standard deviation of deposited activity as a function of particle size.

International Commission on Radiological Protectio

A Review on Building Resilient Power Networks: Emphasizing Adjacent Span Dynamics

This research article presents a comprehensive review of resilience in power transmission and distribution systems, focusing on key studies that examine structural integrity, mechanical stress distribution, and system reliability under various conditions. The article synthesizes findings across multiple studies, covering assumptions, system topologies, methodologies, and challenges that affect resilience in these networks. Particular attention is given to identifying studies that address the influence of adjacent spans and tower--line interactions, as these factors play a crucial role in the stress distribution and structural dynamics within poles, towers, and transmission lines. In addition to identifying critical factors contributing to system vulnerability, this review emphasizes the importance of continued research to better understand and mitigate risks from extreme events, such as high winds combined with ice storms. By consolidating knowledge on current challenges and future needs, this work outlines future directions to advance resilience studies and contributes to ongoing efforts to strengthen power transmission and distribution networks, reducing disruptions in electricity supply and improving overall system resilience in an evolving climate landscape.

Ahmad, Tawsif [Pacific Northwest National Laborato

Multi-scale structural analysis of swift heavy ion-irradiated ZrO 2 and HfO 2

The radiation-induced monoclinic-to-tetragonal phase transition in ZrO 2 and HfO 2 has been the subject of many investigations, but the transformation pathways and underlying structural mechanisms are still not well understood. In this study, microcrystalline powder samples of ZrO 2 and HfO 2 were irradiated with 946 MeV and 1470 MeV Au ions to a wide fluence range up to 3 × 10 13 ions/cm 2 . To characterize beam-induced structural modifications across all spatial length scales, complementary experimental techniques such as synchrotron X-ray diffraction and spallation neutron total scattering were used. The phase evolution of the tetragonal polymorph with increasing ion fluence is accurately described by a heterogeneous track-overlap model that incorporates both direct- and double-impact processes. These damage accumulation processes are an expression of a core-shell ion track morphology that depends on irradiation conditions and target material. Neutron pair distribution function analysis revealed that ion-beam-induced tetragonal ZrO 2 is merely a configurational average of short-range orthorhombic (Pbcn) domains stabilized by a dense network of domain walls. Furthermore, this knowledge is critical for a better understanding of how crystalline-to-crystalline phase transformations proceed at the atomic scale under extreme conditions.

Monoclinic-to-tetragonal phase transformation

Continual Learning for Particle Accelerators

Particle accelerators operate under dynamically changing conditions, which often lead to data distribution drifts. These drifts pose significant challenges for Machine Learning (ML) models, which typically fail to maintain performance when faced with such non-stationary data. In particle accelerators, the primary sources of these data drifts include changes in accelerator settings and non-measured parameters such as machine degradation and environmental factors. Previous research has proposed conditional models to handle multiple beam configurations effectively; however, it is challenging to train the ML models on all possible configuration settings. Additionally, conditional models alone can not address performance degradation caused by drifts due to non-measured factors. These limitations contribute to a significant gap between ML development and its deployment in real-world operational settings. To bridge this gap, in this paper, we identify some of the key areas within particle accelerators where continual learning can help mitigate drift-induced performance degradation. In addition, we present a practical use case where a conditional Auto-Encoder model coupled with memory-based continual learning has been employed to demonstrate stable performance even when underlying data drifts.

Schram, Malachi [Thomas Jefferson National Acceler

Continual Learning for Particle Accelerators

Particle accelerators operate under dynamically changing conditions, which often lead to data distribution drifts. These drifts pose significant challenges for Machine Learning (ML) models, which typically fail to maintain performance when faced with such non-stationary data. In particle accelerators, the primary sources of these data drifts include changes in accelerator settings and non-measured parameters such as machine degradation and environmental factors. Previous research has proposed conditional models to handle multiple beam configurations effectively; however, it is challenging to train the ML models on all possible configuration settings. Additionally, conditional models alone can not address performance degradation caused by drifts due to non-measured factors. These limitations contribute to a significant gap between ML development and its deployment in real-world operational settings. To bridge this gap, in this paper, we identify some of the key areas within particle accelerators where continual learning can help mitigate drift-induced performance degradation. In addition, we present a practical use case where a conditional Auto-Encoder model coupled with memory-based continual learning has been employed to demonstrate stable performance even when underlying data drifts

Rajput, Kishansingh [Thomas Jefferson National Acc

Heat load measurements for the PIP-II pHB650 cryomodule

This study presents a brief overview of the 1st and 2nd phases and an in-depth analysis of the 3rd phase heat load testing performed on the pHB650 (prototype High Beta 650 MHz) cryomodule at PIP2IT (PIP-II Injector Test Facility), with a focus on both the results and the methodological advancements that have improved testing efficiency and accuracy. A key challenge identified in the testing campaign is the higher-than-expected heat loads observed in the first PIP-II (Proton Improvement Plan II) prototype cryomodules (pSSR1 and pHB650) tested at PIP2IT. Elevated heat loads are concerning given the fixed capacity of the PIP-II cryoplant that is currently being installed at Fermilab. However, understanding the sources of these elevated heat loads offers a critical opportunity to implement effective heat load mitigations on upcoming PIP-II cryomodules to stay within the available capacity of the PIP-II cryoplant. The study includes a summary of test results, descriptions of measurement procedures, and key observations on parameters directly and indirectly related to heat load measurements. Direct observations include measured heat loads and the effectiveness of JT heat exchanger under varying conditions, while indirect observation analyze factors such as the temperature distribution on the two-phase pipe and relief piping under varying conditions. Thermal acoustic oscillations (TAO) were identified during testing, which was mitigated by replacing the original G10 stem with a stainless steel stem equipped with wipers for the cryomodule cooldown valve. A major innovation during pHB650 Phase 3 testing was the development of an automated Python script to streamline data acquisition, analysis, and reporting of heat load results. This script automatically retrieved data from ACNET (Accelerator Control Network), performed heat load calculations, and generated detailed reports featuring plots and tables. This advancement significantly reduced manual labor and enhanced the thoroughness of data analysis compared to earlier campaigns. The heat load test reports were promptly uploaded to the electronic logbook shortly after each test, enabling rapid feedback and collaboration between the SRF and cryogenic teams. The heat load measurements included various components: HTTS (high-temperature thermal shield), LTTS (low-temperature thermal shield), 2K isothermal and non-isothermal heat loads. Results were recorded both within the cryomodule and between the bayonet can supply and return. Measurements were conducted under different operating conditions such as "standard", "linac", and "simulated dynamic". Additionally, HTTS and LTTS heat loads were calculated in real time, allowing for the tracking of thermal stability and identification of changes during testing, both in steady-state and transient conditions. The results of this testing campaign not only provide valuable insights into the performance of the pHB650 cryomodule but also highlight best practices and lessons learned that will inform future cryomodule testing at PIP2IT. These include adopting automated tools for data analysis, refining real-time measurement capabilities, and emphasizing detailed pre-test planning. The framework established in this campaign aims to set an improved standard for cryomodule testing and heat load reporting in future cryomodule test campaigns.

Porwisiak, D. [Fermilab; Wroclaw Tech. U.]

Insights into determining pore size properties of ultrafiltration membranes

The selectivity of porous membranes is often characterized using solute rejection tests, where membranes are challenged with dilute aqueous solutions of neutral solutes at operating conditions that minimize concentration polarization and fouling. In single solute tests, a membrane is challenged with one molecular weight (MW) solute at a time from low to high MW. Since single solute methods are time-intensive, mixed solute tests have become more common, where a mixture of several MW solutes challenges a membrane at once. However, the presence of large solutes in a mixture increases the rejection of smaller solutes. Furthermore, there are no universally accepted operating conditions or standard methods used by membrane manufacturers or researchers for the experiments, leading to difficulty in pore size and pore characteristic comparisons. In this paper, commercial ultrafiltration membranes were challenged with single and mixed solute polyethylene glycol (PEG) and dextran aqueous solutions. First, rejection values determined using total organic carbon (TOC) and high-performance liquid chromatography (HPLC) from single solute filtration experiments are compared. Differences in rejection curves obtained by the two techniques are attributed to solute polydispersity. Mixed solute filtration experiments with binary mixtures of solutes showcased co-solute interactions, which increase with both the size and weight percent of large solute in the mixture. Mixed solute filtration experiments at varying operating conditions (i.e., stir speed and flux) were conducted to determine operating conditions that mitigate co-solute interactions. Stir speed had a minimal effect on co-solute interactions. In contrast, low flux conditions can help minimize co-solute interactions, leading to pore size distributions that closely resemble results observed in single solute filtration using narrowly dispersed solutes. Additionally, at low flux conditions, the predicted membrane pore size distributions utilizing mixed solute experiments with PEG and dextran were similar.

36 MATERIALS SCIENCE

Department of Transportation PHMSA Aerosol Spray Project: Phase-0

This report discusses the work conducted at Sandia National Laboratories during the preliminary phase (Phase-0) of the Department of Transportation (DOT) Pipeline and Hazardous Materials Safety Administration (PHMSA) project tasked to better understand what happens to a high-pressure liquid canister or vessel during a fire in which an accidental instantaneous release occurs. Phase 0 had two main objects: (1) to establish a methodology for the high temperature and pressure spray vessel release and (2) to characterize the spray droplet formation. For this test series, diagnostic equipment such as the Malvern Spraytec, high-speed photometric cameras, pencil gauges, and thermocouples were used. Additionally, the effect of surface tension on the particle size distribution was evaluated with 1-liter of distilled water and with the same including the addition of 0.5% soap/water mixture. Results from this effort indicated that the plume formed from the instantaneous release in all conditions primarily included two distinct particle size distributions including 217-312µm and 0.53µm on average. Soapy water formed a higher concentration of smaller mist (0.53µm) than distilled water, potentially due to decreased surface tension with the added surfactant. Though results showed good correlation to certain particle size distributions it is encouraged to conduct additional tests like this with a wider range of liquids with different properties, which could affect the overall particle size distribution when released.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Laser aberration signatures in expelled electrons from a tenuous gas

We describe a mechanism by which the aberration content of a focused, multiterawatt laser is imprinted upon the forward angular distribution of electrons ionized within and ponderomotively expelled from the focal volume. In our experiments, the laser aberration type and magnitude are controllably varied, and the measured electron distributions are correspondingly modified in a way consistent with predictions from numerical simulations. This imprint mechanism shows potential for enabling the development of accurate focal-spot characterization of intense lasers when fired at full power and is being developed for extension to petawatt laser systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY