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At least 271 records · Page 15

Impact of confined geometries on hopping and trapping of motile bacteria in porous media

We use a random walk particle-tracking (RWPT) approach to elucidate the impact of porous media confinement and cell-cell interactions on bacterial transport. The model employs stochastic alternating motility states consisting of hopping movement and trapping reorientation. The stochastic motility patterns are defined based on direct visualization of individual trajectory data. We validate our model against experimental data, at single-cell resolution, of bacterial E. coli motion in three-dimensional confined porous media. Results show that the model is able to efficiently simulate the spreading dynamics of motile bacteria as it captures the impact of cell-cell interaction and pore confinement, which marks the transition to a late-time subdiffusive regime. Furthermore, the model is able to qualitatively reproduce the observed directional persistence. Lastly, our RWPT model constitutes a meshless simple method which is easy to implement and does not invoke ad hoc assumptions but represents the basis for a multiscale approach to the study of bacterial dispersal in porous systems.

54 ENVIRONMENTAL SCIENCES↗

Phase Space Reconstruction from Accelerator Beam Measurements Using Neural Networks and Differentiable Simulations

Characterizing the phase space distribution of particle beams in accelerators is a central part of accelerator understanding and performance optimization. However, conventional reconstruction-based techniques either use simplifying assumptions or require specialized diagnostics to infer high-dimensional (> $2D$) beam properties. In this Letter, we introduce a general-purpose algorithm that combines neural networks with differentiable particle tracking to efficiently reconstruct high-dimensional phase space distributions without using specialized beam diagnostics or beam manipulations. Furthermore, we demonstrate that our algorithm accurately reconstructs detailed 4D phase space distributions with corresponding confidence intervals in both simulation and experiment using a single focusing quadrupole and diagnostic screen. This technique allows for the measurement of multiple correlated phase spaces simultaneously, which will enable simplified 6D phase space distribution reconstructions in the future.

47 OTHER INSTRUMENTATION↗

Matrix Diffusion Controls Mountain Hillslope Groundwater Ages and Inferred Storage Dynamics

Groundwater age distributions provide fundamental insights on coupled water and biogeochemical processes in mountain watersheds. Field-based studies have found mixtures of young and old-aged groundwater in mountain catchments underlain by bedrock; yet, the processes that dictate these groundwater age distributions are poorly understood. In this work, we use the coupled ParFlow-CLM integrated hydrologic and EcoSLIM particle tracking models to simulate groundwater age distributions on a lower montane hillslope in the East River Watershed, Colorado (USA). We develop a convolution-based approach to propagate fracture-matrix diffusion processes to the EcoSLIM advection-dominated age distributions. We compare observed 3 H and 4 He concentrations from two groundwater wells against model predictions that have varying advective transport times and matrix diffusion magnitudes. Based on a Monte Carlo analysis that considers uncertain matrix and fracture parameters, we find that matrix diffusion is needed to jointly predict 3 H and 4 He observations at both wells. The advection-dominated age distributions lack adequate mixing of young and old-aged water to capture the observed co-occurrence of 3 H and 4 He. The model scenario that best matches the 3 H, 4 He, and water level observations when considering both advective flowpath and matrix diffusion mixing processes has a dynamic bedrock groundwater reservoir that is susceptible to considerable storage losses during low-snow periods. This dynamic groundwater system amplifies the need to assimilate deeper bedrock groundwater into watershed hydro-biogeochemical predictions. This work further highlights the importance of considering matrix diffusion when interpreting environmental tracers in bedrock groundwater systems.

54 ENVIRONMENTAL SCIENCES↗

Energy Exascale Computational Fluid Dynamics Simulations With the Spectral Element Method

Development and application of the open-source GPU-based fluid-thermal simulation code, NekRS, are described. Time advancement is based on an efficient kth-order accurate timesplit formulation coupled with scalable iterative solvers. Spatial discretization is based on the high-order spectral element method (SEM), which affords the use of fast, low-memory, matrix-free operator evaluation. Further, recent developments include support for nonconforming meshes using overset grids and for GPU-based Lagrangian particle tracking. Results of large-eddy simulations of atmospheric boundary layers for wind-energy applications as well as extensive nuclear energy applications are presented.

42 ENGINEERING↗

AIVT: Inference of turbulent thermal convection from measured 3D velocity data by physics-informed Kolmogorov-Arnold networks

We propose the artificial intelligence velocimetry-thermometry (AIVT) method to reconstruct a continuous and differentiable representation of the temperature and velocity in turbulent convection from measured three-dimensional (3D) velocity data. AIVT is based on physics-informed Kolmogorov-Arnold networks and trained by optimizing a loss function that minimizes residuals of the velocity data, boundary conditions, and governing equations. We apply AIVT to a set of simultaneously measured 3D temperature and velocity data of Rayleigh-Bénard convection, obtained by combining particle image thermometry and Lagrangian particle tracking. This enables us to directly compare machine learning results to true volumetric, simultaneous temperature and velocity measurements. We demonstrate that AIVT can reconstruct and infer continuous, instantaneous velocity and temperature fields and their gradients from sparse experimental data at a high resolution, providing an additional approach for understanding thermal turbulence.

Science & Technology - Other Topics↗

Kinematics reconstruction in solenoidal spectrometers operated in active target mode

Here, we discuss the reconstruction of low-energy nuclear reaction kinematics from charged-particle tracks in solenoidal spectrometers working in Active Target Time Projection Chamber mode. In this operation mode, reaction products are tracked within the active gas medium of the Active Target with a three dimensional space point cloud. We have inferred the reaction kinematics from the point cloud using an algorithm based on a linear quadratic estimator (Kalman filter). The performance of this algorithm has been evaluated using experimental data from nuclear reactions measured with the Active Target Time Projection Chamber (AT-TPC) detector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Data From: "Warming and snow loss increase reliance on old groundwater in a Colorado River headwater"

This repository contains the data and code associated with the paper titled "Warming and snow loss increase reliance on old groundwater in a Colorado River headwater," published in Nature Geoscience, 2026. This study seeks to answer how various ages of groundwater interact with mountainous streamflow in mountainous headwaters such as the East River. It includes various model-data processing scripts, primarily for ParFlow-CLM analysis of simulated water years 2015-2021, and two numerical warming experiments (+2.5 and +4.0 degrees C), including run scripts, forcing scripts, and post-processing, as well as comparison to observation datasets, detailed below. This data requires the use of R (.r, .rmd), Python (.py), Jupyter Notebook or Jupyter Lab (.ipynb), ParFLOW-CLM, EcoSLIM. Further information on the use of all file formats mentioned below (e.g. .tff. .nc) are provided within the associated scripts and directory where the files are located. Contents & Usage ASO/: ​​Contains the bash and python scripts used to convert airborne snow observatory (ASO) data (ASO, 2023) in various data formats (georeferenced tiff file, NetCDF, UTM, and to latitude/longitude) then regrided to the ParFlow equivalent grid. Output data are in regrid_regll_data.zip and subsequently visualized and analyzed in plot_and_compare.py for Supplementary Figures A14 and A15. The wksht_ASO_comparison.xlsx spreadsheet is used to calculate the data for Supplementary Figure A16. EcoSLIM/: Contains the scripts and input files to run the EcoSLIM particle tracking simulations (/run_scripts) and the post-processing python script (/plot_scripts/eco_agedist_plots.ipynb). Jasechko et al./: Contains the jupyter notebook (Extract_Elevation.ipynb) to determine the outlet elevations of the 260 watersheds used in Jasechko et al. (2016), and the corresponding table, Table_S1_Watersheds_alt.csv. Used to create Supplementary Information Figure A2. PLM_Wells/: Contains the QA/QC-ed groundwater level time series of the PLM-1 and PLM-6 Monitoring Wells from Faybishenko et al. (2023), reformatted to water years used for Supplementary Figures A19 and and A20. ParFlow/: Contains the input files and run scripts to run ParFlow-CLM (/run_scripts), the python and tool command language (Tcl) scripts to create and distribute the ParFlow forcing simulation files (/forcing), and various scripts and intermediary files to analyze the model outputs (/post_process). SQUIRE/: Contains the processing scripts and intermediary files for the Surface QUantitatIve pRecipitation Estimation (SQUIRE) data (Grover, 2023) used to generate Supplementary Figure A18. USGS_Streamflow/: Contains the raw and gap-filled United States Geological Survey streamflow data (U.S. Geological Survey, 2026) used at the Almont station (site number 09112500). Gap-filling is performed in the R script with data from the Taylor station (site number 09110000). (/USGS_09112500_EAST_RIVER_AT_ALMONT_GAP_FILLED/code_almont_streamflow_gap_fill.Rmd). discharge/: Contains the gap-filled discharge data at the Watershed Function SFA East River pumphouse site (Newcomer et al., 2022) used to generate Supplementary Figure A13 and to compute hourly Nash-Sutcliffe model efficiency coefficients (NSE) in Table A4. snotel_and_flux_tower/: Contains the snow telemetry data (U.S. Department of Agriculture, 2024) from the Butte (site ID 380) and Schofield (site ID 737) stations, reformatted by water year, accessed with the snotelr R package. Used to create Supplementary Figure A17. Also contains the flux tower observational data (FluxTower_Pumphouse_ESS-DIVE.ET_only.h.txt) from Ryken et al. (2022) and sap flux transpiration data (MaxB_Transpiration_5Sites.daily_sums.h.txt) from Ryken (2021), used to create Supplementary Figures A22 and A23, respectively. Raw EcoSLIM model outputs are in excess of 24TB, and are stored on National Energy Research Scientific Computing Center (NERSC) and publicly available via the external link provided in the paper.

atmospheric warming↗

Dynamic Aperture Evaluation for the Hadron Storage Ring in the Electron-Ion Collider

The Electron-Ion Collider (EIC) is aiming at a design luminosity of 1e34 cm⁻²s⁻¹. To maintain such a high luminosity, both beams in the EIC need an acceptable beam lifetime in the presence of the beam-beam interaction. For this purpose, we carried out weak-strong element-by-element particle tracking to evaluate the long-term dynamic aperture for the hadron ring lattice design. We improved our simulation code SimTrack to treat some new lattice design features, such as radially offset on-momentum orbits, coordinate transformations in the interaction region, etc. In this article, we will present the preliminary dynamic aperture calculation results with β^{*}- function scan, radial orbit shift, crossing angle collision, and magnetic field errors.

Luo, Y.↗

FFA@CEBAF beam transport error and tolerance simulation studies

The Continuous Electron Beam Accelerator Facility (CEBAF) is a 12 GeV recirculating electron accelerator at the Thomas Jefferson National Accelerator Facility (JLAB). Major upgrades to the accelerator are being investigated which include a new 650 MeV injection beamline and state-of-the-art fixed-field alternating (FFA) gradient recirculation arcs. The upgrade will extend the energy of the electron beam to over 20 GeV. In this paper, we provide an error and tolerance simulation study of the amended beam optics transport of the existing accelerator tuned for 22 GeV operation. The study is conducted with the particle tracking codes elegant and Bmad in two parts. In the first part, we treat each section of the accelerator (electromagnetic arcs and linacs) modularly with ideal conditions at the beginning. The second part is a pseudo start-to-end (S2E) simulation with accumulated errors propagating from one beamline to the next.

Accelerator Physics↗

Beam Performance of the Positron Transport Line for CEBAF Positron Upgrade

The Low Energy Recirculator Facility (LERF) at Jefferson Lab, formerly operated for the Free-Electron Laser program, has been proposed as the injector complex for the planned 12 GeV CEBAF positron upgrade (Ce+BAF), with an additional pathway to support a potential 22 GeV CEBAF electron upgrade. In this configuration, LERF would generate and pre-accelerate positrons to 123 MeV, matching the present injection energy into the North Linac. Due to the relatively large emittance expected from the positron source, a comprehensive acceptance study has been performed from LERF through the CEBAF recirculating linacs and beam transport lines to the experimental halls. The objective is to establish the positron phase-space acceptance and provide design feedback to the positron production and capture systems. Furthermore, given CEBAF’s capability to deliver highly polarized beams, spin-tracking simulations have been carried out including magnet imperfections, alignment errors, and synchrotron-radiation–induced energy spread. Particular attention is given to the evolution of the spin tune and the corresponding depolarization mechanisms along the beam delivery path, especially for providing longitudinal polarization at the experimental halls. These results inform injector design choices and assess the overall feasibility of delivering high-polarization positron beams in CEBAF.

Ogur, S. [Thomas Jefferson National Accelerator Fa↗

Transport of 12 GeV positron beams at Ce+BAF

Jefferson Lab (JLab) is developing a concept to upgrade the Continuous Electron Beam Accelerator Facility (CEBAF) to additionally deliver spin-polarized continuous-wave positron beams for its nuclear physics program users (Ce+BAF 12 GeV). The concept involves repurposing the Low Energy Recirculator Facility (LERF) at JLab as a dual injector, first producing 100-300 MeV spin-polarized electron beams which are subsequently used for the generation and formation of 123 MeV continuous-wave positron beams. The positron beams are transported to CEBAF and injected for acceleration up to 12 GeV, tailored to the requirements of its four experimental halls. Given the higher emittance of the secondary positron beams, the CEBAF optics are optimized for low dispersion and low beta functions to enhance transmission within the Ce+BAF acceptance limits and with an R56 to manage the positron beams bunch length and energy spread. Potential bottlenecks are being investigated through both optical modeling and measurements using an electron beam, as well as degraded electron beams, to map the 6d acceptance of CEBAF as it is today. This presentation shares preliminary results from multi-particle tracking simulations of the positron beam up to 12 GeV, including spatial, momentum, and spin characteristics, and explores the feasibility of delivering beams simultaneously to multiple experimental halls via extraction optics.

Accelerator Physics↗

ParFlow Sand Tank: A tool for groundwater exploration

The ParFlow Sand Tank model is an open source application designed to allow users to interactively simulate and visualize groundwater movement through the subsurface. The app is designed for both research and education; teaching hydrogeology concepts and making it easy explore and run sophisticated groundwater simulations. Our goal is to support increased accessibility and usability of research grade hydrology tools for research and teaching. The Sand Tank application simulates groundwater and surface water fluxes as well as contaminant transport in real time using the integrated physical hydrology model ParFlow (Kollet & Maxwell, 2006; Maxwell & Miller, 2005; Osei-Kuffuor et al., 2014) and the particle tracking code EcoSlim (Maxwell et al., 2019). ParFlow is a numerical hydrology model that simulates spatially distributed groundwater and surface water flow. It is a well established research tool with more than 90 publications documenting its development use to advance our understanding of groundwater dynamics and groundwater surface water interactions from the hillslope to the continental scale e.g. (Condon et al., 2020; Condon & Maxwell, 2019; Maxwell & Condon, 2016). It is designed for efficient parallel computation and has been run on many platforms spanning from laptops to supercomputers. However, one of the challenges of ParFlow is that it requires significant training and hydrologic expertise to develop simulations. The Sand Tank application makes this model accessible to anyone for education and exploration. Our application uses ParFlow for its simulation backend and ParaView for the data loading and processing. The communication infrastructure relies on the ParaViewWeb framework. We use model templates deployed in Docker images to setup the Sand Tank framework. Users can build the application locally or interact with it through our web deployment. When interacting with a template users can interactively change model parameters like subsurface processes or pump/inject water into the subsurface and watch the system respond to their changes in real time as the simulation runs. Additionally, our template setup will allow more advanced users to build custom templates of increasing complexity for both research and educational purposes.

54 ENVIRONMENTAL SCIENCES↗

Fast Dynamic Aperture Optimization with Reversal Integration

A fast method for dynamic aperture (DA) optimization of storage rings has been developed through the use of reversal integration. Even if dynamical systems have an exact reversal symme- try, a numerical forward integration di ers from its reversal. For chaotic trajectories, cumulative round-o errors are scaled, which results in an exponential growth in the di erence. The exponential e ect, intrinsically associated with the Lyapunov exponent, is a generic indicator of chaos because it represents the sensitivity of chaotic motion to an initial condition. A chaos indicator of the charged particle motion is then obtained by comparing the forward integrations of particle trajectories with corresponding reversals, a.k.a. \backward integrations." The indicator was con rmed to be ob- servable through short-term particle tracking simulations. Therefore, adopting it as an objective function could speed up optimization. The DA of the National Synchrotron Light Source II storage ring, and another test di raction-limited light source ring, were optimized using this method for the purpose of demonstration.

36 MATERIALS SCIENCE↗

Preliminary Deposition Modeling: For Determining the Deposition of Corrosive Contaminants on SNF Canisters

This report fulfills the M3 milestone M3SF-20PN010207045. During fiscal year (FY) 2019, Pacific Northwest National Laboratory (PNNL) worked to develop initial deposition and particle tracking models which could be used to better understand how corrosive contaminants deposit on the surfaces of spent nuclear fuel (SNF) canisters during dry storage. These models may be useful in understanding the likelihood of chloride induced stress corrosion cracking (CISCC) on SNF canisters

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Multi-variable, Multi-value Hydrodynamic Modeling Approach to Support Marine Energy and Coastal Resilience Applications

Funded by the Marine Energy Seedling Laboratory Program, the study reported on here aimed to develop a multi-variable, multi-value hydrodynamic modeling approach based on the Finite-Volume Community Ocean Model (FVCOM) to support a wide range of marine renewable energy and coastal resilience applications. We migrated the marine hydrokinetic energy module to simulate tidal energy extraction by tidal turbines under wave-current interactions. We explored the particle tracking module in FVCOM and applied it to Sequim Bay, Washington, to illustrate the surface current field and mimic the pollutant transport near the surface. A tracer-water age module was added to FVCOM to examine water exchange through the entrance. Lastly, a user-specified vertical coordinate option was added to FVCOM to improve simulation of the effect of floating turbines on surface currents and scalar transport. The above-described model development has been tested using a simplified model domain and demonstrated in real-world coastal systems. The outcome of this project will provide a useful modeling code and approach for marine renewable energy and coastal resilience research and applications.

16 TIDAL AND WAVE POWER↗

Introduction to an MCGIDI Mini-App and Performance Comparisons with XSBench

In high-performance Monte Carlo (MC) radiation transport codes, cross section lookups often account for the majority of computational expens. In response to this observation, a number of nuclear data mini-apps have been developed to profile and optimize the lookup process. A review of these mini-apps can be found in Ref. In contrast to a fully fledged MC code, nuclear data mini-apps do not feature particle tracking; instead, the cross section lookup process is considered in isolation, a simplification that allows for easier implementation and evaluation of various lookup schemes and techniques. GIDI+, as described on its public repository1, is ...a collection of C++ libraries for accessing evaluated and processed nuclear data stored in the Generalized Nuclear Database Structure (GNDS). In addition to reading GNDS files, GIDI+ has functions to sum and collapse multi-group data as needed by deterministic transport codes, and to sample GNDS data as needed by Monte Carlo transport codes. Certain modes of Mercury, a LLNL-developed MC radiation transport code, utilize GIDI+ for cross section lookups. Specifically, Mercury uses the MCGIDI library contained within GIDI+ to perform lookups on GPUs. A mini-app exercising MCGIDI’s cross section lookup capabilities would prove useful for optimization, which in turn could improve the performance of client codes such as Mercury. Such a mini-app could also be used to assess the performance of MCGIDI compared to other nuclear data mini-apps. In this document, we introduce a nuclear data mini-app built with the MCGIDI library. The MCGIDI mini-app (MCGIDI-MA) was developed to closely resemble the methodology present in XSBench, a nuclear data mini-app developed at Argonne National Laboratory. The remainder of this section provides an overview on XSBench. Section 2 describes MCGIDI-MA and its usage. Section 3 contains performance results of MCGIDI-MA on LLNL’s Lassen and Quartz compute platforms, as well as comparisons to XSBench performance where appropriate. In Section 4, we present a summary of our findings.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

EMITTANCE GROWTH DUE TO RF PHASE NOISE IN CRAB CAVITIES

The Electron-Ion Collider (EIC) incorporates beam crabbing to recover geometric luminosity loss from the nonzero crossing angle at the interaction point (IP). It is well-known that crab cavity imperfections can cause growth of colliding beam emittances, thus degrading collider performance. Here we report a particle tracking study to quantify these effects. Presently the study is focused on crab cavity RF phase noise. Simulations were carried out using Bmad. Dependence of emittance growth on phase noise level was obtained which could be used for developing crab cavity phase control specifications. We also benchmarked these simulations with theory.

Huang, H.↗

Fission TPC cross section ratio results [Abstract]

The fission TPC was designed for precision fission cross section ratio measurements. The high-fidelity 3D particle tracking data is used to conduct a detailed analysis of the uncertainty contributions. In this contribution a brief overview of the instrument was presented. The results of the 238 U(n,f)/ 235 U(n,f) cross section ratio measurement published in [Phys. Rev C 97, 034618 (2018)] were reviewed and the preliminary status of the 239 Pu(n,f)/ 235 U(n,f) cross section ratio measurement was shown.

238U(n,f)/235U(n,f) cross section ratio↗