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DOE OSTI2023

A sharp interface Lagrangian-Eulerian method for flexible-body fluid-structure interaction

This paper introduces a sharp-interface approach to simulating fluid-structure interaction (FSI) involving flexible bodies described by general nonlinear material models and across a broad range of mass density ratios. This new flexible-body immersed Lagrangian-Eulerian (ILE) scheme extends our prior work on integrating partitioned and immersed approaches to rigid-body FSI. Our numerical approach incorporates the geometrical and domain solution flexibility of the immersed boundary (IB) method with an accuracy comparable to body-fitted approaches that sharply resolve flows and stresses up to the fluid-structure interface. Unlike many IB methods, our ILE formulation uses distinct momentum equations for the fluid and solid subregions with a Dirichlet-Neumann coupling strategy that connects fluid and solid subproblems through simple interface conditions. As in earlier work, we use approximate Lagrange multiplier forces to treat the kinematic interface conditions along the fluid-structure interface. This penalty approach simplifies the linear solvers needed by our formulation by introducing two representations of the fluid-structure interface, one that moves with the fluid and another that moves with the structure, that are connected by stiff springs. This approach also enables the use of multi-rate time stepping, which allows us to use different time step sizes for the fluid and structure subproblems. Our fluid solver relies on an immersed interface method (IIM) for discrete surfaces to impose stress jump conditions along complex interfaces while enabling the use of fast structured-grid solvers for the incompressible Navier-Stokes equations. The dynamics of the volumetric structural mesh are determined using a standard finite element approach to large-deformation nonlinear elasticity via a nearly incompressible solid mechanics formulation. This formulation also readily accommodates compressible structures with a constant total volume, and it can handle fully compressible solid structures for cases in which at least part of the solid boundary does not contact the incompressible fluid. Selected grid convergence studies demonstrate second-order convergence in volume conservation and in the pointwise discrepancies between corresponding positions of the two interface representations as well as between first and second-order convergence in the structural displacements. The time stepping scheme is also demonstrated to yield second-order convergence. To assess and validate the robustness and accuracy of the new algorithm, comparisons are made with computational and experimental FSI benchmarks. Test cases include both smooth and sharp geometries in various flow conditions. Furthermore, we also demonstrate the capabilities of this methodology by applying it to model the transport and capture of a geometrically realistic, deformable blood clot in an inferior vena cava filter.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Progress towards the FRIB-EDM 3 -Frontend: A tool to provide radioactive molecules from isotope harvesting for fundamental symmetry studies

The under-construction FRIB-EDM 3 -instrument was designed to study polar radioactive molecules (such as RaF) in transparent cryogenic solids by laser spectroscopy. The instrument is divided into a frontend- and a backend section. The frontend accepts an aqueous sample from isotope harvesting and provides a mass-separated molecular ion beam in an ultra-high vacuum environment. In the backend, the ions are guided into alkali-metal vapor and the resulting neutrals are co-deposited in a solid argon matrix to perform laser spectroscopy. Here, this work addresses the frontend of the instrument. The efficient ionization of harvested radioisotopes from aqueous samples is achieved with a spray-ionization method. Subsequently, the molecular ion beam is analyzed by mass-to-charge ratio by a quadrupole mass filter. To verify the feasibility of the approach, numerical simulations with the COMSOL and SIMION packages have been conducted. While the former was applied to study transport in ion funnels, the latter was used to investigate ion beam transmission through the lower pressure sections. Following promising simulation results, a first experimental setup is under construction.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Monte Carlo toolkit for designing and validating step-range-filter spectrometer designs

Here, we present a Monte Carlo toolkit for validating step range filter (SRF) spectrometer designs. Geant4 is used to transport charged particles through the SRF filters to generate synthetic SRF data that include realistic CR-39 effects. Synthetic SRF spectra generated by this method inherently account for instrument response and allow for the quantification of SRF performance before shots. The usefulness of this toolkit is demonstrated through its application to a number of problems. A new broadband SRF for the ∼10 MeV wide 3He3He proton spectrum is validated, and an analysis method for analyzing 3He3He-p SRF data that accounts for instrument response is put forth. In addition, an SRF design for the compact recoil-proton spectrometer (CRS) on the Z-machine is validated. Finally, a new calibration technique for the DD-p SRF is proposed and validated.

Johnson, T. M. (ORCID:0000000193032949)↗

DOE OSTI2026

Design and fabrication of ion traps for low RF power dissipation

Large surface-electrode ion traps with multiple trapping regions and junctions are a natural approach to scaling trapped ion quantum computers, supporting the connectivity and ion counts necessary for complex quantum algorithms. However, a major hurdle in this scaling is on-chip power dissipation from the applied RF voltage, which increases at a rate between linear and cubic relative to trap size, depending on whether the losses are dielectric or Ohmic. Here, we present two versions of a trap with features designed to reduce both types of RF power dissipation. The first variant contains a raised RF electrode that increases the electrode–ground distance to reduce capacitance. Different DC voltage sources are demonstrated on this trap to show that technical noise before the filter remains the dominant source of voltage noise and therefore motional heating. The second variant additionally includes a method for removing dielectric from beneath the RF electrode to further reduce dielectric losses. These traps were demonstrated at room temperature with 40 Ca + ions. In conclusion, the similar heating rates and heating rate axial frequency dependencies between 2.4 and 3.0 MHz illustrate that this dielectric modification is not detrimental to trap performance.

Sterk, J. D. [Sandia National Laboratories (SNL-NM↗

DOE OSTI2025

Single-shot spatiotemporal plasma density measurements with a chirped probe pulse

In this work, we present the development and demonstration of a diagnostic for the measurement of the spatial and temporal evolution of plasma density in a single shot. Single-shot Advanced Plasma Probe HolographIc REconstruction (SAPPHIRE) utilizes a chirped probe pulse, a diffractive optical element, a self-referenced interferometer, and an interference bandpass filter to achieve high-fidelity electron density measurements suitable for underdense plasmas that exhibit cylindrical symmetry. The method overcomes limitations in conventional diagnostics, such as reliance on shot-to-shot reproducibility, while capturing plasma dynamics on picosecond timescales with micron-level spatial resolution. The capabilities of SAPPHIRE are demonstrated through measurements of laser-driven plasma channels in helium–nitrogen gas jets. SAPPHIRE demonstrates the formation and expansion of plasma channels in a single shot and the propagation of supersonic ionization fronts while revealing shot-to-shot variations in the plasma profiles. Experimental results are validated against theoretical models and scaling laws, underscoring the robustness and accuracy of this technique. By enabling ultrafast, high-resolution plasma diagnostics in a single exposure, SAPPHIRE represents a transformative advancement in plasma measurement technology.

Grace, Elizabeth S. [Lawrence Livermore National L↗

DOE OSTI2024

Progress Toward Gamma-Ray Imaging for Automated Holdup Measurement in Gloveboxes

Shielded gloveboxes are currently being constructed to facilitate dilution and disposal of many tons of excess plutonium oxide. Measuring holdup in these gloveboxes is expected to be challenging because of the limited available lines of sight through the glovebox shielding. A system of gamma-ray imagers is being developed to provide localization and quantification for holdup. The system will be mounted above the glovebox, where there is minimal shielding. Multiple imagers with overlapping coded-aperture fields of view are employed to enable three-dimensional reconstruction. Compton reconstruction is also available to localize sources outside the coded-aperture field of view. Improved uncertainties with respect to current techniques are expected by virtue of the fixed installation, spectroscopic performance of the detectors, and iterative image reconstruction techniques. Measurement campaigns have been undertaken at an active glovebox at Savannah River Site to test the gamma-ray imaging system in an operational environment, providing a simple test of a single imager that mimics the geometry of the installation proposed for future shielded gloveboxes. Data taken during quiescent periods in the glovebox were used to measure the buildup of material on an outlet filter and record a trend over time. Calibration data was taken with known sources to simplify analysis and provide a reliable assay of the filter. Resulting images make it possible to isolate the filter from other sources and recognize compromised data. This paper will present details of the measurement and analysis methods.

Schmitt, Kyle↗

DOE OSTI2020

Microbial macroecology: In search of mechanisms governing microbial biogeographic patterns

Abstract Introduction Rapidly advancing technologies and accumulating information about microbial communities across the globe allow the quantification of microbial properties and functions at a macro‐scale. These emerging microbial biogeographic patterns call for a practical macroecological approach to investigate their underlying mechanisms. Aims The primary aims of this paper are to review the advancements of microbial macroecology in seeking mechanisms governing microbial biogeographic patterns, and to further lay out a roadmap for microbial macroecology in 10 years. Methods We reviewed the progress of microbial macroecology and demonstrated the application of the microbial macroecological approach to microbial biogeographic patterns with three case studies. Results Microbial macroecology provides a platform for understanding microbial abundance, community structure, and functioning across space, time, and taxonomic hierarchy. It emphasizes the integral effects of environmental filtering, microbial responses, diversification, dispersal, and local extinction that drive the microbial biogeographic patterns. The microbial macroecological approach emphasizes the last two stages of the four‐stage scientific method applied to microbial ecology: (a) describing microbial traits across scales to reveal patterns, (b) mathematically representing these patterns, (c) developing and testing conceptual models to build a mechanistic understanding of these patterns from a macroecological perspective, (d) plugging the new knowledge into the theoretical advancements. Three case studies were used to demonstrate the microbial macroecological approach for understanding the global patterns of microbial biomass carbon, microbial composition (fungi : bacteria ratio), and microbial carbon use efficiency. Conclusions Microbial macroecology offers a platform for understanding the mechanisms that drive biogeographic patterns of microbial abundance, diversity and functions. It is likely that these patterns and mechanisms will be increasingly incorporated into predictive models that link climate, carbon dynamics, and biogeochemical processes. A roadmap is outlined for the growing microbial macroecology field; we expect significant progress will be made in five research directions over the next 10 years.

Xu, Xiaofeng↗

DOE OSTI2020

Transient Safety Filter Design for Grid-Forming Inverters

Unlike conventional generators, inverter-based generation are fundamentally incapable of providing rotational inertia. While grid-forming inverters alleviate some of that problem by synthesizing small inertia via feedback control, additional control mechanisms are needed to ensure safety and security during transients. In this paper, we propose novel real-time safety-constrained feedback controllers (``safety filters'') for droop-based (grid-forming) inverters to ensure transient security of the grid. The safety filter acts as a buffer between the network operational layer and the inverter-control layer, and only lets those dispatch control signals pass to the inverter droop-controller, which are guaranteed to not violate the safety specifications (frequency, voltage, current limits). Using a distributed barrier certificates method, we construct sector-like conditions on the control policies, which guarantee the satisfaction of transient safety specifications. Sum-of-square programming is used to synthesize the safety filters. Numerical simulation results are provided to illustrate the performance of the proposed filter on inverter-based microgrids.

Kundu, Soumya↗

DOE OSTI2025

Angular-spectral filtering of recoil protons for optimization of fast neutron imaging employing proton converters

Fast neutron imaging is an important capability for diverse applications such as inertial confinement fusion diagnostics, cargo security, nuclear nonproliferation and arms control, and industrial inspection. Traditional phosphor image plates can be enhanced for fast neutron imaging using hydrogenous plastic converters which allow fast neutrons to scatter off hydrogen nuclei to produce energetic protons that can be recorded by the image plate. However, protons emitted by image plates are not constrained in their emission angle, which contributes to the blur of the resulting image. Here, we investigate two methods that can alter the spatial extent of converted protons that deposit energy in the image plate: reducing the converter thickness, and introducing a proton filter between the plastic converter and image plate to reduce the contribution of lower-energy, off-axis protons to the image. Here we determine the optimal plastic converter thickness for maximizing the signal intensity to be 2–3 mm through Monte Carlo simulations, and we benchmark this result against experimental measurements with a deuterium-tritium (DT) neutron generator. Next, we evaluate the image smearing and signal loss for various converters to show that solely reducing the converter thickness has the expected effect of reducing the blur from proton image smearing of the sharpness of an edge recorded on the image plate at the cost of reducing the signal intensity. The use of a proton filter is shown to achieve a similar improvement of edge sharpness as reducing the converter thickness while also sacrificing the signal intensity. We conclude that the use of proton energy filtering can improve the sharpness of fast neutron images in situations where the converter thickness cannot be reduced below some practical minimum. For more intense neutron sources, the signal intensity is of less concern, and optimizing the resolution of the image plate and therefore of the imaging system could have greater value. In these applications, proton filters may allow for improved fast neutron imaging measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Low Energy Neutron-induced Charged-particle (Z) (LENZ) instrument development with a focus on pulse shape discrimination for low-energy charged particles

To study neutron-induced charged-particle reactions with high precision, the Low Energy Neutron-induced Charged-particle (Z) instrument (LENZ) was developed at the Los Alamos Neutron Science Center. For the interest of measuring (n,p) and (n, α) reactions simultaneously, Pulse Shape Discrimination methods were investigated to identify different charged particles in the energy range of 3 - 20 MeV and improve signal-to-background ratios using Double-sided Silicon Strip Detectors and waveform digitizers. The risetime and pulse shape properties of detected charged particles were characterized for various silicon detector’s thickness with different orientations. During the post-processing of waveforms, we implemented different digital filters for effective particle identifications and improved energy- and timing- resolutions. We validated the optimized digital filters and pulse shape analyses, via measurements with 228 Th and 229 Th calibration sources, proton-induced reactions on a 7 LiF target, and neutron-induced reactions on CH 2 , Ta 2 O 5 , 58 Ni, and 6 LiF/ 59 Ni targets at the time-of-flight facility, LANSCE. In conclusion, the summary of effective thresholds and Figure of Merits on separating different charged particles is reported.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

The ZTF Source Classification Project. I. Methods and Infrastructure

The Zwicky Transient Facility (ZTF) has been observing the entire northern sky since the start of 2018 down to a magnitude of 20.5 (5σ for 30 s exposure) in the g, r, and i filters. Over the course of two years, ZTF has obtained light curves of more than a billion sources, each with 50–1000 epochs per light curve in g and r, and fewer in i. To be able to use the information contained in the light curves of variable sources for new scientific discoveries, an efficient and flexible framework is needed to classify them. In this paper, we introduce the methods and infrastructure that will be used to classify all ZTF light curves. Our approach aims to be flexible and modular and allows the use of a dynamical classification scheme and labels, continuously evolving training sets, and the use of different machine-learning classifier types and architectures. Finally with this setup, we are able to continuously update and improve the classification of ZTF light curves as new data become available, training samples are updated, and new classes need to be incorporated.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

AlphaBuilding ResCommunity: A multi-agent virtual testbed for community-level load coordination

Training and validating algorithms in a simulation testbed can accelerate research and applications of optimal control of residential loads to improve energy flexibility and grid resilience. We developed an open-source simulation environment, AlphaBuilding ResCommunity, that can be used to train and validate algorithms to control a single thermostatically controlled load (TCL) or coordinate a group of TCLs. We used reduced-order models to simulate the thermodynamics of TCLs, and the parameter values were determined from the connected smart thermostat data of real households. The environment was built upon the standardized OpenAI Gym interface. Ancillary functions, such as retrieving the parameters and weather forecasts, are provided to facilitate control strategies that require predictive information. Compared with existing efforts, AlphaBuilding ResCommunity has three advantages: (1) more realistic model settings because the parameter values are identified from actual household operating data, and modelling and measurement uncertainty are considered; (2) passive thermal storage control; and (3) ease of use due to a simple software dependency and standardized interface. We demonstrated the applications of the environment by implementing a Kalman Filter and Model Predictive Control on a single TCL and a Priority-Stack-Based Control and Alternating Direction Method of Multipliers to coordinate multiple TCLs for load tracking.

Wang, Z↗

DOE OSTI2021

DART-PFLOTRAN: An ensemble-based data assimilation system for estimating subsurface flow and transport model parameters

Ensemble-based Data Assimilation (EDA), based on the Monte Carlo approach, has been effectively applied to estimate model parameters through inverse modeling in subsurface flow and transport problems. However, implementation of EDA approach involves a complicated workflow that include setting up and executing ensemble forward model simulations, processing observations and model simulation results for parameter updates, and repeat for sequential or iterative EDA. To facilitate the management of such workflow and lower the barriers for adopting EDA-based parameter estimation in subsurface science, we develop a generic software frame-work linking the Data Assimilation Research Testbed (DART) with a massively parallel subsurface FLOw and TRANsport code PFLOTRAN. The new DART-PFLOTRAN leverages both the core data assimilation engines in DART and the computational power afforded by PFLOTRAN. In addition to the standard smoother and filtering options, DART-PFLOTRAN enables an iterative EDA workflow based on the Ensemble Smoother for Multiple Data Assimilation method (ES-MDA) to improve estimation accuracy for nonlinear forward problems. Here, we verify the implementation of ES-MDA in DART-PFLOTRAN using two synthetic cases designed to estimate static permeability and dynamic exchange fluxes across the riverbed, respectively, from continuous temperature measurements made across a depth profile. One-dimensional hydro-thermal simulations are performed in both cases to relate temperature responses with the parameters of interest. In the case of estimating dynamic parameters, we demonstrate the flexibility of DART-PFLOTRAN in automating sequential ES-MDA workflow, which will significantly reduce the time researchers spend on managing complex workflows in similar applications. Both studies yield accurate estimations of the parameters compared to their synthetic truth, while ES-MDA leads to more accurate estimation when a high level of nonlinearity exist between observed responses and unknown parameters. With a code base in Python and Fortran, DART-PFLOTRAN paves the way for applications in large-scale subsurface inverse modeling by automating the complex workflow of sequential ES-MDA that can be executed on various computing platforms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Seeing through nuclear fuel: Three-dimensional, nondestructive X-ray microscopy and volumetric analyses of neutron-irradiated TRISO-coated fuel kernels

The three-dimensional (3D) characterization of nuclear fuel with X-ray microscopy has historically proven difficult, due to uranium’s high attenuation of easily accessible X-rays, both in a laboratory setting and at a synchrotron user facility. However, this imaging modality provides nondestructive information that can be used to investigate morphological changes arising from external stimuli (e.g., neutron irradiation, high-temperature testing). Using an appropriate X-ray energy spectrum and an adequate X-ray filter, suitable transmissions through properly sized nuclear fuel specimens can be achieved. Here, in this study, we present the methods and results of using a commercially available, laboratory-based X-ray microscope (XRM) to examine the extent of 3D morphological changes of tristructural isotropic (TRISO)-coated fuel particles, specifically uranium oxide/uranium carbide fuel kernels, after high-temperature neutron irradiation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Analysis of ISOCS Measurements to Establish Methodology Uncertainty

Qualification measurements were performed at the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) on a variety of measurement standards. These measurements will be used to qualify the In-Situ Object Counting System (ISOCS) measurement method with a high-purity germanium (HPGe) detector for use at ORNL. Measured items include uranium isotopic standards, filter papers coated with uranium oxide (U 3 O 8 ), U 3 O 8 line sources, and a uranium tetrafluoride (UF 4 ) source. The 235 U mass was estimated using the ISOCS calibration software for each source and compared with the declared isotope mass value.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Machine Learning-driven Molecular Design for Therapeutic Discovery

The ongoing novel coronavirus pandemic (COVID-19) has highlighted the need for new therapeutics to counter the threat of emerging viral pathogens. The main proteases are a promising target for developing antiviral inhibitors. In this work, we utilized a novel combination of artificial intelligence-driven iterative design of covalent inhibitor candidates, physics-based computational modeling of protein-inhibitor interactions, and “All in One” Native MS biophysical assay screening and characterization of therapeutic candidates. With our existing expertise in hit generation using a particular scaffold as a starting point, we first generated tens of thousands of compounds that preserve the key scaffold. In order to optimize the candidates, we calculated about 136 descriptors consisting of 2D and 3D features for molecules targeting the SARS-CoV-2 Main protease (Mpro). These compounds were initially filtered according to properties and further sorted by predicted binding affinity using our automated docking modeling and machine learning methods. We tested a handful of candidates and identified two as inhibitors of Mpro with micromolar affinities.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Applying Time-Parallelization to Turbulent Flows

Parallelization of the temporal domain is explored for the solution of turbulent flows. Multigrid reduction-in-time (MGRIT) is used to advance the large-scale fluid dynamics in time sequentially on the coarsest space-time grid but propagate the information in time parallel on all other levels. The goal of this process is to accurately and efficiently resolve the coarse-scale turbulence structure and use that to drive the fine-scales of the turbulent flow. The extra forcing from nonlinear multigrid facilitates the coupling and interaction between fine and coarse scales, through which the multiscale nonlinear physics is properly captured. Adaptive mesh refinement is employed to finely resolve only the regions with strong gradients, which provides further computational efficiency. The underlying computational fluid dynamics solver is a fourth-order finite-volume scheme with the standard 4-stage Runge-Kutta method. An advanced approach is devised and implemented to enable MGRIT to solve highly turbulent flows successfully. Furthermore, the method is applied to solve a Taylor-Green vortex problem and a doubleshear-layer turbulent mixing flow. Results are promising, validating that MGRIT with the filtering approach has the potential to efficiently solve general turbulent flows.

Computational Fluid Dynamics↗

DOE OSTI2025

A dynamic likelihood approach to filtering transport processes: advection-diffusion dynamics

A Bayesian data assimilation scheme is formulated for advection-dominated advective and diffusive evolutionary problems, based upon the Dynamic Likelihood (DLF) approach to filtering. The DLF was developed specifically for hyperbolic problems –waves–, and in this paper, it is extended via a split step formulation, to handle advection-diffusion problems. In the dynamic likelihood approach, observations and their statistics are used to propagate probabilities along characteristics, evolving the likelihood in time. The estimate posterior thus inherits phase information. For advection-diffusion the advective part of the time evolution is handled on the basis of observations alone, while the diffusive part is informed through the model as well as observations. We expect, and indeed show here, that in advection-dominated problems, the DLF approach produces better estimates than other assimilation approaches, particularly when the observations are sparse and have low uncertainty. The added computational expense of the method is cubic in the total number of observations over time, which is on the same order of magnitude as a standard Kalman filter and can be mitigated by bounding the number of forward propagated observations, discarding the least informative data.

97 MATHEMATICS AND COMPUTING↗