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DOE OSTI2020

Electron beam injection from a hollow cathode plasma into a downstream reactive environment: Characterization of secondary plasma production and Si 3 N 4 and Si etching

A material etching system was developed by combining beam electron injection from a direct current (DC) hollow-cathode (HC) electron source with the downstream reactive environment of a remote CF 4 /O 2 low temperature plasma. The energy of the injected beam electrons is controlled using an acceleration electrode biased positively relative to the HC Argon discharge. For an acceleration voltage greater than the ionization potential of Ar, the extracted primary electrons can produce a secondary plasma in the process chamber. We characterized the properties of the secondary plasma by performing Langmuir probe measurements of the electron energy probability function (EEPF) 2.5 cm below the extraction ring. The data indicate the existence of two major groups of electrons, including electrons with a primary beam electron energy which varies as the acceleration voltage is varied, along with low energy electrons produced by ionization of the Ar gas atoms in the process chamber by the injected beam electrons. When combining the HC Ar beam electron with a remote CF 4 /O 2 electron cyclotron wave resonance (ECWR) plasma, the EEPF of both the low energy plasma electron and beam electron components decreases. Additionally, we studied surface etching of Si3N4 and poly-crystalline Si (poly-Si) thin films as a function of process parameters, including the acceleration voltage (0-70 V), discharge current of the HC discharge (1-2 A), pressure (2- 100 mTorr), source to substrate distance (2.5 to 5 cm), and feed gas composition (with or without CF 4 /O 2 ). The direction of the incident beam electrons was perpendicular to the surface. Si 3 N 4 and poly-crystalline silicon etching are seen and indicate an electronneutral synergy effect. No/little remote plasma spontaneous etching was observed for the conditions used in this study, and the etching is confined to the substrate area irradiated by the injected beam electrons. The electron etched Si 3 N 4 surface etching rate profile distribution is confined within a ~30 mm diameter circle, which is slightly broader than the area for which poly-Si etching is seen, and coincides closely with the spatial profile of beam electrons as determined by the Langmuir probe measurements. The magnitude of poly-Si etching rate is by a factor of two times smaller than the Si 3 N 4 etching rate. In this paper, we discuss possible explanations of the data and the role of surface charging.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Modeling Isotope Separation in Electrochemical Lithium Deposition

Naturally occurring Li consists of two stable isotopes, 6 Li with an abundance of about 7.5%, and 7 Li making up the remainder with 92.5%. The development of a 6 Li enrichment technique, in terms of technical reliability and environmental safety to reach 6 Li future requirements, represents a key step in the roadmap for nuclear fusion energy supply worldwide. This paper uses finite element analysis-based models to simulate electrochemical Li isotope separation, which is an attractive method in terms of simplicity, safety, and scalability. In the model, we quantitatively analyze how different electrochemical factors including thermodynamics, charge-transfer kinetics, and diffusivities affect the separation process (separation factor), together with cell parameters, such as cell length and current density. The maximum separation factor of 1.128 could be obtained with the cell under the optimal thermodynamic, kinetic, and diffusive conditions, which is among the highest separation factors ever reported. Furthermore, these results will assist in designing the actual isotope separation setup with large separation factor and appropriate timing for sample collection.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2025

Enhanced Carbon Dioxide Uptake in Drilled Hollow Core Fibers for Raman Spectroscopy

Fiber-based Raman spectroscopy enhances the Raman signal by maximizing the overlap of the optical field and the gas species. However, filling the hollow-core fiber (HCF) with gas requires time that is dependent on the fiber core diameter, fiber length, and pressure of the gas. At ambient pressure, the fiber gas uptake is driven by diffusion into the fiber ends, severely limiting the response time of the system. By laser drilling access holes to the core along the length of the fiber, the uptake time of the gas is reduced, improving the system response time. In this work, we study the carbon dioxide (CO 2 ) sensor dynamics based on Raman signal intensity generated in HCFs. The signal intensity versus gas concentration is characterized by controlling the CO 2 concentration in the surrounding environment of the fiber. Next, we characterize the gas uptake time in HCFs as a function of fiber length. Finally, we optimize the access hole configuration along the fiber, demonstrating reduced sensor uptake time by a factor of three.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Comparing Designed Training Sets to Optimize Multivariate Regression Models for Pr, Nd, and Nitric Acid Using Spectrophotometry

Chemometric regression models were developed for the quantification of praseodymium (Pr, 0–1000 µg/mL), neodymium (Nd, 0–1000 µg/mL), and nitric acid (HNO 3 , 0.1–5 M) using spectrophotometry. Designed calibration sets were composed of 20 samples each: 10 model points and 10 lack-of-fit (LOF) points. The D-optimal designs effectively minimized the number of samples required to build models, and each design resulted in similar prediction performance, suggesting that statistical design of experiments can provide a reliable framework for selecting training set samples in three-variable systems. Partial least squares regression (PLSR) models were validated against a one-factor-at-a-time validation set composed of 125 samples (three variables, five levels). The top PLS-1 models resulted in average percent root mean square error of prediction error values of 3.5%, 1.7%, and 1.2% for Pr(III), Nd(III), and HNO 3 , respectively. Power set augmentations of the model and LOF samples were investigated to optimize the number of training set samples. PLSR models built using just required model points (10) had similar predictive capabilities as models including the LOF points (20) but with fewer samples. The number of validation samples was also varied systematically to learn how many samples are needed to validate regression models. This work addresses long-standing questions in the field of chemometrics to help make this approach amenable to the near-real-time quantification of hazardous species in remote settings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Surrogate modeling of Cellular-Potts agent-based models as a segmentation task using the U-Net neural network architecture

The Cellular-Potts model is a powerful and ubiquitous framework for developing computational models for simulating complex multicellular biological systems. Cellular-Potts models (CPMs) are often computationally expensive due to the explicit modeling of interactions among large numbers of individual model agents and diffusive fields described by partial differential equations (PDEs). In this work, we develop a convolutional neural network (CNN) surrogate model using a U-Net architecture that accounts for periodic boundary conditions. We use this model to accelerate the evaluation of a mechanistic CPM previously used to investigate in vitro vasculogenesis. The surrogate model was trained to predict 100 computational steps ahead (Monte-Carlo steps, MCS), accelerating simulation evaluations by a factor of 562 times compared to single-core CPM code execution on CPU. Over short timescales of up to 3 recursive evaluations, or 300 MCS, our model captures the emergent behaviors demonstrated by the original Cellular-Potts model such as vessel sprouting, extension and anastomosis, and contraction of vascular lacunae. This approach demonstrates the potential for deep learning to serve as a step toward efficient surrogate models for CPM simulations, enabling faster evaluation of computationally expensive CPM simulations of biological processes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Advanced Solar and Load Forecasting Incorporating HD Sky Imaging (Phase III)

Due to rapidly changing sky conditions, the available solar irradiance for energy generation is subject to wide swings in amplitude. As the market penetration of solar energy continues to increase rapidly, these variations in solar power generation are beginning to have an impact on grid stability and increased wear on power switches. Solar power forecasting plays a critical role in operations for Independent System Operators (ISOs) and utilities. Accurate forecasts help maintain grid reliability, optimize generation from renewables, and reduce operating costs. Of particular interest to the ISOs and utilities are sudden changes in solar irradiance, termed “ramp events,” due to the movement of clouds. One significant impact of ramp events on the grid is additional ancillary service requirements necessary to manage such variability. Ramp events can also cause voltage fluctuations in the distribution grids and trigger actions of automated line equipment (e.g., tap changers), leading to additional maintenance costs. In high penetration solar regions, forecasts must be made for both transmission-connected and distribution-connected resources – either behind the meter or in front of it. Particularly for distributed solar energy resources, forecasting can be a challenge due to the lack of visibility of the energy resource. Brookhaven National Laboratory (BNL) has been working towards nowcasting Global Horizontal Irradiance (GHI) using low-cost technologies for several years now. The Solar NowCasting technology being developed by BNL is a 0 – 30 min solar “nowcasting” technology applicable to a scale covering both large generating facilities and residential, distributed solar installations that relies on a network of ground-based high-definition (HD) cameras and surface pyranometers. GHI forecasts are being produced for both regions using 8 ground-based HD cameras and at least 2 surface pyranometers. When stitched together, the camera images can be used to forecast the impact of clouds on available solar irradiance over a domain of ~50 km 2 . Phase I of the project was the engineering scale up conceptual design stage. Phase II was the initial field test and demonstration, in which the technology was scaled up by a factor of 20 times and successfully demonstrated in eastern Long Island. In Phase III, an additional forecasting network was added in upstate NY and both networks are currently being operated until at least a full year of data is gathered by the Albany network to allow for the collection of sufficient data to evaluate performance against the persistence and smart persistence models using the Solar Arbiter.

14 SOLAR ENERGY↗

DOE OSTI2022

304L Can Crush Validation Studies

Accurate prediction of ductile behavior of structural alloys up to and including failure is essential in component or system failure assessment, which is necessary for nuclear weapons alteration and life extensions programs of Sandia National Laboratories. Modeling such behavior requires computational capabilities to robustly capture strong nonlinearities (geometric and material), rate- dependent and temperature-dependent properties, and ductile failure mechanisms. This study's objective is to validate numerical simulations of a high-deformation crush of a stainless steel can. The process consists of identifying a suitable can geometry and loading conditions, conducting the laboratory testing, developing a high-quality Sierra/SM simulation, and then drawing comparisons between model and measurement to assess the fitness of the simulation in regards to material model (plasticity), finite element model construction, and failure model. Following previous material model calibration, a J 2 plasticity model with a microstructural BCJ failure model is employed to model the test specimen made of 304L stainless steel. Simulated results are verified and validated through mesh and mass-scaling convergence studies, parameter sensitivity studies, and a comparison to experimental data. The converged mesh and degree of mass-scaling are the mesh discretization with 140,372 elements, and a mass scaling with a target time increment of 1.0e-6 seconds and time step scale factor of 0.5, respectively. Results from the coupled thermal-mechanical explicit dynamic analysis are comparable to the experimental data. Simulated global force vs displacement (F/D) response predicts key points such as yield, ultimate, and kinks of the experimental F/D response. Furthermore, the final deformed shape of the can and field data predicted from the analysis are similar to that of the deformed can, as measured by 3D optical CMM scans and DIC data from the experiment.

36 MATERIALS SCIENCE↗

DOE OSTI2023

(U) A General-Purpose Code for Correlated Sampling Using Batch Statistics with MCNP6 for Fixed-Source Problems

Correlated sampling can be used to reduce the uncertainty of a difference of tallies by taking advantage of the negative covariance term in the sandwich formula. Booth first showed how correlated sampling can be applied with batch statistics using MCNP’s tally fluctuation chart (TFC) to reduce the uncertainty of a difference of tallies in fixed-source problems. Booth presented a problem in which a 1273% uncertainty in a difference was reduced to 8% by accounting for correlations. Researchers He and Su recently studied correlated sampling using the TFC in MCNP version 5. They determined that the code did not print enough digits in the TFC tally means for accurate batch statistics in some cases. After modifying the source code, they concluded that “correlated sampling can yield a standard deviation of about one magnitude smaller than that predicted by the direct, un-correlated simulation when the changes in system response are small (say about 1%), which is equivalent to saving in CPU time by a factor of 100. Such saving [sic] becomes less significant as the change in system response becomes larger.” He and Su provided the formulas needed to apply batch statistics to compute the correlated uncertainty of a difference of tallies. In this report, we follow up on their work by providing the formulas needed to apply batch statistics to compute the correlated uncertainty of a ratio of tallies and of a difference of two tallies divided by a third tally. We extend these formulas to differences and ratios of ratios. These formulas are applied to reduce the uncertainty associated with calculating a relative sensitivity. He and Su did not investigate the accuracy of their correlated sampling uncertainty estimates. We use their test problems and evaluate the accuracy of the uncertainty estimates by comparing with results obtained from random sampling, and, in simple cases, with theoretical values of the “exact” uncertainties. We find that the uncertainties obtained from batch statistics are accurate as long as at least 100 batches are used. We present a new computer code, COSUBS (COrrelated Sampling Using Batch Statistics), that reads MCNP6 TFCs and applies correlated sampling using batch statistics for the tally combinations that the user specifies. COSUBS is a very general tool that compares all TFCs for a base case and one or two perturbed cases. It computes uncertainties for ratios if given only a base case. This report is organized as follows. The equations to apply batch statistics to the difference of random tallies are reviewed in Sec. II. Section III presents the equations for applying batch statistics to a ratio of random tallies; this is useful for computing relative sensitivities using a one-sided finite difference and the relative sensitivity using the differential operator method. Section IV presents the equations for applying batch statistics to a difference of two random tallies divided by a third; this is useful for computing a relative sensitivities using a central difference. Section V presents the equations for applying batch statistics to a difference of two ratios with four random tallies. Section VI presents the equations for applying batch statistics to a one-sided finite difference estimate of the relative sensitivity of a ratio (this uses four random tallies). Section VII presents the equations for applying batch statistics to a central difference estimate of the relative sensitivity of a ratio (this uses six random tallies). Section VIII presents the equations for applying batch statistics to a sum of random tallies. Section IX discusses how to apply batch statistics using MCNP6. Section X presents COSUBS, describing its command-line options and logic. Sections XI through XVI present numerical results for various test problems. Section XVII is a summary and conclusions. Appendix A derives the theoretical Monte Carlo tally variance given certain assumptions; these variances are used to verify the batch statistics for some of the problems. Appendix B lists the MCNP6 input for the unperturbed example problem. Appendix C presents modifications made to MCNP6.3 to support this work.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Relativistically Induced Transparency in Plasma (Final Research Report)

The major goal of this project was to study the process of relativistic transparency in plasmas. This process occurs when a very high intensity laser pulse interacts with a plasma. The electric field of the laser oscillates the electron speeds approaching the speed of light, increasing the effective mass of the electrons by the time-averaged Lorentz factor <γ>. The increase in the effective mass alters the critical density, the density at which the plasma becomes opaque to the electromagnetic wave of the laser. This project used experiments and particle-in-cell simulations to study this process in ultra-thin foil interactions. Experiments were performed through the LaserNetUS program on the Ohio State University laser system Scarlet. The transmitted and reflected light was studied as a function of the target thickness, the near-field profiles, the total energy and pulse duration were measured. Particle-in-cell simulations, using the OSIRIS code were used to model the interaction and better understand the dynamics. The results of both show current relativistic transparency theory is insufficient to predict the results, this is likely because the theories do not account for the laser energy absorption into the target and global plasma fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Oxidation of Dissolved Tetravalent Selenium by Birnessite: Se Isotope Fractionation and the Effects of pH and Birnessite Structure

Redox reactions control the mobility and bioavailability of selenium (Se) in biogeochemical systems, both modern and ancient. Se isotope ratio measurements (e.g., 82 Se/ 76 Se) have been developed to enhance understanding of biogeochemical transformations and transport of Se. Stable isotope ratios of many elements are known to be powerful indicators of redox reactions, and shifts in 82 Se/ 76 Se have been observed for Se reduction reactions. However, Se isotope shifts caused by naturally relevant oxidation reactions have not been published. Here, we report Se isotope fractionation factors for oxidation of Se(IV) by birnessite. Experiments were conducted at pH = 4.0 and 5.5, with two types of birnessite of contrasting composition at two concentrations of suspended birnessite. The results are consistent with a single 82 Se/ 76 Se fractionation factor, for all times during all experiments, of 0.99767 (±0.0035 2 s.d.). Expressed as ε, the fractionation is 2.33‰ (±0.08‰).

58 GEOSCIENCES↗

DOE OSTI2020

Post-Calibration Uncertainty Analysis for Travel Times at a Naval Weapons Industrial Reserve Plant

The Naval Weapons Industrial Reserve Plant (NWIRP) in McGregor, Texas began manufacturing explosives in 1980 and several hazardous chemicals were discovered in lakes and streams surrounding the site in 1998. Contaminants traveled to local lakes and streams much faster than initially predicted. This research estimated contaminant travel times and identified locations where monitoring wells should be installed to yield the greatest reductions in uncertainties in travel-time predictions. To this end, groundwater and particle-tracking models for NWIRP site were built to predict hydraulic heads and contaminant travel times. Next, parameter (hydraulic conductivities) uncertainties, parameter identifiabilities, observation (hydraulic heads) worth, and predictive (contaminant travel times) uncertainties were quantified. Parameter uncertainties were reduced by up to 92%; a total of 19 of 158 parameters were at least moderately identifiable; travel-time uncertainties were reduced up to 92%. Additionally, travel-time predictions and post-calibration parameter distributions were generated using the null-space Monte Carlo (NSMC) technique. NSMC predicted that conservative tracers exited the flow system within a year, which matches with field data. Finally, an observations-worth analysis found that additional 11 more measurements would reduce travel-time uncertainties by factors from 1.04 to 4.3 over existing data if monitoring wells were installed at the suggested locations.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2020

Bistable dynamics and Hopf bifurcation in a refined model of early stage HIV infection

Recent clinical studies have shown that HIV disease pathogenesis can depend strongly on many factors at the time of transmission, including the strength of the initial viral load and the local availability of CD4+ T-cells. In this article, a new within-host model of HIV infection that incorporates the homeostatic proliferation of T-cells is formulated and analyzed. Due to the effects of this biological process, the influence of initial conditions on the proliferation of HIV infection is further elucidated. The identifiability of parameters within the model is investigated and a local stability analysis, which displays additional complexity in comparison to previous models, is conducted. The current study extends previous theoretical and computational work on the early stages of the disease and leads to interesting nonlinear dynamics, including a parameter region featuring bistability of infectious and viral clearance equilibria and the appearance of a Hopf bifurcation within biologically relevant parameter regimes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Secured fault detection in a power substation

Systems and methods for fault detection and protection in electric power systems that evaluates electromagnetic transients caused by faults. A fault can be detected using sampled data from a first monitored point in the power system. Detection of fault transients and associated characteristics, including transient direction, can also be extracted through evaluation of sample data from other monitored points in the power system. A monitoring device can evaluate whether to trip a switching device in response to the detection of the fault and based on confirmation of an indication of detection of fault transients at the other monitored points of the power system. The determination of whether to trip or activate the switching device can also be based on other factors, including the timing of receipt of an indication of the detection of the fault transients and/or an evaluation of the characteristics of the detected transients.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Statistical Approaches for Pebble Bed Reactor Operations and Safeguards

The design of pebble bed reactors (PBRs) and their method of operation align more closely with statistical approaches used in manufacturing and process control than traditional safeguards statistical approaches. The reason is PBRs will employ a nondestructive assay (NDA) measurement (burnup measurement system [BUMS]) that is part of the fuel handling system supporting discharge decisions in addition to the reactor code which monitor performance. The integration of these two approaches provides the opportunity to monitor reactor performance statistically for both operations and safeguards in ways not achievable using other reactor designs. For light water reactors (LWRs), knowledge about reactor code performance in predicting irradiated special nuclear material (SNM) content historically was only achieved from special measurement campaigns or from fuel reprocessing. Conversely, through statistical comparison of the BUMS with the reactor code-predicted values, PBRs can achieve this in real time. The resulting SNM distribution is an indicator of reactor performance because factors such as transit time and path of the pebble fuel through the reactor determine the plutonium production and uranium depletion. By analyzing the predicted and measured values, opportunities exist to adjust operating parameters, fuel design, and other characteristics to optimize performance and fuel utilization. From a safeguards perspective, this approach also provides the information necessary to validate declared values and evaluate whether the reactor is being operated as expected. This paper outlines statistical approaches for PBRs that can be used to support both operations and safeguards.

Ball, Cory↗

DOE OSTI2023

Secured fault detection in a power substation

Cui, Tao↗

DOE OSTI2022

‪A Novel Methodology for Longitudinal Studies of Home Thermal Comfort Perception and Behavior

Human-building interactions significantly influence building energy consumption and affect peak energy demand. For example, heating and cooling contribute 46% of daily peak residential energy demand. Grid-interactive efficient buildings (GEBs) can potentially increase energy-demand flexibility and accelerate the adoption of renewables. However, traditional demand response (DR) programs focused on shedding peak loads disregard the human-building interactions leading to occupant thermal frustration. Specifically, they do not model occupants’ ability to override thermostat controls, nor how indoor environmental conditions and sociocultural factors affect the timing and magnitude of overrides. Studies have found 20% of occupants override thermostat setpoints during DR events longer than 6 hours yet lack detail about the motivation that might guide more successful efforts. Balancing energy-demand flexibility with occupant thermal comfort requires understanding dynamic occupant behavior, the underlying psychophysiological drivers, in the context of homes. This paper presents methods for scalable longitudinal studies of residential occupant behavior dynamics to inform the development of psychophysiological occupant-centric building models. Smart sensors were installed to measure local environmental conditions in 20 homes in two regions of the United States. Just-in-time ecological momentary assessments (EMAs) provided qualitative data on occupant thermal comfort and local environmental conditions not captured in Internet-of-Things (IoT) based studies or existing datasets. Participant interviews provided insight into environmental attitudes, mental models, and the role of economics in comfort and behavior, which in turn may affect thermostat interactions. Based on these data, interventions in the next phase of the study will collect data and monitor occupant behavior during simulated DR events.

Kane, Michael↗

DOE OSTI2026

Fast and bright scintillators for ultrafast materials dynamics using 4th generation synchrotron

We present recent advances in fast and bright scintillators for ultrafast X-ray phase contrast imaging of dynamic materials experiments at the upgraded Advanced Photon Source (APS-U), a fourth generation synchrotron. APS-U enables hard X-ray imaging at frame rates of at least 13 MHz (corresponding to 77 ns or shorter interframe intervals), creating a new need for scintillators with faster response and higher light output than lutetium yttrium oxyorthosilicate (LYSO). For indirect imaging and diffraction with ultrafast cameras, commercial lanthanum bromide (LaBr3) and cerium bromide (CeBr3) are promising candidates. These materials exhibit decay times approximately a factor of two shorter than LYSO (around 40 ns) and lutetium oxyorthosilicate (LSO), while maintaining comparable light yield per incident X-ray photon. However, their implementation at APS-U requires addressing several challenges, including material limitations due to hygroscopicity, efficient optical coupling to imaging systems, and high quantum efficiency for conversion of scintillation light, predominantly at wavelengths below 400 nm, into detectable electronic signals. We report results from material characterization, detector integration and packaging, and beamline experiments of materials with impact. In addition, emerging scintillator classes, including perovskites and high-entropy materials, are discussed as potential alternatives for next-generation ultrafast X-ray diagnostics.

Wang, Zhehui [Los Alamos] (ORCID:0000000178264063)↗

DOE OSTI2020

Stability Analysis of Interface Conditions for Ocean-Atmosphere Coupling

In this paper, we analyze the stability of different coupling strategies for multidomain PDEs that arise in general circulation models used in climate simulations. We focus on fully coupled ocean–atmosphere models that are needed to represent and understand the complicated interactions of these two systems, becoming increasingly important in climate change assessment in recent years. Numerical stability issues typically arise because of different time-stepping strategies applied to the coupled PDE system. In particular, the contributing factors include using large time steps, lack of accurate interface flux, and single-iteration coupling. We investigate the stability of the coupled ocean–atmosphere models for various interface conditions such as the Dirichlet–Neumann condition and the bulk interface condition, which is unique to climate modeling. By analyzing a simplified model, we demonstrate here how the parameterization of the bulk condition and other numerical and physical parameters affect the coupling stability and establish stability conditions for different coupling strategies.

97 MATHEMATICS AND COMPUTING↗