Robert Moser

Abstract A comprehensive collisional-radiative model is developed and coupled with a one-dimensional two-temperature fluid model to study capacitively coupled radio-frequency argon discharges at pressures ranging from 0.5 to 5 Torr and electrode peak-to-peak voltages of 150 and 300 V. The fluid model is formulated using the drift-diffusion approximation. The CR model accounts for the argon ground state, 30 excited states in the 4 s, 4p, 3d, and 5 s manifolds, electrons, atomic (Ar + ) and molecular (Ar <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msup> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> <mml:mo>+</mml:mo> </mml:msup> </mml:mrow> </mml:math> ) ions, and argon excimer molecules (Ar <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msup> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> <mml:mo>∗</mml:mo> </mml:msup> </mml:mrow> </mml:math> ). The processes included in the model are electron-impact excitation and ionization, radiation emission, heavy-particle collisions, radiative recombination, and processes involving Ar <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msup> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> <mml:mo>+</mml:mo> </mml:msup> </mml:mrow> </mml:math> and Ar <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msup> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> <mml:mo>∗</mml:mo> </mml:msup> </mml:mrow> </mml:math> molecules. Non-Maxwellian electron energy distribution functions, calculated using Bolsig+, are considered, with fine-structure collisional cross-sections acquired from the LXCat database. A detailed comparison is presented between numerical predictions and experimental measurements from a glow discharge device developed at UT Austin, focusing on populations of excited states in the 4p and 4 s manifolds, and electron number density. Additional comparisons are made with experimental data and PIC/Monte Carlo simulations from the study by (Donkó et al 2023 Plasma Sources Sci. Technol. 32 065002). While agreement with the Donkó et al data is somewhat improved—particularly with the PIC/Monte Carlo results—the CR-fluid model systematically overpredicts the experimental values. Possible contributing factors to these discrepancies and improvements to the model are discussed. In addition, the sensitivity of the results to the EEDF modeling is assessed by comparing simulations using Bolsig+-derived, Druyvesteyn, and Maxwellian distributions. The results show that predictions of electron temperature and plasma potential are strongly affected by the assumed EEDF shape. The inclusion of higher-lying excited states beyond the 4p manifold was found to have a minimal impact on discharge dynamics under the conditions studied. The code has been made publicly available on GitHub as open-source software.

We present an algorithm for solving the one-dimensional space collisional Boltzmann transport equation (BTE) for electrons in low-temperature plasmas (LTPs). Modeling LTPs is useful in many applications, including advanced manufacturing, material processing, and hypersonic flows, to name a few. The proposed BTE solver is based on an Eulerian formulation. It uses Chebyshev collocation method in physical space and a combination of Galerkin and discrete ordinates in velocity space. We present self-convergence results and cross-code verification studies compared to an in-house particle-in-cell (PIC) direct simulation Monte Carlo (DSMC) code. Boltzsim is our open source implementation of the solver. Furthermore, we use Boltzsim to simulate radio-frequency glow discharge plasmas (RF-GDPs) and compare with an existing methodology that approximates the electron BTE. We compare these two approaches and quantify their differences as a function of the discharge pressure. The two approaches show an 80x, 3x, 1.6x, and 0.98x difference between cycle-averaged time periodic electron number density profiles at 0.1 Torr, 0.5 Torr, 1 Torr, and 2 Torr discharge pressures, respectively. As expected, these differences are significant at low pressures, for example less than 1 Torr.

We explore the treatment of near-wall turbulence in coarse-grained representations of wall-bounded turbulence. Such representations are complicated by the fact that at high Reynolds number the near-wall effects occur in an asymptotically thin layer. Because of this, many near-wall models are posed as effective boundary conditions, essentially eliminating the thin wall layer that is too thin to resolve. This is commonly referred to as wall-modeled large eddy simulation, and the viability of this approach is supported by the weakness of the interaction between the near-wall turbulence and that further away. Such models are generally informed by known characteristics of near-wall turbulence, such as the log-layer in the mean velocity and the so-called law-of-the-wall. In this chapter, we consider such coarse-grained near-wall models and the approximations implicit in their formulation from the perspective of thin-layer asymptotics.

Abstract The predictive capability of a plasma discharge model depends on accurate representations of electron-impact collision cross sections, which determine the corresponding reaction rates and electron transport properties. The values of cross sections can be known only approximately either through experiments or simulations and are thus subject to uncertainties. Quantifying the uncertainties in plasma simulations allows us to assess the reliability of simulations and to provide a basis for interpreting discrepancies between simulations and experiments. For such uncertainty quantification of plasma simulations, it is essential to quantify the uncertainties of the underlying cross sections. Although much effort has been committed to calibrate the cross section values, their uncertainties are not well investigated. We characterize uncertainties in electron-argon atom collision cross sections using a Bayesian framework. Six collision processes—elastic momentum transfer, ionization, and four excitations—are characterized with semi-empirical models, which effectively capture the features important to the macroscopic properties of the plasma. A probability model for the uncertain parameters of these semi-empirical models is developed. Specifically, a Gaussian-process likelihood model is proposed to capture discrepancies among data sets, as well as the model-form inadequacies of the semi-empirical models. Two other likelihood models are compared with the proposed Gaussian-process model, to illustrate the importance of the choice of the likelihood model. The cross section models are calibrated using the electron-beam experiments and ab-inito quantum simulations. The resulting calibrated uncertainties capture well the scattering among the data sets. The calibrated cross section models are further validated against swarm-parameter experiments and zero-dimensional Boltzmann equation simulations of widely used cross section datasets.

OBJECTIVES: To investigate the resource capacity for blood banking in critical access hospitals (CAHs) in Kansas and the experiences of medical laboratory personnel working in them. METHODS: An electronic survey was implemented to record data from all 82 CAHs in Kansas between May and July 2023. The distance between hospitals with no blood bank services and commercial blood banks was calculated. RESULTS: Only 63.4% of Kansas CAHs located in nonmetropolitan counties reported access to 24/7 blood bank services. In 12.2% of laboratories with 5 or fewer workers, there were no staff proficient in blood bank testing. While 72% of laboratories could perform type and screen and crossmatching, many lacked antibody identification capacity. Only 2 hospitals had the capacity to transfuse packed red blood cells, plasma, and platelets simultaneously if needed, with 20.6% of nonmetropolitan hospitals holding no blood products in inventory. CONCLUSIONS: The blood banking capacity of CAHs in Kansas is influenced by the lack of workforce availability and training, reduced availability of blood products, and distance from facilities where blood is processed. Solutions tailored to the unique rural environment are needed to ensure adequate access to blood for patients.

INTRODUCTION: Rural communities often face chronic challenges of high rates of serious health conditions coupled with inadequate access to health care services-challenges exacerbated by the COVID-19 pandemic. One strategy with the potential to mitigate these problems is the increased use of telehealth technology. A feature of telehealth applications-collaboration between health care providers for consultation and other purposes-referred to herein as Rural Provider-to-Provider Telehealth (RPPT), introduces important expertise that may not exist locally in rural communities. Literature indicates that RPPT is operationalized through many methods with an array of purposes. While RPPT is a promising strategy that brings additional expertise to patient-centered rural care delivery, there is limited evidence addressing important considerations, including how patient access and outcomes, provider satisfaction and performance, and payment may be affected by its use. METHODS: Recognizing the significant potential of RPPT and the need for more information associated with its use, the National Institutes of Health convened a Pathways to Prevention (P2P) workshop to further understand RPPT's effectiveness and impact on improving health outcomes in rural settings. The P2P initiative, supported by several federal health agencies, engaged rural health stakeholders and experts to examine four key questions, identify related knowledge gaps, and provide recommendations to advance understanding of the use and impact of RPPT. RESULTS: Included in this report is a description of the process used to generate information about RPPT, the identification of key knowledge gaps, and specific recommendations to further build needed evidence. DISCUSSION: The emerging use of RPPT is an important tool for bridging gaps in access to care that impacts rural populations. However, to fully understand the value and effects of RPPT, new research is needed to fill the knowledge gaps identified in this report. Additionally, this report should help engage providers, payors, and policymakers interested in supporting evidence-informed RPPT practice, policy, and payment, with the ultimate aim of improving access to health care and health status of rural communities in the United States and worldwide.

We present a numerical method for the velocity-space, spatially homogeneous, collisional Boltzmann equation for electron transport in low-temperature plasma (LTP) conditions. Modeling LTP plasmas is useful in many applications, including advanced manufacturing, material processing, semiconductor processing, and hypersonics, to name a few. Most state-of-the-art methods for electron kinetics are based on Monte-Carlo sampling for collisions combined with Lagrangian particle-in-cell methods. We discuss an Eulerian solver that approximates the electron velocity distribution function using spherical harmonics (angular components) and B-splines (energy component). Our solver supports electron-heavy elastic and inelastic binary collisions, electron-electron Coulomb interactions, steady-state and transient dynamics, and an arbitrary nmber of angular terms in the electron distribution function. We report convergence results and compare our solver to two other codes: an in-house particle Monte-Carlo ethod; and Bolsig+, a state-of-the-art Eulerian solver for electron transport in LTPs. Furthermore, we use our solver to study the relaxation time scales of the higher-order anisotropic correction terms. Our code is open-source and provides an interface that allows coupling to multiphysics simulations of low-temperature plasmas.

The predictive capability of a plasma discharge model depends on accurate representations of electron-impact collision cross sections, which determine the key reaction rates and transport properties of the plasma. Although many cross sections have been identified through experiments and quantum mechanical simulations, their uncertainties are not well-investigated. We characterize the uncertainties in electron-argon collision cross sections using a Bayesian framework. Six collision processes -- elastic momentum transfer, ionization, and four excitations -- are characterized with semi-empirical models, whose parametric uncertainties effectively capture the features important to the macroscopic properties of the plasma, namely transport properties and chemical reaction rates. The method is designed to capture the effects of systematic errors that lead to large discrepancies between some data sets. Specifically, for the purposes of Bayesian inference, each of the parametric cross section models is augmented with a Gaussian process representing systematic measurement errors as well as model inadequacies in the parametric form. The results show that the method is able to capture scatter in the data between the electron-beam experiments and ab-initio quantum simulations. The calibrated cross section models are further validated against measurements from swarm-parameter experiments.

We develop a finite-rate chemistry mechanism for a non-equilibrium argon plasma. The mechanism includes electrons, singly ionized argon atom, and independent lumped state representations for the metastable and resonant argon excited atoms in the 1s manifold, and a single lumped state for the higher 4p excited argon states. This mechanism is validated against experimental data for the 4p excited state densities in a capacitively coupled argon (CCP) plasma discharge for intermediate pressures. A self-consistent one-dimensional plasma discharge model is used to represent the (CCP) discharge physics. Uncertainties in the reaction rate parameters were propagated through the discharge model to establish uncertainties in the model predictions. Results from the 1-D simulations of the glow discharge at different operating conditions are compared to experimental measurements, showing good agreement at higher pressures.

This article seeks to understand the circumstances under which minoritized women are descriptively represented. Drawing from a unique dataset of 7,978 legislators in 37 countries, we conduct the first cross-national examination of minoritized women’s representation at the level of individual legislators. We find that gender quotas, ethnic parties, and ethnic seats are effective at enhancing minoritized women’s political representation across different electoral systems, especially when clustered together. And, although ethnic parties and ethnic seats promote the representation of both minoritized women and men, ethnic seats provide a more level playing field between minoritized women and men than ethnic parties.

Wall-bounded turbulent shear flows are known to exhibit universal small-scale dynamics that are modulated by large-scale flow structures. Strong pressure gradients complicate this characterization, however. They can cause significant variation of the mean flow in the streamwise direction. For such situations, we perform asymptotic analysis of the Navier–Stokes equations to inform a model for the effect of mean flow growth on near-wall turbulence in a small domain localized to the boundary. The asymptotics are valid whenever the viscous length scale is small relative to the length scale over which the mean flow varies. To ensure the correct momentum environment, a dynamic procedure is introduced that accounts for the additional sources of mean momentum flux through the upper domain boundary arising from the asymptotic terms. Comparisons of the model's low-order, single-point statistics with those from direct numerical simulation and well-resolved large eddy simulation of adverse-pressure-gradient turbulent boundary layers indicate the asymptotic model successfully accounts for the effect of boundary layer growth on the small-scale near-wall turbulence.

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ExaWind Objective: Create an open-source predictive physics-based simulation capability that will provide a validated "ground truth" foundation for wind plant siting, operational controls, and reliably integrating wind energy into the grid ExaWind Motivation: Validated, predictive wind plant simulations will reduce the cost of energy by providing a path to better understanding of wind plant flow physics, which will lead to new plant layout design in complex terrain new turbine technologies to optimize plant performance a foundation for improved computer-aided engineering models, which will enable better design optimization