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At least 667 records · Page 37

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DOE OSTI2012

THE HANLE EFFECT OF Ly{alpha} IN A MAGNETOHYDRODYNAMIC MODEL OF THE SOLAR TRANSITION REGION

In order to understand the heating of the solar corona it is crucial to obtain empirical information on the magnetic field in its lower boundary (the transition region). To this end, we need to measure and model the linear polarization produced by scattering processes in strong UV lines, such as the hydrogen Ly{alpha} line. The interpretation of the observed Stokes profiles will require taking into account that the outer solar atmosphere is highly structured and dynamic, and that the height of the transition region may well vary from one place in the atmosphere to another. Here, we report on the Ly{alpha} scattering polarization signals we have calculated in a realistic model of an enhanced network region, resulting from a state-of-the-art radiation magnetohydrodynamic simulation. This model is characterized by spatially complex variations of the physical quantities at transition region heights. The results of our investigation lead us to emphasize that scattering processes in the upper solar chromosphere should indeed produce measurable linear polarization in Ly{alpha}. More importantly, we show that via the Hanle effect the model's magnetic field produces significant changes in the emergent Q/I and U/I profiles. Therefore, we argue that by measuring the polarization signals produced by scattering processes and the Hanle effect in Ly{alpha} and contrasting them with those computed in increasingly realistic atmospheric models, we should be able to decipher the magnetic, thermal, and dynamic structure of the upper chromosphere and transition region of the Sun.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Linear MHD stability analysis of post-disruption plasmas in ITER

Most of the plasma current can be replaced by a runaway electron (RE) current during plasma disruptions in ITER. In this case the post-disruption plasma current profile is likely to be more peaked than the pre-disruption profile. The MHD activity of such plasma will affect the runaway electron generation and confinement and the dynamics of the plasma position evolution (Vertical Displacement Event), limiting the timeframe for runaway electrons and disruption mitigation. In the present paper, we evaluate the influence of the possible RE seed current parameters on the onset of the MHD instabilities. By varying the RE seed current profile, we search for subsequent plasma evolutions with the highest and the lowest MHD activity. This information can be applied to a development of desirable ITER disruption scenario.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

A Comparative Assessment of Economic Model Predictive Control Strategies for Fuel Economy Optimization of Heavy-Duty Trucks

This paper provides a comparative assessment of three control strategies that fuse a global, offline dynamic programming (DP) optimization with online model predictive control (MPC) in an effort to minimize fuel consumption for a heavy-duty truck. The online MPC optimization, which is local in nature, makes refinements to a coarsely (but globally, subject to grid resolution) optimized target velocity profile from the DP optimization. Three candidate economic MPC formulations are evaluated: a time-based formulation that directly penalizes predicted fuel consumption, a simplified time-based formulation that penalizes braking effort in place of fuel consumption, and a distance-based convex formulation that maintains a tradeoff between energy expenditure and tracking of the coarsely optimized velocity based on DP. The performance of each approach is presented for three representative route profiles, using a medium-fidelity proprietary Volvo model of the heavy-duty truck’s longitudinal dynamics. Results demonstrate 4-7% fuel economy improvement across all three formulations, when compared to a baseline strategy. Furthermore, we present a detailed analysis of energy usage by “type” (aerodynamic losses, braking losses, and comparison of brake-specific fuel consumption), under each candidate control approach.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Oxidation Dynamics of Supported Catalytic Cu Clusters: Coupling to Fluxionality

Copper oxide nanoclusters have a wide range of catalytic applications, such as the selective oxidation of hydrocarbons. O 2 binding to the catalyst, activation, and release upon reagent oxidation are key events in these catalytic chemistries. Furthermore, these events are expected to be accompanied by significant structural changes of the Cu clusters, because O atoms integrate into the cluster, rather than bind to its surface. Topping the complexity of the problem, partially oxidized Cu clusters are known to exhibit strong fluxionality and feature diverse and interconverting structures and oxygen contents in conditions of oxidative dehydrogenation (ODH). Hence, a significant dynamic coupling between the “hot” O 2 molecule impacting the cluster at reaction temperatures and the cluster fluxionality can be expected. In this work, we focus on the dynamics of dioxygen integration into a partially oxidized Cu cluster supported on hydroxylated amorphous alumina–a system recently reported to be an exceptionally selective catalyst for cyclohexane ODH with very little CO produced, whose mechanistic underpinnings are of utmost interest. The statistics over a swarm of adsorption and scattering trajectories where O 2 hits various sites on the cluster at reaction temperature shows that the O 2 binding does not only follow the minimal energy paths. O 2 also rarely integrates into the cluster in a single step and instead first binds to a single Cu atom via either an η 1 -O 2 or an η 2 -O 2 mode. Surprisingly, this step often has a higher barrier than the subsequent O 2 integration and dissociation, which in turn take multiple steps and complete the oxidation process. Dynamic trajectories starting from the key transition state of integration of the adsorbed O 2 can also lead to different intermediate structures during or right after the dissociation, due to the energy released from the transition state and the thermal intracluster effects. From these activated O 2 chemisorbed structures, O 2 dissociation occurs with moderate barriers (~0.5 eV), producing multiple final oxidized Cu 4 O 4 states. Hence, a diversity of reaction profiles for the attack of supported Cu cluster by O 2 emerges due to the dynamic effects, with implications for mechanisms, kinetic models, and catalyst design principles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Finite-Time Universality in Nonequilibrium CFT

Recently, remarkably simple exact results were presented about the dynamics of heat transport in the local Luttinger model for nonequilibrium initial states defined by position-dependent temperature profiles. We present mathematical details on how these results were obtained. We also give an alternative derivation using only algebraic relations involving the energy-momentum tensor which hold true in any unitary conformal field theory (CFT). This establishes a simple universal correspondence between initial temperature profiles and the resulting heat-wave propagation in CFT. We extend these results to larger classes of nonequilibrium states. It is proposed that such universal CFT relations provide benchmarks to identify nonuniversal properties of nonequilibrium dynamics in other models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model

The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development. We use time-course gene expression profiles of a mouse model to estimate the relative abundance of cells and cytokines. We then employ a least-squares optimization method to evaluate the model’s parameters based on the mice data. The resulting dynamics of the cells and cytokines obtained from the optimal set of parameters exhibit a decent agreement between the data and predictions. We perform a sensitivity analysis to identify the crucial parameters of the model and then perform a local bifurcation on them. The results reveal a strong connection between adipocytes, IL6, and the cancer population, suggesting them as potential targets for therapies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Why Are There so Few Reports of High-Energy Electron Drift Resonances? Role of Radial Phase Space Density Gradients

Models of monochromatic Pc5 (2–7 mHz) ultralow frequency (ULF) wave interactions with high energy (greater than ~1 MeV) electrons predict drift resonant interactions that can cause rapid radial transport and acceleration. There are few reports of electron drift resonance at energies greater than ~1 MeV, in contrast to lower energies; moreover, all previous reports occur in the aftermath of interplanetary shocks. These two facts are difficult to reconcile with theory and numerical simulations predicting that greater than ~1 MeV drift resonances should occur more often and in a wider variety of driving conditions. In this study, we show that a combination of observational sampling biases and nominal radial phase space density gradients is one explanation for this discrepancy between theory and observations. In particular, we examine electron dynamics in two case studies with very similar satellite coverage, solar wind conditions, and Pc5 wave properties, yet with different radial phase space density profiles. Using global wave and particle observations, we show that the events have vastly different particle responses despite having similar wave properties. Placing these results in context with past studies, we further show here that nominal radial PSD gradients near geostationary orbit can mask the expected drift resonance particle response and explain (1) the small number of past greater than ~1 MeV drift resonance reports and (2) the restriction of these reports to interplanetary shock events. We argue that future observational studies characterizing radial transport via drift resonance should examine global particle dynamics, including observations of the radial phase space density profile.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation

ABSTRACT Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in health and disease. IMPORTANCE Studies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism.

Noecker, Cecilia↗

DOE OSTI2013

Improved Protein Arrays for Quantitative Systems Analysis of the Dynamics of Signaling Pathway Interactions

Astronauts and workers in nuclear plants who repeatedly exposed to low doses of ionizing radiation (IR, <10 cGy) are likely to incur specific changes in signal transduction and gene expression in various tissues of their body. Remarkable advances in high throughput genomics and proteomics technologies enable researchers to broaden their focus from examining single gene/protein kinetics to better understanding global gene/protein expression profiling and biological pathway analyses, namely Systems Biology. An ultimate goal of systems biology is to develop dynamic mathematical models of interacting biological systems capable of simulating living systems in a computer. This Glue Grant is to complement Dr. Boothman’s existing DOE grant (No. DE-FG02-06ER64186) entitled “The IGF1/IGF-1R-MAPK-Secretory Clusterin (sCLU) Pathway: Mediator of a Low Dose IR-Inducible Bystander Effect” to develop sensitive and quantitative proteomic technology that suitable for low dose radiobiology researches. An improved version of quantitative protein array platform utilizing linear Quantum dot signaling for systematically measuring protein levels and phosphorylation states for systems biology modeling is presented. The signals are amplified by a confocal laser Quantum dot scanner resulting in ~1000-fold more sensitivity than traditional Western blots and show the good linearity that is impossible for the signals of HRP-amplification. Therefore this improved protein array technology is suitable to detect weak responses of low dose radiation. Software is developed to facilitate the quantitative readout of signaling network activities. Kinetics of EGFRvIII mutant signaling was analyzed to quantify cross-talks between EGFR and other signaling pathways.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2024

Power System Operational Impacts of Electric Vehicle Dynamic Wireless Charging

The electrification of the transportation sector poses an opportunity for reducing greenhouse gas (GHG) emissions from passenger vehicles. Electric vehicle (EV) charging through dynamic wireless power transfer (DWPT), known as roadway electrification, could shift EV demand profiles to better coincide with renewable electricity generation. However, this would be a very large new load and few studies evaluate the regional impacts of DWPT charging in a power transmission system. This paper defines methods that address dataset generation for passenger vehicle trips and models to evaluate regional impacts for this emerging technology. Household vehicle miles traveled (VMT) data form localized EV demand profiles through discrete-event simulation. This data serves as exogenous inputs for a Production Cost Model (PCM) of a synthetic transmission system based on the Electric Reliability Council of Texas's (ERCOT) network. EV charging methods are compared for both a 2018 baseline generation mixture and a high-renewable generation case incorporating 20 GW of installed solar photovoltaic (PV) capacity. The PCM employs unit commitment and economic dispatch (UC&ED) models to compare financial, environmental, and grid reliability impacts from EV charging across passenger EV adoption levels. In-transit charging could reduce grid operational costs by as much as 1.49%, with up to $13.7B saved in annual vehicle operational costs for consumers compared to gas-powered vehicles. Health impacts analysis from power plant and vehicle tailpipe emissions from this study show net health benefits increase by 40% for in-transit charging coupled with high renewable generation. Renewable resources provide an avenue for cost-effective in-transit charging with reduced emissions. The combination of dataset generation and open-source power system modeling establish a foundation for the holistic evaluation of regional DWPT impacts.

dynamic wireless power transfer↗

DOE OSTI2015

PLASMA INSTABILITIES IN THE CONTEXT OF CURRENT HELIUM SEDIMENTATION MODELS: DYNAMICAL IMPLICATIONS FOR THE ICM IN GALAXY CLUSTERS

Understanding whether Helium can sediment to the core of galaxy clusters is important for a number of problems in cosmology and astrophysics. All current models addressing this question are one-dimensional and do not account for the fact that magnetic fields can effectively channel ions and electrons, leading to anisotropic transport of momentum, heat, and particle diffusion in the weakly collisional intracluster medium (ICM). This anisotropy can lead to a wide variety of instabilities, which could be relevant for understanding the dynamics of heterogeneous media. In this paper, we consider the radial temperature and composition profiles as obtained from a state-of-the-art Helium sedimentation model and analyze its stability properties. We find that the associated radial profiles are unstable to different kinds of instabilities depending on the magnetic field orientation at all radii. The fastest growing modes are usually related to generalizations of the magnetothermal instability (MTI) and the heat-flux-driven buoyancy instability which operate in heterogeneous media. We find that the effect of sedimentation is to increase (decrease) the predicted growth rates in the inner (outer) cluster region. The unstable modes grow quickly compared to the sedimentation timescale. This suggests that the composition gradients as inferred from sedimentation models, which do not fully account for the anisotropic character of the weakly collisional environment, might not be very robust. Our results emphasize the subtleties involved in understanding the gas dynamics of the ICM and argue for the need of a comprehensive approach to address the issue of Helium sedimentation beyond current models.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Resolution and Dynamical Core Dependence of Atmospheric River Frequency in Global Model Simulations

This study examines the sensitivity of atmospheric river (AR) frequency simulated by a global model with different grid resolutions and dynamical cores. Analysis is performed on aquaplanet simulations using version 4 of Community Atmosphere Model (CAM4) at 240, 120, 60 and 30 km model resolutions each with the Model for Prediction Across Scales (MPAS) and High-Order Methods Modeling Environment (HOMME) dynamical cores. The frequency of AR events decreases with model resolution and the HOMME dynamical core produces more AR events than MPAS. Comparing the frequencies determined using absolute and percentile thresholds of large-scale conditions used to define an AR, model sensitivity is found to be related to the overall sensitivity of sub-tropical westerlies, atmospheric precipitable water content and profile and to a lesser extent on extra-tropical Rossby wave activity to model resolution and dynamical core. Real world simulations using MPAS at 120 km and 30 km grid resolutions also exhibit a decrease of AR frequency with increasing resolution over southern East Pacific, but there difference is smaller over northern East Pacific. This inter-hemispheric difference is related to the enhancement of convection in over the tropics with increased resolution. This anomalous convection sets off Rossby wave patterns that weaken the subtropical westerlies over southern East Pacific but have relatively little effect on those over northern East Pacific. In comparison to NCEP2 reanalysis, MPAS real world simulations are found to underestimate AR frequencies at both resolutions likely because of their climatologically drier sub-tropics and poleward shifted jets. This study highlights the important links between model climatology of large-scale conditions and extremes.

atmopheric river frequency↗

DOE OSTI2023

Insights into the relation between vertical cloud structure and dynamics of three polar lows: Observations from COMBLE

The vertical structure of three polar lows is described using profiling radar, lidar, and passive remote sensors deployed at a coastal site in northern Norway. The data were collected as part of the Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE). These data are examined in the context of satellite imagery, operational weather radar reflectivity imagery, and output from the AROME-Arctic model. A comparison to satellite images shows that AROME-Arctic captured the polar lows well. All three polar lows form in marine cold-air outbreaks and are surrounded by open-cellular convection typical of such outbreaks. Two of the lows form in a forward shear environment, and one under reverse shear. Initially, the three polar lows are comma-shaped; two of them transition to be more spirali-form at their mature stage and have mostly cloud-free warm cores. The warm cores are the result of a warm-seclusion process. All three lows have stratiform precipitation bands, marked by little cloud liquid water, and rather high surface precipitation rate. The vertical drafts and turbulence in these stratiform clouds are generally weak. In conclusion, all three lows also have convective clouds, which have stronger vertical drafts, stronger turbulence, and pockets of high liquid water content.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Coupled transmission and distribution simulations to assess distributed generation response to power system faults

Not Available

Kenyon, Rick Wallace (ORCID:0000000344599708)↗

DOE OSTI2014

Inertia driven radial breathing and nonlinear relaxation in cylindrically confined pure electron plasma

The dynamics of cylindrically trapped electron plasma has been investigated using a newly developed 2D Electrostatic PIC code that uses unapproximated, mass-included equations of motion for simulation. Exhaustive simulations, covering the entire range of Brillouin ratio, were performed for uniformly filled circular profiles in rigid rotor equilibrium. The same profiles were then loaded away from equilibrium with an initial value of rigid rotation frequency different from that required for radial force balance. Both these sets of simulations were performed for an initial zero-temperature or cold load of the plasma with no spread in either angular velocity or radial velocity. The evolution of the off-equilibrium initial conditions to a steady state involve radial breathing of the profile that scales in amplitude and algebraic growth with Brillouin fraction. For higher Brillouin fractions, the growth of the breathing mode is followed by complex dynamics of spontaneous hollow density structures, excitation of poloidal modes, leading to a monotonically falling density profile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Inertia driven radial breathing and nonlinear relaxation in cylindrically confined pure electron plasma

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

A gyrokinetic simulation model for 2D equilibrium potential in the scrape-off layer of a field-reversed configuration

The equilibrium potential structure in the scrape-off layer (SOL) of the field-reversed configuration (FRC) can be affected by the penetration of edge biasing applied at the divertor ends. The primary focus of the paper is to establish a formulation that accurately captures both parallel and radial variations of the two-dimensional (2D) potential in SOL. The formulation mainly describes a quasi-neutral plasma with a logical sheath boundary. A full-f gyrokinetic ion model and a massless electron model are implemented in the GTC-X code to solve for the self-consistent equilibrium potential, given fixed radial potential profiles at the boundaries. The first essential point of this 2D model lies in its ability to couple radial and parallel dynamics stemming from resistive currents and drag force on ions. The model successfully recovers the fluid force balance and continuity equations. These collisional effects on 2D potential mainly appear through the density profile changes, modifying the potential through electron pressure gradient. This means an accurate prescription of electron density and temperature profiles is important in predicting the potential structure in the FRC SOL. The Debye sheath potential and the potential profiles applied at the boundaries can be additional factors contributing to the 2D variations in SOL. This comprehensive full-f scheme holds promise for future investigations into turbulent transport in the presence of the self-consistent 2D potential together with the non-Maxwellian distributions and open boundary conditions in the FRC SOL.

Physics↗

DOE OSTI2025

Subject-specific modeling framework for particle deposition using computational fluid dynamics

Quantifying particle deposition and dose in the respiratory tract requires a physiologically realistic representation and reproducible computational workflows. However, existing modeling frameworks, such as the International Commission on Radiological Protection (ICRP) compartmental models and the Multiple Path Particle Dosimetry (MPPD) tool, lack detailed deposition profiles and subject-specific capabilities. The combination of advances in computer vision algorithms applied to the respiratory tract and Computational Fluid and Particle Dynamics (CFPD) allows high-fidelity simulations of particle behavior in anatomically accurate geometries derived from individual CT scans. The segmentation, preprocessing, and file preparation task for a CFPD simulation was often time-consuming, and no prior studies to-date have yet presented a fully automated framework. This work presents a fully automated workflow to obtain individualized particle deposition profiles in the human respiratory tract. The pipeline starts with segmenting upper and lower airway geometries using morphological and deep learning-based methods, generating three-dimensional (3D) models from CT imaging data. Next, a series of algorithms are presented to quality check and prepare the 3D geometry for a CFD or CFPD simulation. The preprocessing step includes correcting geometric artifacts, enforcing a physically consistent mesh, and automatically identifying and capping multiple outlets, which is required for CFD/CFPD simulations. These processed models are then input into open-source (OpenFOAM) or commercial (StarCCM+) CFD solvers, where flow and transient particle transport equations — including turbulence and particle–wall interactions are solved under realistic breathing conditions. Finally, the resulting particle deposition profiles can be integrated with Monte Carlo radiation transport codes and state-of-the-art computational phantoms to assess organ-specific absorbed doses in scenarios of radioactive aerosol inhalation. The presented work streamlines respiratory tract segmentation, preprocessing for CFD/CFPD simulations, and integration with dose assessment workflows, reducing manual intervention and improving access to high-fidelity, subject-specific modeling. The high precision in predicted particle deposition and dose distributions can improve personalized treatment strategies in respiratory medicine and refine dose estimates for radiation protection.

AI↗