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At least 1,405 records · Page 78

Signal Whisperers: Enhancing Wireless Reception Using DRL-Guided Reflector Arrays

This paper presents a multi-agent reinforcement learning (MARL) approach for controlling adjustable metallic reflector arrays to enhance wireless signal reception in non-line-of-sight (NLOS) scenarios. Unlike conventional reconfigurable intelligent surfaces (RIS) that require complex channel estimation, our system employs a centralized training with decentralized execution (CTDE) paradigm where individual agents corresponding to reflector segments autonomously optimize reflector element orientation in three-dimensional space using spatial intelligence based on user location information. Through extensive ray-tracing simulations with dynamic user mobility, the proposed multi-agent beam-focusing framework demonstrates substantial performance improvements over single-agent reinforcement learning baselines, while maintaining rapid adaptation to user movement within one simulation step. Comprehensive evaluation across varying user densities and reflector configurations validates system scalability and robustness. The results demonstrate the potential of learning-based approaches for adaptive wireless propagation control.

deep reinforcement learning↗

Distinct Gas-Particle Partitioning and Viscosity Characteristics of Secondary Organic Aerosols Derived from α-Pinene versus Ocimene

Secondary organic aerosols (SOA) have complex, multicomponent composition that controls particle viscosity and gas-particle partitioning, key factors to their atmospheric evolution. This study investigates the chemical composition, volatility and viscosity of SOA formed by ozonolysis of cyclic α-pinene (PSOA) and acyclic ocimene (OSOA) monoterpenes. Using Temperature-Programmed Desorption combined with Direct Analysis in Real-Time ionization and High-Resolution Mass Spectrometry, we determined the molecular composition and saturation mass concentration of individual SOA constituents. These data enabled gas-particle partitioning and viscosity estimates under varied atmospheric conditions. PSOA, composed of higher molecular weight and less oxidized species, shows higher condensability and viscosity under high total organic mass (tOM) loadings. Here, in contrast, OSOA, consisting of more oxidized, lower molecular weight species, exhibits greater sensitivity to tOM, with viscosity increasing significantly upon dilution. Poke-flow experiments support this trend, indicating that OSOA undergoes more dynamic compositional and phase changes during atmospheric aging. These observations reveal distinct dynamic trends in the atmospheric transformations and reactivity of SOA from cyclic and acyclic monoterpenes, with the latter showing greater compositional changes during aging that alter viscosity and diffusion. This highlights the importance of incorporating such dynamic transformations into atmospheric models to improve predictions of SOA atmospheric loadings, lifetimes, and impacts.

cyclic and acyclic monoterpenes↗

Systematic Underestimation of Canopy Conductance Sensitivity to Drought by Earth System Models

The response of vegetation canopy conductance (g c ) to changes in moisture availability ($γ^{m}_{gc}$) is a major source of uncertainty in climate projections. While vegetation typically reduces stomatal conductance during drought, accurately modeling how and to what degree stomata respond to changes in moisture availability at global scales is particularly challenging, because no global scale g c observations exist. Here, we leverage a collection of satellite, reanalysis and station-based near-surface air and surface temperature estimates, which are physically and statistically linked to $γ^{m}_{gc}$ due to the local cooling effect of g c through transpiration, to develop a novel emergent constraint of $γ^{m}_{gc}$ in an ensemble of Earth System Models (ESMs). We find that ESMs systematically underestimate $γ^{m}_{gc}$ by ~33%, particularly in grasslands, croplands, and savannas in semi-arid and bordering regions of the Central United States, Central Europe, Southeastern South America, Southern Africa, Eastern Australia, and parts of East Asia. We show that this underestimation occurs because ESMs inadequately reduce g c when soil moisture decreases. As g c controls carbon, water and energy fluxes, the misrepresentation of modeled $γ^{m}_{gc}$ contributes to biases in ESM projections of gross primary production, transpiration, and temperature during droughts. Our results suggest that the severity and duration of droughts may be misrepresented in ESMs due to the impact of sustained g c on both soil moisture dynamics and the biosphere-atmosphere feedbacks that affect local temperatures and regional weather patterns.

54 ENVIRONMENTAL SCIENCES↗

The decay of HIV under anti-retroviral therapy is biphasic even in humanized mice with just T cells

HIV-1 plasma viral load decays in a biphasic manner during antiretroviral therapy (ART). It was hypothesized that this is due to infection of different cell types, namely CD4+ T cells and macrophages. We studied this possibility directly by modeling the decay of HIV-1 in humanized mice. We utilized previously published data from humanized T-cell only mice (TOM) and myeloid-only mice (MOM) infected with HIV-1 and treated with a potent ART regimen. Viral load decay dynamics were modeled using either a single or a biexponential decay fitted using nonlinear mixed effects techniques. Fits were compared using the corrected Bayesian information criterion (BICc). In TOM, the biphasic model was significantly better than a single-phase decay model (ΔBICc ≈ 16) despite additional parameters. In MOM, the biphasic decay was statistically better, but there was substantial uncertainty because the virus goes below detection very fast. The first-phase half-life was consistent between groups (1.2 days in MOM and 1.3 days in TOM) and similar to the half-life estimated in human infection. The second-phase decay in these mice was minimal likely due to low initial viral loads. Additional analyses with mice containing both CD4+ T cells and macrophages or X4-tropic virus-infected MOM mice confirmed the biphasic pattern, demonstrating the robustness of this result. The biphasic decline in HIV-1 occurs, even with only CD4+ T cells, refuting the hypothesis that distinct cell populations (CD4+ T cells and macrophages) drive each decay phase. These findings support an alternative model in which the observed dynamics arise from intrinsic properties of the viral infection lifecycle rather than from cellular compartmentalization.

59 BASIC BIOLOGICAL SCIENCES↗

Multi-Agency Annual Southeastern Beach Mouse Habitat Occupancy Monitoring

The southeastern beach mouse (Peromyscus polionotus niveiventris, hereafter SEBM), a federally threatened species was identified by Merritt Island National Wildlife Refuge (MINWR) as one of the top five priorities for management. The Kennedy Space Center (KSC) Environmental Management Branch was asked to provide support in the form of population monitoring for SEBM on KSC and the surrounding properties. When we began the project, the SEBM was known to occupy sites ranging from Volusia through Brevard and Indian River Counties, but the exact distribution within the Federal lands encompassing the Cape Canaveral Barrier Island Complex (CCBIC) was not well known. The broad range of habitat conditions encompassing the species’ historical range and the diversity of sites historically known to contain SEBM required a landscape-scale approach for both monitoring the population and for investigating species habitat relationships. We designed a monitoring plan for the SEBM with the goal of estimating the habitat occupancy of beach mice annually each winter/spring throughout the entire area of suitable coastal habitat (approximately 72 km linear distance along the beach). Methods were tested in a 2008 pilot study, and during 2010-2018 we monitored the proportion of coastal habitat occupied by the SEBM on the CCBIC. Monitoring was focused on using dynamic habitat occupancy surveys with data collected with rapid assessment techniques (i.e., track tubes or live-traps) to detect SEBM occurrence at sampling stations. An important component of the study design was the use of repeated samples that provided the information needed to estimate detectability. Measuring detectability was required to account for the fact that surveys could fail to detect animals at sites at which they were actually present (Mackenzie et al., 2002). This monitoring framework is very flexible, allowing numerous hypothesis to be tested about how various factors influence beach mouse occupancy using habitat, geographic, and environmental covariates. Our survey has been the longest survey conducted for any of the seven extant beach mouse subspecies and has encompassed nearly the entire remaining range of the SEBM. Although occupancy surveys of other beach mouse subspecies via track tubes have been conducted on the Gulf coast of Florida by Florida Fish and Wildlife Conservation Commission (FWC), United States Fish and Wildlife Service (USFWS), and various universities, we expanded previous methods to fit unique aspects of the SEBM, and thus our study was very different from any of the previous studies. To achieve this specificity, we employed an adaptive approach throughout the study, with all activities aimed at providing managers with information related to environmental compliance and natural resource management on KSC and the surrounding Federal lands.

Eric Douglas Stolen↗

Hexagonal Distributed Embedded Energy Converters (HexDEECs)

Distributed Embedded Energy Converter Technologies (DEEC-Tec) is a new domain for marine renewable energy research that utilizes a conglomeration of small distributed embedded energy converters (DEECs) that, in aggregate, form larger metamaterial frameworks. These resulting DEEC-Tec metamaterials can then, in turn, be used to construct flexible ocean wave energy converters called flexWECs. DEEC-Tec enables flexWECs: (i) to be inherently broad-banded ocean wave frequency energy converters and (ii) to have an inherent lack of highly loaded rigid bodies. The DEEC-Tec domain also benefits the marine renewable energy domain by inherently availing ways that marine energy can be harvested and converted that heretofore has not yet been considered possible: real-time execution of transforming topologies (e.g., actively changing a flexWEC's shape and form) and morphologies (e.g., actively changing a flexWEC's stiffness and damping throughout its entire structure). Presented, is one specific type of DEEC, a HexDEEC, that shows promise in aiding the adoption and further development of the DEEC-Tec domain - it is a small energy transducer being developed by the United States National Renewable Energy Laboratory. The HexDEEC is a small (characteristic length approximating a centimeter) energy transducer that converts the dynamic deformations of an elastomer into electricity through a charging-discharging cycle of a capacitor whose capacitance is varied by those elastic deformations. The HexDEEC is composed of a hyperelastic hexagonal housing (nominally silicon rubber) with six electrodes on its inner faces. The upper three electrodes share the same charge while the lower three electrodes oppose the upper electrode charges. Externally, the HexDEEC has two arms extending away from the middle vertices of the hexagon. Via principles governing the relationship between electrical capacitance and electrical potential (voltage and charge), electricity is generated when the HexDEEC's arms are dynamically pulled or released under tensile loading as doing so causes the distance between the upper and lower sets of electrodes to change - varying the energy converter's overall capacitance. Analytical and numerical modeling have already been used to estimate the electrical energy produced by a HexDEEC. The cursory models approximate the HexDEEC as a parallel plate variable capacitor - simplifying from six to two opposing plates with a constant dielectric volume between those two plates. To account for the elastic HexDEEC material properties, software such as SolidWorks and STAR-CCM+ have been used to generate hyperelastic models; notably, Mooney-Rivlin based models. Individual HexDEECs have been fabricated by drawing uncured liquid silicon rubber into molds via vacuum pressure. To simplify manufacturing, HexDEEC sub-components - e.g., electrodes, wires - can be placed within those molds such that they are directly embedded into the hexagonal housing during the curing process. Furthermore, DEEC-Tec metamaterials can be created by interweaving or sequentially layering multiple HexDEEC strands together. The HexDEEC based metamaterial could then generate electricity through its gross deformations. Ultimately, HexDEECs represent a specific type of energy transducer that can be leveraged, by the DEEC-Tec domain, to create metamaterials used to construct novel flexWECs.

DEEC-Tec↗

An analysis of parameters affecting ampacity in aircraft bipolar MVDC power cables via coupled electrical, thermal, and computational fluid dynamic modelling

Abstract The next generation of aircraft, including more electric aircraft and all‐electric aircraft (AEA), requires electric power systems with high power density and low system mass specifications. Increasing the voltage of the system to the range of a few kV, medium voltage (MV), is a reasonable approach to achieving high‐power‐density and low‐system‐mass EPSs for aircraft applications. Higher voltages, however, pose many challenges for aviation MV power cables such as arcs and arc tracking, partial discharges (PDs), and thermal management. In this regard, thermal management is more challenging since heat transfer by convection is greatly reduced at wide‐body aircraft's cruising altitudes due to the reduced air pressure. In this paper, a finite element method (FEM) model is developed in COMSOL Multiphysics for an aircraft bipolar MVDC (±5 kV) power cable. Using the model, the maximum permissible cable current at a low pressure of 18.8 kPa (at an altitude of 12.2 km from sea level, the usual cruising altitude for wide‐body aircraft) is calculated. Also, an analytical model is developed based on analytical and proven empirical correlations governing conductive, radiative, and convective heat transfers at the steady state to estimate the ampacity of the bipolar cable system at reduced pressure. It was shown that the proposed analytical model can be used for atmospheric pressure and systems with a larger number of poles, expanding its range of applications. The results of the FEM and analytical models correlate at wide ranges of parameters such as ambient temperature, duct size, distance between the positive and negative pole cables, and the overall diameter of the cables. The influence of horizontal and vertical arrangement of poles is included in the analytical model. The results of this study can be used to design bipolar MVDC power cable systems for the envisaged wide‐body AEA.

Azizi, Arian↗

Utilization of STRAT Data

One of the goals of the STRAT mission was to improve our understanding of transport in the stratosphere. We have used our coupled 2-D model to analyse transport between the tropics and midlatitudes using aircraft measurements of (CO2) and (N2O) made during the SPADE and ASHOE/MAESA campaigns (Boering et al. 1994) for model validation. We have further used the model to estimate errors in the experimental determination of the age of stratospheric air that arise from nonlinear increases of real tracers such as (CO2) and (SF6). The interpretation of measurements made during STRAT is still in progress. Most of the work performed under this contract has been described in the second year progress report, submitted in April of 1996. In the following, the research is summarized and some additional work that has become relevant in the meantime is described. We have developed an interactive model of the dynamics, chemistry and radiation of the stratosphere with partial support from this contract. The dynamics module integrates the primitive equations on a sphere. Lower boundary zonal winds and eddy geopotential heights are specified from observations. Chemistry and tracer transport are done in two dimensions. The chemistry model is a family model. Long lived species are transported and short lived species are determined in intervals of 5 to 10 days by assuming photochemical steady state. Full diurnal integrations with the fast species are performed periodically and diurnal coefficients, derived from the explicit integration are used to determine the steady state solution. Heating rates in the stratosphere are calculated from model ozone and the model temperatures and circulation fields are used in the chemistry transport module.

Source record↗

Cross-scale covariance for material property prediction

A simulation can stand its ground against an experiment only if its prediction uncertainty is known. The unknown accuracy of interatomic potentials (IPs) is a major source of prediction uncertainty, severely limiting the use of large-scale classical atomistic simulations in a wide range of scientific and engineering applications. Here we explore covariance between predictions of metal plasticity, from 178 large-scale (~10 8 atoms) molecular dynamics (MD) simulations, and a variety of indicator properties computed at small-scales (≤10 2 atoms). All simulations use the same 178 IPs. In a manner similar to statistical studies in public health, we analyze correlations of strength with indicators, identify the best predictor properties, and build a cross-scale “strength-on-predictors” regression model. This model is then used to estimate regression error over the statistical pool of IPs. Small-scale predictors found to be highly covariant with strength are computed using expensive quantum-accurate calculations and used to predict flow strength, within the statistical error bounds established in our study.

36 MATERIALS SCIENCE↗

A multi model ensemble reveals net climate benefits from regenerative practices in US Midwest croplands

Process-based cropping systems models (CSMs) are key components of measurement, monitoring, reporting, and verification frameworks of carbon markets, but model-specific differences limit their applicability across diverse pedo-climatic conditions and agronomic practices. Multi-model ensemble (MME) provides an opportunity to better estimate changes in soil organic carbon (SOC) and nitrous oxide (N 2 O) emissions from agronomic practices at scale. We used an MME across 46 million hectares of US Midwest cropland at a resolution of 4-km 2 to assess the aggregate ability of different regenerative practices to sequester SOC and N 2 O emissions compared to their counterfactual dynamic baselines. MME was validated against long-term trials and compared to its constituent CSMs, showing greater accuracy and lower uncertainty. The results show that adopting no-till combined with cover crops increased SOC stocks by 0.36 ± 0.12 Mg ha -1 yr -1 , corresponding to a net regional SOC gain of 16.4 Tg C yr -1 compared to business-as-usual baselines. These benefits are halved when each management is practiced individually, and the SOC gains are only fully realized with low initial carbon stock. By including N 2 O emissions, we can assess the overall climate mitigation potential, specifically, the extent to which carbon sequestration can offset direct N 2 O emissions. The magnitude of this potential varies depending on management practices and geographic location with net climate benefits on average ranging from 0 to 3 Mg CO 2 -eq ha -1 yr -1 . High-resolution MME results allow for robust estimates of climate mitigation, reducing barriers to carbon market participation and supporting regenerative agriculture initiatives at scale.

carbon credits↗

Bottomonium properties in the quark-gluon plasma from a lattice-QCD informed 𝑇-matrix approach

Recent computations of bottomonium correlation functions with extended sources in lattice-discretized quantum chromodynamics (lQCD) provide new insights into heavy-quark dynamics at distance scales which are of the order of the inverse temperature. We analyze these results employing the thermodynamic 𝑇-matrix framework, in a continued effort to interpret lQCD data for quarkonium correlation functions in a nonperturbative and self-consistently solved quantum-many-body approach to a strongly coupled quark-gluon plasma (QGP). Its key inputs are the in-medium driving kernel (potential) of the scattering equation and an interference function which implements 3-body effects in the quarkonium coupling to the thermal medium. A simultaneous description of lQCD results for the bottomonium correlators with extended operators and the previously analyzed Wilson line correlators only requires minor refinements of the potential but calls for stronger interference effects at larger separation of the bottom quark and antiquark. We then analyze the poles of the self-consistent 𝑇 matrices on the real axis to assess the survival of the various bound states. Here, we estimate the pertinent temperatures where the poles disappear for the various bottomonium states and discuss the relation to the corresponding peaks in the bottomonium spectral functions. We also recalculate the spatial diffusion coefficient of the QGP and find it to be similar to that in our previous study.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Experimental Investigation of Innovative Cooling Schemes on an Additively Manufactured Engine Scale Turbine Nozzle Guide Vane

This study includes the design, validation, and fabrication via direct metal laser sintering (DMLS) of a gas turbine nozzle guide vanes (NGV) that incorporates three innovative cooling schemes specifically enabled by additive manufacturing. The novel NGV design is the culmination of an extensive research and development effort over a period of 4 years that included low- and high-speed cascade testing coupled with unsteady computational fluid dynamics for numerous candidate innovative cooling architectures. The final vane design (SJ-vane) consists of sweeping jet (SJ) film cooling holes on the suction surface (SS), sweeping jet impingement holes at the leading edge and double-wall partial length triangular pin-fin with impinging jet at the trailing edge. For comparison purposes, a second DMLS enabled vane (777-vane) was designed and fabricated with prototypical cooling circuits to serve as a baseline. This vane consists of a shaped film cooling holes on the suction surface, circular impingement holes at the leading edge, and full-length cylindrical pin-fins at the trailing edge. Experiments with the two DMLS enabled vanes were performed at the Ohio State University Turbine Reacting Flow Rig (TuRFR) at engine-relevant temperature (1375 K) and Mach number conditions. Infrared (IR) thermography was utilized to measure the wall temperature of the pressure and suction surface at several coolant mass flowrates to estimate the overall cooling effectiveness (ϕ). Results showed improved cooling performance for the advanced cooling schemes (sweeping jet film cooling, impingement cooling, and triangular pin-fin cooling) compared with the baseline cooling schemes.

Engineering↗

Optimization of Archimedes Screw for Use in Hydroelectric Projects

In 2017, the Department of Energy’s (DOE) Water Power Technologies Office (WPTO) made federal funding available to several awardees to investigate and provide innovative technological solutions to reduce capital costs of installed hydroelectric facilities at non-powered dam’s (NPD’s) across the United States, while maintaining a high level of efficiency. Awardees were to develop specific technologies that showed promise of reducing installed capital cost (ICC) by at least 20% over a given baseline and maintain a water-to-wire efficiency of at least 80% at head levels of 50 feet or less and flows of 1000 cubic feet per second (cfs) or less. Canyon Hydro (Canyon) was selected as an awardee for this funding and worked to refine the implementation of the Archimedes screw turbine for use at these site conditions. Canyon and its project partners analyzed several dam inventory datasets to determine the most common head and flow range of current NPD’s in order to best select design conditions for a turbine that would perform successfully at common heads and flows. Computational Fluid Dynamic (CFD) analyses were conducted after site conditions had been selected to optimize the turbine geometry for efficiency. Through this effort we were able to estimate water-to-wire efficiency over a range of flows. Equipment design focused on concepts of modularity and pre-fabricated construction. These methodologies were used where possible to reduce costly on-site construction and shorten deployment timelines. Cost modeling was conducted with input from industry experts in general construction, pre-fabricated concrete construction, and composite fabrication. As a hydroelectric turbine manufacturer of 35 years, Canyon drew upon its own knowledge base in steel fabrication, water-to-wire component specification and ancillary systems to develop the remaining cost matrix for the project. As a result of these efforts, Canyon was able to present findings that indicated a modular Archimedes screw turbine system could be designed that reduced ICC by 23.9% and maintain a maximum water-to-wire efficiency of 82.3%, meeting the goals of the project.

13 HYDRO ENERGY↗

Understanding Solar Eruptions with SDO/HMI Measuring Photospheric Flows, Testing Models, and Steps Towards Forecasting Solar Eruptions

The Solar Dynamics Observatory (SDO) is carrying the first full-disk imaging vector magnetograph, the Helioseismic and Magnetic Imager (HMI), into an inclined geosynchronous orbit. This magnetograph will provide nearly continuous measurements of photospheric vector magnetic fields at cadences of 90 seconds to 12 minutes with 1" resolution, precise pointing, and unfettered by atmospheric seeing. The enormous data stream of 1.5 Terabytes per day from SAO will provide an unprecedented opportunity to understand the mysteries of solar eruptions. These ground-breaking observations will permit the application of a new technique, the differential affine velocity estimator for vector magnetograms (DAVE4VM), to measure photospheric plasma flows in active regions. These measurements will permit, for the first time, accurate assessments of the coronal free energy available for driving CMEs and flares. The details of photospheric plasma flows, particularly along magnetic neutral-lines, are critical to testing models for initiating coronal mass ejections (CMEs) and flares. Assimilating flows and fields into state-of-the art 3D MHD simulations that model the highly stratified solar atmosphere from the convection zone to the corona represents the next step towards achieving NASA's Living with a Star forecasting goals of predicting "when a solar eruption leading to a CME will occur." Our presentation will describe these major science and predictive advances that will be delivered by SDO/HMI.

Schuck, Peter W.↗

Chemical Reaction and Flow Modeling in Fullerene and Nanotube Production

The development of processes to produce fullerenes and carbon nanotubes has largely been empirical. Fullerenes were first discovered in the soot produced by laser ablation of graphite [1]and then in the soot of electric arc evaporated carbon. Techniques and conditions for producing larger and larger quantities of fullerenes depended mainly on trial and error empirical variations of these processes, with attempts to scale them up by using larger electrodes and targets and higher power. Various concepts of how fullerenes and carbon nanotubes were formed were put forth, but very little was done based on chemical kinetics of the reactions. This was mainly due to the complex mixture of species and complex nature of conditions in the reactors. Temperatures in the reactors varied from several thousand degrees Kelvin down to near room temperature. There are hundreds of species possible, ranging from atomic carbon to large clusters of carbonaceous soot, and metallic catalyst atoms to metal clusters, to complexes of metals and carbon. Most of the chemical kinetics of the reactions and the thermodynamic properties of clusters and complexes have only been approximated. In addition, flow conditions in the reactors are transient or unsteady, and three dimensional, with steep spatial gradients of temperature and species concentrations. All these factors make computational simulations of reactors very complex and challenging. This article addresses the development of the chemical reaction involved in fullerene production and extends this to production of carbon nanotubes by the laser ablation/oven process and by the electric arc evaporation process. In addition, the high-pressure carbon monoxide (HiPco) process is discussed. The article is in several parts. The first one addresses the thermochemical aspects of modeling; and considers the development of chemical rate equations, estimates of reaction rates, and thermodynamic properties where they are available. The second part addresses modeling of the arc process for fullerene and carbon nanotube production using O-D, 1-D and 2-D fluid flow models. The third part addresses simulations of the pulsed laser ablation process using time-dependent techniques in 2-D, and a steady state 2-D simulation of a continuous laser ablation process. The fourth part addresses steady state modeling in O-D and 2-D of the HiPco process. In each of the simulations, there is a variety of simplifications that are made that enable one to concentrate on one aspect or another of the process. There are simplifications that can be made to the chemical reaction models , e.g. reduction in number of species by lumping some of them together in a representative species. Other simulations are carried out by eliminating the chemistry altogether in order to concentrate on the fluid dynamics. When solving problems with a large number of species in more than one spatial dimension, it is almost imperative that the problem be decoupled by solving for the fluid dynamics to find the fluid motion and temperature history of "particles" of fluid moving through a reactor. Then one can solve the chemical rate equations with complex chemistry following the temperature and pressure history. One difficulty is that often mixing with an ambient gas is involved. Therefore, one needs to take dilution and mixing into account. This changes the ratio of carbon species to background gas. Commercially available codes may have no provision for including dilution as part of the input. One must the write special solvers for including dilution in decoupled problems. The article addresses both ful1erene production and single-walled carbon nanotube (SWNT) production. There are at least two schemes or concepts of SWNT growth. This article will only address growth in the gas phase by carbon and catalyst cluster growth and SW T formation by the addition of carbon. There are other models that conceive of SWNT growth as a phase separation process from clusters me up carbon and metal catalyst, with the carbon precipitating from the cluster as it cools. We will not deal with that concept in this article. Further research is needed to determine the rates at which these composite clusters form, evaporate, and segregate.

Scott, Carl D.↗

Understanding Solar Eruptions with SDO/HMI Measuring Photospheric Flows, Testing Models, and Steps Towards Forecasting Solar Eruptions

The imminent launch of Solar Dynamics Observatory (SDO) will carry the first full-disk imaging vector magnetograph, the Helioseismic and Magnetic Imager (HMI), into an inclined geosynchronous orbit. This magnetograph will provide nearly continuous measurements of photospheric vector magnetic fields at cadences of 90 seconds to 12 minutes with I" resolution, precise pointing, and unfettered by atmospheric seeing. The enormous data stream of ~1.5 Terabytes per day from SDO will provide an unprecedented opportunity to understand the mysteries of solar eruptions. These ground-breaking observations will permit the application of a new technique, the differential affine velocity estimator for vector magnetograms (DAVE4VM), to measure photospheric plasma flows in active regions. These measurements will permit, for the first time, accurate assessments of the coronal free energy available for driving CMEs and flares. The details of photospheric plasma flows, particularly along magnetic neutral-lines, are critical to testing models for initiating coronal mass ejections (CMEs) and flares. Assimilating flows and fields into state-of-the art 3D MHD simulations that model the highly stratified solar atmosphere from the convection zone to the corona represents the next step towards achieving NASA's Living with a Star forecasting goals of predicting "when a solar eruption leading to a CME will occur." This talk will describe these major science and predictive advances that will be delivered by SDO /HMI.

Schuck, Peter W.↗

NASA's High-Resolution GEOS Forecasting and Reanalysis Products: A Unified Tool from Local to Global Scales

NASA's GMAO produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric chemical composition at unprecedented horizontal resolution of 0.25 degrees (~25 km), freely available to the public. This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). GEOS-CF also assimilated satellite observations into the system for improved representation of weather and smoke. The assimilation system is currently being expanded to include chemically reactive trace gases. While the main focus of this new product is on tropospheric air quality information, the GEOS-Chem chemistry model used in this system includes the unified tropospheric stratospheric chemistry mechanism for improved forecasts of total column ozone during anomalous dynamical and chemical events. I will discuss current capabilities of the GEOS Constituent Data Assimilation System (CoDAS) to improve atmospheric composition modeling and possible future directions for GEOS-CF and reanalysis products. In addition, I will show how machine learning techniques can be used to correct for sub-grid-scale variability, which further improves model estimates at a given observation site.

Co-DAS↗

Lithium-ion Battery Strain Gauge Monitoring and Depth of Discharge Estimation

Lithium-ion battery diagnostics and prognostics rely on measurements of electrical impedance, capacity, and voltage to infer the internal state of the battery. Mechanical changes to the cell structure represent an additional measure of the battery’s state because these changes are related to the overall battery health. As lithium-ion batteries are charged and discharged, lithium ions are inserted or removed from the anode and cathode, a process called intercalation and de-intercalation. As lithium ions intercalate and de-intercalate, they can cause changes to the lattice of the electrode particles, resulting in volumetric changes. These volumetric changes cause mechanical stresses and strains on the lithium-ion battery electrodes, and subsequently, the whole cell’s thickness varies as it is charged and discharged. This paper presents a study on the use of surface-mounted strain gauges for in-situ measurement of structural changes to lithium-ion batteries, along with a characterization of the unit-to-unit differences in strain response. A neural network modeling structure is then used to predict the battery’s depth of discharge under dynamic discharge conditions.

Lithium-ion batteries, depth of discharge, strain ↗