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At least 289 records · Page 16

Tectonics and evolution of the Juan Fernandez microplate at the Pacific-Nazca-Antarctic triple junction

Magnetic and bathymetric profiles derived from the R/V Endeavor survey and focal mechanism studies for earthquakes on two of the Juan Fernandez microplate boundaries are analyzed. It is observed that the Nazca-Juan Fernandez pole is in the northern end of the microplate since the magnetic lineation along the East Ridge of the microplate fans to the south. The calculation of the relative motion of the Juan Fernandez-Pacific-Nazca-Antarctic four-plate system using the algorithm of Minster et al. (1974) is described. The development of tectonic and evolutionary models of the region is examined. The tectonic model reveals that the northern boundary of the Juan Fernandez microplate is a zone of compression and that the West Ridge and southwestern boundary are spreading obliquely; the evolutionary model relates the formation of the Juan Fernandez microplate to differential spreading rates at the triple junction.

Anderson-Fontana, S.↗

SOL width broadening by spreading of pedestal turbulence

The pedestal turbulence intensity required to convert the thin, laminar H-mode scrape-off layer (SOL) to a broad turbulent SOL is calculated using the theory of turbulence spreading. A lower bound on the pedestal turbulence level to exceed the neoclassical heuristic drift (HD) width is derived. A reduced model of SOL turbulence spreading is used to determine the SOL width as a function of intensity flux from the pedestal to the SOL. The cross-over value for exceeding the HD model width is then calculated. We determine the pedestal turbulence levels—and the critical scalings thereof—required to achieve this level of broadening. Both drift wave and ballooning mode turbulence are considered. Here, a sensitivity analysis reveals that the key competition is that between spreading and linear E × B shear damping. The required pedestal turbulence levels scale with ρ/R.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Characterization of Partially Observed Epidemics - Application to COVID-19

This report documents a statistical method for the "real-time" characterization of partially observed epidemics. Observations consist of daily counts of symptomatic patients, diagnosed with the disease. Characterization, in this context, refers to estimation of epidemiological parameters that can be used to provide short-term forecasts of the ongoing epidemic, as well as to provide gross information for the time-dependent infection rate. The characterization problem is formulated as a Bayesian inverse problem, and is predicated on a model for the distribution of the incubation period. The model parameters are estimated as distributions using a Markov Chain Monte Carlo (MCMC) method, thus quantifying the uncertainty in the estimates. The method is applied to the COVID-19 pandemic of 2020, using data at the country, provincial (e.g., states) and regional (e.g. county) levels. The epidemiological model includes a stochastic component due to uncertainties in the incubation period. This model-form uncertainty is accommodated by a pseudo-marginal Metropolis-Hastings MCMC sampler, which produces posterior distributions that reflect this uncertainty. We approximate the discrepancy between the data and the epidemiological model using Gaussian and negative binomial error models; the latter was motivated by the over-dispersed count data. For small daily counts we find the performance of the calibrated models to be similar for the two error models. For large daily counts the negative-binomial approximation is numerically unstable unlike the Gaussian error model. Application of the model at the country level (for the United States, Germany, Italy, etc.) generally provided accurate forecasts, as the data consisted of large counts which suppressed the day-to-day variations in the observations. Further, the bulk of the data is sourced over the duration before the relaxation of the curbs on population mixing, and is not confounded by any discernible country-wide second wave of infections. At the state-level, where reporting was poor or which evinced few infections (e.g., New Mexico), the variance in the data posed some, though not insurmountable, difficulties, and forecasts were able to capture the data with large uncertainty bounds. The method was found to be sufficiently sensitive to discern the flattening of the infection and epidemic curve due to shelter-in-place orders after around 90% quantile for the incubation distribution (about 10 days for COVID-19). The proposed model was also used at a regional level to compare the forecasts for the central and north-west regions of New Mexico. Modeling the data for these regions illustrated different disease spread dynamics captured by the model. While in the central region the daily counts peaked in the late April, in the north-west region the ramp-up continued for approximately three more weeks.

59 BASIC BIOLOGICAL SCIENCES↗

Hierarchical effects facilitate spreading processes on synthetic and empirical multilayer networks

In this paper we consider the effects of corporate hierarchies on innovation spread across multilayer networks, modeled by an elaborated SIR framework. We show that the addition of management layers can significantly improve spreading processes on both random geometric graphs and empirical corporate networks. Additionally, we show that utilizing a more centralized working relationship network rather than a strict administrative network further increases overall innovation reach. In fact, this more centralized structure in conjunction with management layers is essential to both reaching a plurality of nodes and creating a stable adopted community in the long time horizon. Further, we show that the selection of seed nodes affects the final stability of the adopted community, and while the most influential nodes often produce the highest peak adoption, this is not always the case. In some circumstances, seeding nodes near but not in the highest positions in the graph produces larger peak adoption and more stable long-time adoption.

97 MATHEMATICS AND COMPUTING↗

On the control of electron heating for optimal laser radiation pressure ion acceleration

We study the onset of electron heating in intense laser–solid interactions and its impact on the spectral quality of radiation pressure accelerated ions in both hole boring and light sail regimes. Two- and three-dimensional particle-in-cell (PIC) simulations are performed over a wide range of laser and target parameters and reveal how the pulse duration, profile, polarization and target surface stability control the electron heating, the dominant ion acceleration mechanisms and the ion spectra. We find that the onset of strong electron heating is associated with the growth of the Rayleigh–Taylor-like instability at the front surface and must be controlled to produce high-quality ion beams, even when circularly polarized lasers are employed. We define a threshold condition for the maximum duration of the laser pulse that allows mitigation of electron heating and radiation pressure acceleration of narrow energy spread ion beams. The model is validated by three-dimensional PIC simulations, and the few experimental studies that reported low energy spread radiation pressure accelerated ion beams appear to meet the derived criteria. The understanding provided by our work will be important in guiding future experimental developments, for example for the ultrashort laser pulses becoming available at state-of-the-art laser facilities, for which we predict that proton beams with $\sim$ 150–250 MeV, $\sim$ 30% energy spread, and a total laser-to-proton conversion efficiency of $\sim$ 20% can be produced.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

MAPS of Cancer

Our goal was to produce an interactive visualization from a mathematical model that successfully predicts metastases from head and neck cancer. We met this goal early in the project. The visualization is available for the public to view. Our work appears to fill a need for more information about this deadly disease. The idea of this project was to make an easily interpretable visualization based on what we call "functional maps" of disease. A functional map is a graphic summary of medical data, where distances between parts of the body are determined by the probability of disease, not by anatomical distances. Functional maps often beat little resemblance to anatomical maps, but they can be used to predict the spread of disease. The idea of modeling the spread of disease in an abstract multidimensional space is difficult for many people. Our goal was to make the important predictions easy to see. NASA must face this problem frequently: how to help laypersons and professionals see important trends in abstract, complex data. We took advantage of concepts perfected in NASA's graphics libraries. As an analogy, consider a functional map of early America. Suppose we choose travel times, rather than miles, as our measures of inter-city distances. For Abraham Lincoln, travel times would have been the more meaningful measure of separation between cities. In such a map New Orleans would be close to Memphis because of the Mississippi River. St. Louis would be close to Portland because of the Oregon Trail. Oklahoma City would be far from Little Rock because of the Cheyenne. Such a map would look puzzling to those of us who have always seen physical maps, but the functional map would be more useful in predicting the probabilities of inter-site transit. Continuing the analogy, we could predict the spread of social diseases such as gambling along the rivers and cattle rustling along the trails. We could simply print the functional map of America, but it would be more interesting to show meaningful patterns of dispersal. We had previously published the functional map of the head and neck, but it was difficult to explain to either patients or surgeons because that view of our body did not resemble anatomy. This discrepancy between functional and physical maps is just a mathematical restatement of the well-known fact that some diseases, such as head and neck cancer, spread in complex patterns, not always to the next nearest site. We had discovered that a computer could re-arrange anatomy so that this particular disease spreads to the next nearest site. The functional map explains over 95% of the metastases in 1400 patients. In a sense, we had graphed what our body "looks like" to a tumor. The tumor readily travels between adjacent areas in the functional map. The functional map is a succinct visual display of trends that are not easily appreciated in tables of probabilities.

Gray, Lincoln↗

Predictions of the structure of turbulent, particle-laden, round jets

Models of gas and particle motion in turbulent, particle-laden, round jets were evaluated using existing measurements of flow structure. Three models were considered: (1) a locally homogeneous flow model, where velocities and turbulent mixing properties of both phases were assumed to be equal; (2) a deterministic separated flow model, where interphase slip was considered but effects of turbulent dispersion were ignored; and (3) a stochastic separated flow model where effects of interphase slip and turbulent dispersion were considered using random sampling techniques. In all three cases, mean and turbulent properties of the continuous phase were found with a well-calibrated k-epsilon model. The locally homogeneous flow and deterministic separated flow models over- and underestimated particle spread and flow development rates, respectively. The stochastic separated flow model, however, yielded satisfactory predictions of flow structure - except at high particle loadings. Uncertainties in initial conditions for the measurements and possible effects of turbulence modulation by the particles are proposed as the reason for these errors.

Shuen, J.-S.↗

Results of the second Ice Shelf–Ocean Model Intercomparison Project (ISOMIP+)

Ocean-driven basal melting of Antarctic ice shelves plays an important role in the mass loss of the Antarctic Ice Sheet. Ice shelf cavity-resolving ocean models are a valuable tool for understanding ice shelf-ocean interactions and for simulating projections of ice shelf and ocean states under future climate. Designed to assess the current state of ice shelf–ocean modelling, the second Ice Shelf–Ocean Model Intercomparison Project, ISOMIP+, consists of 12 ocean model configurations submitted with a common, idealised experimental setup. Here, we focus on the experiments Ocean0–2 (Asay-Davis et al., 2016), which are ocean models with idealised, static ice shelf geometries, but where the ocean reaches a balance with prescribed far-field ocean conditions. Different thermal transfer coefficient values (ranging from 0.011 to 0.2) are used for each model in the melting parameterisation to achieve a common, tuned melt rate since the models cover a range of types of vertical coordinates, ice–ocean boundary layer treatments, and numerical schemes. These model differences lead to spread in the resultant ocean properties, circulation, boundary-layer structure and spatial distribution of melting. We also highlight similarities between models, such as a shared linear relationship across most models between melt rate and overturning and barotropic streamfunctions during the spin-up and spin-down, demonstrating a robust relationship between melt and circulation across models and forcing conditions. The ISOMIP+ results provide a systematic comparison of ice shelf cavity-capable ocean models. However, we also demonstrate the need for realistic ice shelf–ocean model intercomparison projects (some already underway) to assess model biases and inter-model variation against sparse observations. Further research is needed to understand the differences between models and further improve our modelled representations of the ice–ocean boundary layer and ice shelf cavity circulation.

54 ENVIRONMENTAL SCIENCES↗

Modeling the Observed QBO and Inter-Annual Variations of the Diurnal Tide in the Mesosphere

In the current version of the Numerical Spectral Model (NSM), the Quasi-biennial Oscillation (QBO) is generated primarily by small-scale gravity waves (GW) from Hines' Doppler Spread Parameterization (DSP). The model does not have topography, and the planetary waves are solely generated by instabilities. We discuss a 3D modeling study that describes the QBO extending from the stratosphere into the upper mesosphere, where the oscillation produces significant inter-annual variations in the diurnal tide. The numerical results are compared with temperature measurements from the SABER (TIMED) and MLS (UARS) instruments obtained by Huang et al. (2006). With a GW source that peaks at the Equator and is taken to be isotropic and independent of season, the NSM generates a QBO with variable periods around 26 months and zonal wind amplitudes of almost 25 m/s at 30 km. As reported earlier, the NSM reproduces the observed equinoctial maxima in the diurnal tide at altitudes around 95 km. The modeled QBO modulates the tide such that the seasonal amplitude maxima can vary from one year to another by as much as 30%. To shed light on the underlying mechanisms, the relative importance of the advection terms are discussed, and they are shown to be important in the stratosphere. At altitudes above 80 km, however, the QBO-related inter-annual variations of the tide are generated primarily by GW momentum deposition. In qualitative agreement with the SABER measurements, the model generates distinct zonal-mean QBO temperature variations in the stratosphere and mesosphere. In the stratosphere, the computed amplitudes are not much smaller than those observed, and the rate of downward propagation at the Equator is reproduced. The modeled temperature amplitudes in the mesosphere, however, are much smaller than those observed. The observed and computed temperature variations of the QBO peak at the Equator but extend with phase reversals to high latitudes, in contrast to the zonal winds that are confined to equatorial latitudes. Hemispherical asymmetries also appear in both the model results and the observations. The temperature amplitudes outside the equatorial region however tend to occur at lower latitudes in the model results. While there is qualitative agreement between the TIMED measurements and the model prediction, there are some areas of significant disagreement that require us to reexamine the present version of the NSM. The numerical results critically depend on the chosen parameters that determine the wave forcing, and there are a number of avenues to improve the performance of the model that had not been tuned to fit the observations. The GW spectrum and its latitude dependence in the troposphere are not well known, and numerical experiments are discussed that describe the related model response. While it appears that eastward propagating Kelvin waves and westward propagating Rossby gravity waves are not the primary source to generate the QBO, the GW forcing can seed the oscillation and act as a catalyst to enhance effectiveness of these planetary waves.

Mayr, Hans G.↗

Examining the Relationships Between Education, Social Networks and Democratic Support With ABM

This paper introduces an agent-based model that explores the relationships between education, social networks, and support for democratic ideals. This study examines two factors thai affect democratic support, education, and social networks. Current theory concerning these two variables suggests that positive relationships exist between education and democratic support and between social networks and the spread of ideas. The model contains multiple variables of democratic support, two of which are evaluated through experimentation. The model allows individual entities within the system to make "decisions" about their democratic support independent of one another. The agent based approach also allows entities to utilize their social networks to spread ideas. Current theory supports experimentation results. In add~ion , these results show the model is capable of reproducing real world outcomes. This paper addresses the model creation process and the experimentation procedure, as well as future research avenues and potential shortcomings of the model

Drucker, Nick↗

Animal movement estimation and network-based epidemic modeling: Illustration for the swine industry in Iowa (US)

Animal movement plays a critical role in disease transmission between farms. However, in the United States, the lack of available animal shipment data, sometimes coupled with a lack of detailed information about farm demographics and characteristics, presents great challenges for epidemic modeling and prediction. In this study, we proposed a new method based on the maximum entropy to generate “synthetic” animal movement networks, considering available statistics about the premises operation type, operation size, and the distance between premises. We illustrated our method for the swine movement networks in Iowa and performed network analyses to gain insights into the swine industry. We then applied the generated networks to a network-based epidemic model to identify potential system vulnerabilities in terms of disease transmission. The model was parameterized for African Swine Fever (ASF) as the US swine industry is quite concerned about this disease. Results show that premises with a central role in the network are more vulnerable to disease outbreaks and play an important role in disease spread. Simulations with outbreaks starting from random farms reveal no significant large outbreaks, indicating the system’s relative robustness against arbitrary disease introductions. However, outbreaks originating from high out-degree farms can lead to large epidemic sizes. This underscores the importance for stakeholders and policymakers to continue improving animal movement records and traceability programs in the US and the value of making that data available to epidemiologists and modelers to better understand risk and inform strategies aimed to cost-effectively prevent and control disease transmission. Our approach could be easily adapted to estimate movement networks in other animal production systems and to inform disease spread models for various infectious diseases.

60 APPLIED LIFE SCIENCES↗

Hydrogen station in situ back-to-back fueling data for design and modeling

Hydrogen technologies are rapidly spreading, with significant attention to the mobility sector requiring a robust and widespread fueling infrastructure. Hydrogen stations are indeed fundamental to transitioning from pilot projects towards large-scale implementation in many countries. Operating under extreme conditions, the new stations need more informed designs and equipment to meet the growing demand and their more frequent utilization. Via a set of experimental research activities and investigated scenarios carried out at the Cal State LA Hydrogen Research and Fueling Facility, here this paper shares a novel and comprehensive set of data collected over a period of one year on fueling events frequency and refueling process station behaviors. A performance evaluation of the station is presented under different load scenarios in severe conditions during "back-to-back fuelings", with monitoring of fundamental parameters for infrastructure sizing, including dynamic cooling response, pressure levels, thermodynamics, and the state of charge of the vehicle. The presented data analysis could surely contribute as closer-to-reality inputs for a variety of station performance modeling tools.

08 HYDROGEN↗

Probabilistic Resilience-Oriented Assessment Approach for Transmission Networks Under Wildfires

The rising threat of wildfires poses significant challenges to power transmission networks, particularly in areas prone to such disasters. Traditional approaches for wildfire risk assessment neglect some potential wildfire scenarios. Here, this paper introduces a probabilistic resilience-oriented assessment approach for power transmission networks to address this gap. Initially, a probabilistic wildfire model is developed to capture uncertainties in ignition, intensity, and fire spread. Next, a spatiotemporal fragility model is constructed to assess the impact of wildfires on transmission corridors, incorporating Thermal Aging (TA) and Dynamic Thermal Rate (DTR) change. Finally, a comprehensive resilience metric is defined to evaluate system performance, leveraging the fragility model to determine component and system-level resilience. The approach employs a combinatorial enumeration method to generate potential wildfire scenarios, enhanced by an impact-increment-based state enumeration (IISE) method for computational efficiency. The proposed method provides critical insights for identifying system vulnerabilities and developing robust strategies to protect transmission networks from wildfires. The efficacy of this approach is validated through extensive scenarios of the RTS-GMLC system across Southern California, Nevada and Arizona.

Vahedi, Soroush [Univ. of Connecticut, Storrs, CT ↗

Analysis of turbulent underexpanded jets. II - Shock noise features using SCIPVIS

SCIPVIS, the computational model discussed by Dash et al. (1985), is assessed in predicting the complicated flow structure associated with shock-containing plumes. In addition, the analysis in this study examines this code's applicability as a basic part of a program for estimating broadband shock noise radiation. The results of this study show that excellent agreement exists between predicted and measured static pressure distributions for both underexpanded and overexpanded flow cases considered. Of the three turbulence closure models incorporated in the SCIPVIS code, the kW model of Spalding produces the most uniform agreement with measurement. The k-epsilon-2 model of Launder consistently overestimates plume spreading for supersonic jets with exit Mach numbers in the 1-2 range. Dash's (1983) k-epsilon-2-cc, compressibility-corrected version of Launder's model underestimates plume spreading. Good qualitative agreement was also obtained between the measured longitudinal turbulence intensity and that predicted by the code for the same trial case. Comparison of measured and predicted broadband shock noise spectrum peak values were found to be in excellent agreement. This utilized a variant of the Harper-Bourne and Fisher (1973) phase-array model: the effective shock spacing was reinterpreted as the value of the end of the plume potential core, determined herein by the SCIPVIS code.

Seiner, J. M.↗

A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems

Abstract. Two-way coupling between the stratosphere and troposphere is recognized as an important source of subseasonal-to-seasonal (S2S) predictability and can open windows of opportunity for improved forecasts. Model biases can, however, lead to a poor representation of such coupling processes; drifts in a model's circulation related to model biases, resolution, and parameterizations have the potential to feed back on the circulation and affect stratosphere–troposphere coupling. We introduce a set of diagnostics using readily available data that can be used to reveal these biases and then apply these diagnostics to 22 S2S forecast systems. In the Northern Hemisphere, nearly all S2S forecast systems underestimate the strength of the observed upward coupling from the troposphere to the stratosphere, downward coupling within the stratosphere, and the persistence of lower-stratospheric temperature anomalies. While downward coupling from the lower stratosphere to the near surface is well represented in the multi-model ensemble mean, there is substantial intermodel spread likely related to how well each model represents tropospheric stationary waves. In the Southern Hemisphere, the stratospheric vortex is oversensitive to upward-propagating wave flux in the forecast systems. Forecast systems generally overestimate the strength of downward coupling from the lower stratosphere to the troposphere, even as most underestimate the radiative persistence in the lower stratosphere. In both hemispheres, models with higher lids and a better representation of tropospheric quasi-stationary waves generally perform better at simulating these coupling processes.

Garfinkel, Chaim I. (ORCID:000000017258666X)↗

Investigation of potential aerosol transmission and infectivity of SARS-CoV-2 through central ventilation systems

Here we evaluate the concentrations and probabilities of infection for both building interior and exterior exposure sources using a well-mixed model in a connected multizone building. As a central hub of many community and economic activities, buildings provide social connectivity, but the COVID-19 pandemic has reduced social connectivity due to concerns of viral spread within buildings. Although single zone models of infectious spread are well studied, the impact of aerosolized spread of SARS-CoV-2 via air handling systems in multizone buildings remains unexplored. Here we evaluate the influence of filtration, air exchange rates, and the fraction of outdoor air on the probability of infection using the well-known well-mixed modeling approach for a multizone. We find filtration lowers the concentration and probability of infection in both source and connected rooms provided at least some air is recirculated, but that probability is not zero. Filtration has no influence without recirculation or unless the outdoor air contains virus. We find that increasing the air exchange rate removes virus from the source room faster but also increases the rate of exposure to connected rooms. Therefore, slower air exchange rates reduce infectivity in connected rooms at shorter durations, but higher air exchange rates reduce infectivity at longer durations. We further find that when outdoor air is virus free, increasing the fraction of outdoor air is helpful, but, when outdoor air is infective, pathogen exposure inside can persist for hours after a short-term release.

60 APPLIED LIFE SCIENCES↗

On the prediction of free turbulent jets with swirl using a quadratic pressure-strain model

Data from free turbulent jets both with and without swirl are used to assess the performance of the pressure-strain model of Speziale, Sarkar and Gatski which is quadratic in the Reynolds stresses. Comparative predictions are also obtained with the two versions of the Launder, Reece and Rodi model which are linear in the same terms. All models are used as part of a complete second-order closure based on the solution of differential transport equations for each non-zero component of the Reynolds stress tensor together with an equation for the scalar energy dissipation rate. For non-swirling jets, the quadratic model underestimates the measured spreading rate of the plane jet but yields a better prediction for the axisymmetric case without resolving the plane jet/round jet anomaly. For the swirling axisymmetric jet, the same model accurately reproduces the effects of swirl on both the mean flow and the turbulence structure in sharp contrast with the linear models which yield results that are in serious error. The reasons for these differences are discussed.

Younis, Bassam A.↗

The Rapidly Fading Afterglow of GRB 980519

GRB 980519 had the most rapidly fading of the well-documented GRB afterglows, consistent with t(sup -2.05 +/- 0.04) in BVRI as well as in X-rays during the two days in which observations were made. We report VRI observations from the MDM 1.3m and WIYN 3.5m telescopes, and we synthesize an optical spectrum from all of the available photometry. The optical spectrum alone is well fitted by a power law of the form nu(sup - 1.20 +/- 0.25), with some of the uncertainty due to the significant Galactic reddening in this direction. The optical and X-ray spectra together are adequately fitted by a single power law nu(sup 1.05 +/- 0.10). This combination of steep temporal decay and flat broad-band spectrum places a severe strain on the simplest afterglow models involving spherical blast waves in a homogeneous medium. Instead, the rapid observed temporal decay is more consistent with 2 models of expansion into a medium of density n(r) proportional to r(sup -2), or with predictions of the evolution of a jet after it slows down and spreads laterally. The jet model would relax the energy requirements on some of the more extreme GRBs, of which GRB 980519 is likely to be an example because of its large gamma-ray fluence and faint host galaxy.

Halpern, Jules P.↗