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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

The Post-pericenter Evolution of the Galactic Center Source G2

In early 2014, the fast-moving near-infrared source G2 reached its closest approach to the supermassive black hole Sgr A* in the Galactic center. We report on the evolution of the ionized gaseous component and the dusty component of G2 immediately after this event, revealed by new observations obtained in 2015 and 2016 with the SINFONI integral field spectrograph and the NACO imager at the ESO VLT. The spatially resolved dynamics of the Brγ line emission can be accounted for by the ballistic motion and tidal shearing of a test-particle cloud that has followed a highly eccentric Keplerian orbit around the black hole for the last 12 years. The non-detection of a drag force or any strong hydrodynamic interaction with the hot gas in the inner accretion zone limits the ambient density to less than a few 10{sup 3} cm{sup −3} at the distance of closest approach (1500 R{sub s}), assuming G2 is a spherical cloud moving through a stationary and homogeneous atmosphere. The dust continuum emission is unresolved in L′-band, but stays consistent with the location of the Brγ emission. The total luminosity of the Brγ and L′ emission has remained constant to within the measurement uncertainty. The nature and origin of G2 are likely related to that of the precursor source G1, since their orbital evolution is similar, though not identical. Both objects are also likely related to a trailing tail structure, which is continuously connected to G2 over a large range in position and radial velocity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Phase transformations at interfaces: Observations from atomistic modeling

Here, we review the recent progress in theoretical understanding and atomistic computer simulations of phase transformations in materials interfaces, focusing on grain boundaries (GBs) in metallic systems. Recently developed simulation approaches enable the search and structural characterization of GB phases in single-component metals and binary alloys, calculation of thermodynamic properties of individual GB phases, and modeling of the effect of the GB phase transformations on GB kinetics. Atomistic simulations demonstrate that the GB transformations can be induced by varying the temperature, loading the GB with point defects, or varying the amount of solute segregation. The atomic-level understanding obtained from such simulations can provide input for further development of thermodynamics theories and continuous models of interface phase transformations while simultaneously serving as a testing ground for validation of theories and models. They can also help interpret and guide experimental work in this field.

36 MATERIALS SCIENCE↗
DOE OSTI2019

The dynamic and thermodynamic structure of the monsoon over southern India: New observations from the INCOMPASS IOP

Some of the highest summer monsoon rainfall in South Asia falls on the windward slopes of the Western Ghats mountains on India's west coast and offshore over the eastern Arabian Sea. Understanding of the processes determining the spatial distribution and temporal variability of this region remains incomplete. In this paper, new Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) aircraft and ground‐based measurements of the summer monsoon over the Western Ghats and upstream of them are presented and placed within the context of remote‐sensing observations and reanalysis. The transition from widespread rainfall over the eastern Arabian Sea to rainfall over the Western Ghats is documented in high spatial and temporal resolution. Heavy rainfall offshore during the campaign was associated primarily with mid‐tropospheric humidity, secondarily with sea surface temperature, and only weakly with orographic blocking. A mid‐tropospheric dry intrusion suppressed deep convection offshore in the latter half of the campaign, allowing the build‐up of low‐level humidity in the onshore flow and enhancing rainfall over the mountains. Rainfall on the lee side of the Western Ghats occurred during the latter half of the campaign in association with enhanced mesoscale easterly upslope flow. Diurnal cycles in rainfall offshore (maximum in the morning) and on the mountains (maximum in the afternoon) were observed. Considerable zonal and temporal variability was seen in the offshore boundary layer, suggesting the presence of convective downdraughts and cold pools. Persistent drying of the subcloud mixed layer several hundred kilometres off the coast was observed, suggesting strong mixing between the boundary layer and the free troposphere. These observations provide quantitative targets to test models and suggest hypotheses on the physical mechanisms determining the distribution and variability in rainfall in the Western Ghats region.

Fletcher, Jennifer K.↗
DOE OSTI2020

Spatiotemporally dynamic implicit large eddy simulation using machine learning classifiers

In this article, we utilize machine learning to dynamically determine if a point on the computational grid requires implicit numerical dissipation for large eddy simulation (LES). The decision making process is learnt through a priori training on quantities derived from direct numerical simulation (DNS) data. In particular, we compute eddy-viscosities obtained through the coarse-graining of DNS quantities and utilize their projection onto a Gaussian distribution to categorize areas that may require dissipation. If our learning determines that closure is necessary, an upwinded scheme is utilized for computing the non-linear Jacobian. In contrast, if it is determined that closure is unnecessary, a symmetric and second-order accurate energy and enstrophy preserving Arakawa scheme is utilized instead. This results in a closure framework that precludes the specification of any model-form for the small scale contributions of turbulence but deploys an appropriate numerical dissipation from explicit closure driven hypotheses. Here, this methodology is deployed for the Kraichnan turbulence test-case and assessed through various statistical quantities such as angle-averaged kinetic energy spectra and vorticity structure functions. Our framework thus establishes a link between the use of explicit LES ideologies for closure and numerical dissipation-based modeling of turbulence leading to improved statistical fidelity of a posteriori simulations.

42 ENGINEERING↗
DOE OSTI2020

Exploring Hydrologic Model Process Connectivity at the Continental Scale Through an Information Theory Approach

Exploring water fluxes between hydrological model (HM) components is essential to assess and improve model realism. Many classical metrics for HM diagnosis rely solely on streamflow and hence provide limited insights into model performance across processes. This study applies an information theory measure known as “transfer entropy” (TE) to systematically quantify the transfer of information among major HM components. To test and demonstrate the benefits of TE, we use the Framework for Understanding Structural Errors (FUSE) model to mimic and compare four commonly used HM structures, VIC, PRMS, SACRAMENTO, and TOPMODEL, across 671 catchments spanning a variety of hydrologic regimes in the conterminous United States. We explore connections between HM components and catchment landscape characteristics (e.g., climate, topography, soil, and vegetation) and characterize their nonlinear associations using distance correlation and Spearman correlation coefficients. Our results indicate that while the information transferred from precipitation to runoff is similar across model structures (likely as a result of calibration), the information transferred among other components can vary significantly from a FUSE structure to another. We find that aridity, precipitation duration and frequency, snow fraction, mean elevation, forest area, and leaf area index are often significantly associated with TE between the main HM components. Here, we propose that the presence of meaningful nonlinear associations can be used to diagnose process representation in HMs. Our results highlight the necessity to enhance the conventional streamflow-only calibration approach for a more realistic representation of water dynamics in the models.

large-sample hydrology↗
DOE OSTI2024

Dynamic operation of metal-supported solid oxide electrolysis cells

Symmetric-structure metal-supported solid oxide fuel cells and electrolysis cells (MS-SOFCs, MS-SOECs) offer several advantages over conventional solid oxide cells, including the use of inexpensive materials, high mechanical strength, and rapid ramp-up ability. Aggressive operation of MS-SOCs in fuel cell mode is well-established, including extremely fast start-up, redox tolerance, and imbalanced pressure. Here, we extend dynamic operation to MS-SOCs in SOEC mode with high steam content for both small button cells and a large rectangular cell, including: steam cycling, thermal cycling, redox cycling and power cycling. Steam cycling entailed switching between 3:97 and 50:50 steam:hydrogen ratio. For thermal cycling, the temperature was rapidly varied between 150°C and 700°C for 50 cycles. Redox cycling involved switching the steam side gas between 50 % humidified H 2 and 50 % humidified N 2 for 5 cycles. Power cycling was performed by operating the cell under variable current density, resulting in cell voltage between 1.3V and 2.8V. Degradation rates for each testing strategy were compared to a baseline cell, and found to be similar. In conclusion, the excellent tolerance to dynamic operation increases confidence that MS-SOECs will be compatible with dynamic or intermittent renewable resources.

08 HYDROGEN↗
DOE OSTI2016

Perturbation theory, effective field theory, and oscillations in the power spectrum

We explore the relationship between the nonlinear matter power spectrum and the various Lagrangian and Standard Perturbation Theories (LPT and SPT). We first look at it in the context of one dimensional (1-d) dynamics, where 1LPT is exact at the perturbative level and one can exactly resum the SPT series into the 1LPT power spectrum. Shell crossings lead to non-perturbative effects, and the PT ignorance can be quantified in terms of their ratio, which is also the transfer function squared in the absence of stochasticity. At the order of PT we work, this parametrization is equivalent to the results of effective field theory (EFT), and can thus be expanded in terms of the same parameters. We find that its radius of convergence is larger than the SPT loop expansion. The same EFT parametrization applies to all SPT loop terms and if stochasticity can be ignored, to all N-point correlators. In 3-d, the LPT structure is considerably more complicated, and we find that LPT models with parametrization motivated by the EFT exhibit running with k and that SPT is generally a better choice. Since these transfer function expansions contain free parameters that change with cosmological model their usefulness for broadband power is unclear. For this reason we test the predictions of these models on baryonic acoustic oscillations (BAO) and other primordial oscillations, including string monodromy models, for which we ran a series of simulations with and without oscillations. Most models are successful in predicting oscillations beyond their corresponding PT versions, confirming the basic validity of the model. We show that if primordial oscillations are localized to a scale q, the wiggles in power spectrum are approximately suppressed as exp[−k{sup 2}Σ{sup 2}(q)/2], where Σ(q) is rms displacement of particles separated by q, which saturates on large scales, and decreases as q is reduced. No oscillatory features survive past k ∼ 0.5h/Mpc at z = 0.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

WOBBLING AND PRECESSING JETS FROM WARPED DISKS IN BINARY SYSTEMS

We present results of the first ever three-dimensional (3D) magnetohydrodynamic (MHD) simulations of the accretion–ejection structure. We investigate the 3D evolution of jets launched symmetrically from single stars but also jets from warped disks in binary systems. We have applied various model setups and tested them by simulating a stable and bipolar symmetric 3D structure from a single star–disk–jet system. Our reference simulation maintains a good axial symmetry and also a bipolar symmetry for more than 500 rotations of the inner disk, confirming the quality of our model setup. We have then implemented a 3D gravitational potential (Roche potential) due by a companion star and run a variety of simulations with different binary separations and mass ratios. These simulations show typical 3D deviations from axial symmetry, such as jet bending outside the Roche lobe or spiral arms forming in the accretion disk. In order to find indications of precession effects, we have also run an exemplary parameter setup, essentially governed by a small binary separation of only ≃200 inner disk radii. This simulation shows a strong indication that we observe the onset of a jet precession caused by the wobbling of the jet-launching disk. We estimate the opening angle of the precession cone defined by the lateral motion of the jet axis to be about 4° after about 5000 dynamical time steps.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Experimental Pressure Measurements on Hydropower Turbine Runners

The range of hydrodynamic operating conditions to which the turbine is exposed results in significant pressure fluctuations on both the pressure and suction sides of the blades. Understanding these dynamic pressures has a range of applications. Structurally, the resulting dynamic loads are significant in understanding the design life and maintenance schedule of the bearing, shafts and runner components. The pulsing pressures have also been seen to have a detrimental effect on the surface condition of the blades. Biologically, the pressure gradients and pressure extremes are the primary driver of barotrauma for fish passing through hydroturbines. Improvements in computational fluid dynamics (CFD) can be used to simulate such unsteady pressures in the regions of concern. High frequency model scale and prototype measurements of pressures at the blade are important in the validation of these models. Experimental characterization of pressure fields over hydroturbine blades has been demonstrated by a number of studies which using multiple pressure transducers to map the pressure contours on the runner blades. These have been performed at both model and prototype scales, often to validate computational models of the pressure and flow fields over the blades. This report provides a review of existing studies in which the blade pressure was measured in situ. The report assesses the technology for both model and prototype scale testing. The details of the primary studies in this field are reported and used to inform the types of hardware required for similar experiments based on the Ice Harbor Dam owned by the US Corps of Engineers on the Snake River, WA, USA. Such a study would be used to validate the CFD performed for the BioPA.

13 HYDRO ENERGY↗
DOE OSTI2020

X-Ray Afterglows from the Gamma-Ray Burst “Large-angle” Emission

In this work, we derive basic analytical results for the timing and decay of the gamma-ray burst (GRB) counterpart and delayed afterglow light curves for a brief emission episode from a relativistic surface endowed with angular structure, consisting of a uniform core of size ${\theta }_{c}$ (Lorentz factor ${{\rm{\Gamma }}}_{c}$ and surface emissivity ${i}_{\nu ^{\prime} }^{{\prime} }$ are angle independent) and an axially symmetric power-law envelope (${\rm{\Gamma }}\sim {\theta }^{-g}$). In this "large-angle emission" model, radiation produced during the prompt emission phase (GRB) at angles $\theta \gt {\theta }_{c}$ arrives at the observer well after the burst (delayed emission). The dynamical time range of the very fast decaying GRB "tail" and of the flat afterglow "plateau" and the morphology of the GRB counterpart/afterglow are all determined by two parameters: the core's parameter ${{\rm{\Gamma }}}_{c}{\theta }_{c}$ and the envelope's Lorentz factor index g, leading to three types of light curves that display three post-GRB phases (type 1: tail, plateau/slow decay, post-plateau/normal decay), two post-GRB phases (type 2: tail and fast decay), or just one (type 3: normal decay). We show how X-ray light-curve features can be used to determine core and envelope dynamical and spectral parameters. Testing of the large-angle emission model is done using the Swift/XRT X-ray emission of two afterglows of type 1 (GRB 060607A, GRB 061121), one of type 2 (GRB 061110A), and one of type 3 (GRB 061007). We find that the X-ray afterglows with plateaus require an envelope Lorentz factor ${\rm{\Gamma }}\sim {\theta }^{-2}$ and a comoving-frame emissivity ${i}_{\nu ^{\prime} }^{{\prime} }\sim {\theta }^{2}$; thus, for a typical afterglow spectrum ${F}_{\nu }\sim {\nu }^{-1}$, the lab-frame energy release is uniform over the emitting surface.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

KGML-ag: a modeling framework of knowledge-guided machine learning to simulate agroecosystems: a case study of estimating N<sub>2</sub>O emission using data from mesocosm experiments

Abstract. Agricultural nitrous oxide (N2O) emission accounts for a non-trivial fraction of global greenhouse gas (GHG) budget. To date, estimating N2O fluxes from cropland remains a challenging task because the related microbial processes (e.g., nitrification and denitrification) are controlled by complex interactions among climate, soil, plant and human activities. Existing approaches such as process-based (PB) models have well-known limitations due to insufficient representations of the processes or uncertainties of model parameters, and due to leverage recent advances in machine learning (ML) a new method is needed to unlock the “black box” to overcome its limitations such as low interpretability, out-of-sample failure and massive data demand. In this study, we developed a first-of-its-kind knowledge-guided machine learning model for agroecosystems (KGML-ag) by incorporating biogeophysical and chemical domain knowledge from an advanced PB model, ecosys, and tested it by comparing simulating daily N2O fluxes with real observed data from mesocosm experiments. The gated recurrent unit (GRU) was used as the basis to build the model structure. To optimize the model performance, we have investigated a range of ideas, including (1) using initial values of intermediate variables (IMVs) instead of time series as model input to reduce data demand; (2) building hierarchical structures to explicitly estimate IMVs for further N2O prediction; (3) using multi-task learning to balance the simultaneous training on multiple variables; and (4) pre-training with millions of synthetic data generated from ecosys and fine-tuning with mesocosm observations. Six other pure ML models were developed using the same mesocosm data to serve as the benchmark for the KGML-ag model. Results show that KGML-ag did an excellent job in reproducing the mesocosm N2O fluxes (overall r2=0.81, and RMSE=3.6 mgNm-2d-1 from cross validation). Importantly, KGML-ag always outperforms the PB model and ML models in predicting N2O fluxes, especially for complex temporal dynamics and emission peaks. Besides, KGML-ag goes beyond the pure ML models by providing more interpretable predictions as well as pinpointing desired new knowledge and data to further empower the current KGML-ag. We believe the KGML-ag development in this study will stimulate a new body of research on interpretable ML for biogeochemistry and other related geoscience processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Recent advances, and unresolved issues, in the application of computational modelling to the prediction of the biological effects of nanomaterials

Nanomaterials research is one of the fastest growing contemporary research areas. The unprecedented properties of these materials have meant that they are being incorporated into products very quickly. Regulatory agencies are concerned they cannot assess the potential hazards of these materials adequately, as data on the biological properties of nanomaterials are still relatively limited and expensive to acquire. Computational modelling methods have much to offer in helping understand the mechanisms by which toxicity may occur, and in predicting the likelihood of adverse biological impacts of materials not yet tested experimentally. This paper reviews the progress these methods, particularly those QSAR-based, have made in understanding and predicting potentially adverse biological effects of nanomaterials, and also the limitations and pitfalls of these methods. - Highlights: • Nanomaterials regulators need good information to make good decisions. • Nanomaterials and their interactions with biology are very complex. • Computational methods use existing data to predict properties of new nanomaterials. • Statistical, data driven modelling methods have been successfully applied to this task. • Much more must be learnt before robust toolkits will be widely usable by regulators.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Well-balanced treatment of gravity in astrophysical fluid dynamics simulations at low Mach numbers

We report accurate simulations of flows in stellar interiors are crucial to improving our understanding of stellar structure and evolution. Because the typically slow flows are merely tiny perturbations on top of a close balance between gravity and the pressure gradient, such simulations place heavy demands on numerical hydrodynamics schemes. We demonstrate how discretization errors on grids of reasonable size can lead to spurious flows orders of magnitude faster than the physical flow. Well-balanced numerical schemes can deal with this problem. Three such schemes were applied in the implicit, finite-volume SEVEN-LEAGUE HYDRO code in combination with a low-Mach-number numerical flux function. We compare how the schemes perform in four numerical experiments addressing some of the challenges imposed by typical problems in stellar hydrodynamics. We find that the α-β and deviation well-balancing methods can accurately maintain hydrostatic solutions provided that gravitational potential energy is included in the total energy balance. They accurately conserve minuscule entropy fluctuations advected in an isentropic stratification, which enables the methods to reproduce the expected scaling of convective flow speed with the heating rate. The deviation method also substantially increases accuracy of maintaining stationary orbital motions in a Keplerian disk on long timescales. The Cargo–LeRoux method fares substantially worse in our tests, although its simplicity may still offer some merits in certain situations. Overall, we find the well-balanced treatment of gravity in combination with low Mach number flux functions essential to reproducing correct physical solutions to challenging stellar slow-flow problems on affordable collocated grids.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Molecular simulations of hydrated phyllomanganates

Hydrated phyllomanganates are layered Mn-oxide minerals with interlayers that can possess variable water contents and react strongly with trace metals due to octahedral vacancies in the layer. The unique properties of phyllomanganates afford them a significant role in many environmental phenomena that affect soil and water composition mainly via cation exchange and adsorption of trace metals. Slight variations in the structural and chemical composition often result in a dramatic difference in the chemical reactivity of the minerals. Molecular simulations at the classical mechanical level of theory, which uses a simplified description of the interatomic potential energies, can provide an atomistic perspective of the relationship between the chemical composition and the bulk and interlayer structures. Here, we introduce a set of interatomic potentials for hydrated phyllomanganates with variable vacancy and Mn 3+ content and report the classical mechanical simulation results performed at standard temperature and pressure. The potentials we introduce provide not only a reasonable reproduction of the experimentally determined atomic structures of the chalcophanite group, but also new insights on similar phyllomanganate minerals with hexagonal symmetry and a range of vacancy contents. When a vacancy is protonated, Mn 3+ is unstable in the hexagonal birnessite layer and occupies the interlayer as a cap on the associated vacancy. When a vacancy was charge-balanced by Mn 3+ and Na + , considerable amounts of Mn 3+ were incorporated into the hexagonal birnessite layer, but only at total Mn(III) contents greater than ~10% and with disordered layer stacking. The potentials also predicted a vacancy-free, triclinic Na-birnessite structure with Mn(III)-rich rows in the layer which were arranged parallel to the b-axis and separated by two rows of Mn(IV) octahedra. The dominant interlayer Na complex at a water content ≥0.7 H 2 O/MnO 2 was an octahedrally-coordinated, split interlayer site with two birnessite O atoms in the axial positions and four interlayer H 2 O in the equatorial positions. Other interlayer Na complexes including some edge- and face-sharing complexes existed in trace amounts (<10%). These classical mechanical simulations represent a successful first test of the introduced interatomic potentials, which can be used to further explore the interlayer and surface complexes of phyllomanganate and birnessite-group minerals.

58 GEOSCIENCES↗
DOE OSTI2019

A New Criterion to Improve Operational Drizzle Detection with Ground-Based Remote Sensing

Light shallow precipitation in the form of drizzle is one of the mechanisms for liquid water removal, affecting cloud lifetime and boundary layer dynamics and thermodynamics. The early formation of drizzle drops is of particular interest for quantifying aerosol–cloud–precipitation interactions. In models, drizzle initiation is represented by the autoconversion, that is, the conversion of liquid water from a cloud liquid water category (where particle sedimentation is ignored) into a precipitating liquid water category. Various autoconversion parameterizations have been proposed in recent years, but their evaluation is challenging due to the lack of proper observations of drizzle development in the cloud. This work presents a new algorithm for Classification of Drizzle Stages (CLADS). CLADS is based on the skewness of the Ka-band radar Doppler spectrum. Skewness is sensitive to the drizzle growth in the cloud: the observed Gaussian Doppler spectrum has skewness zero when only cloud droplets are present without any significant fall velocity. Defining downward velocities positive, skewness turns positive when embryonic drizzle forms and becomes negative when drizzle starts to dominate the spectrum. CLADS identifies spatially coherent structures of positive, zero, and negative skewness in space and time corresponding to drizzle seeding, drizzle growth/nondrizzle, and drizzle mature, respectively. We test CLADS on case studies from the Jülich Observatory for Cloud Evolution Core Facility (JOYCE-CF) and the Barbados Cloud Observatory (BCO) to quantitatively estimate the benefits of CLADS compared to the standard Cloudnet target categorization algorithm. We suggest that CLADS can provide additional observational constraints for understanding the processes related to drizzle formation better.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Climate Induced Spillover and Implications for U.S. Security.

Developing nations incur a greater risk to climate change than the developed world due to poorly managed human/natural resources, unreliable infrastructure and brittle governing/economic institutions. These vulnerabilities often give rise to a climate induced “domino effect” of reduced natural resource production-leading to economic hardship, social unrest, and humanitarian crises. Integral to this cascading set of events is increased human migration, leading to the “spillover” of impacts to adjoining areas with even broader impact on global markets and security. Given the complexity of factors influencing human migration and the resultant spill-over effect, quantitative tools are needed to aid policy analysis. Toward this need, a series of migration models were developed along with a system dynamics model of the spillover effect. The migration decision models were structured according to two interacting paths, one that captured long-term “chronic” impacts related to protracted deteriorating quality of life and a second focused on short-term “acute” impacts of disaster and/or conflict. Chronic migration dynamics were modeled for two different cases; one that looked only at emigration but at a national level for the entire world; and a second that looked at both emigration and immigration but focused on a single nation. Model parameterization for each of the migration models was accomplished through regression analysis using decadal data spanning the period 1960-2010. A similar approach was taken with acute migration dynamics except regression analysis utilized annual data sets limited to a shorter time horizon (2001-2013). The system dynamics spillover model was organized around two broad modules, one simulating the decision dynamics of migration and a second module that treats the changing environmental conditions that influence the migration decision. The environmental module informs the migration decision, endogenously simulating interactions/changes in the economy, labor, population, conflict, water, and food. A regional model focused on Mali in western Africa was used as a test case to demonstrate the efficacy of the model.

Tidwell, Vincent C.↗
DOE OSTI2024

Enhancing Biopreparedness through a Model System to Understand the Molecular Mechanisms that Lead to Pathogenesis and Disease Transmission: NW-BRaVE

The science of biopreparedness to counter biological threats hinges on understanding the fundamental principles and molecular mechanisms that lead to pathogenesis and disease transmission. Our vision to address this challenge is to create a powerful and user-friendly platform to elucidate the fundamental principles of how molecular interactions drive pathogen-host relationships and host shifts. We will enable groundbreaking discoveries by integrating a wide range of structural, genomics, proteomics, and other advanced omics measurements, along with evolutionary and artificial intelligence predictions. To make sure the system is applicable to real-world problems, we will develop it in the context of a tractable model system, the small, abundant, and accessible photosynthetic cyanobacteria and their constantly co-adapting viral pathogens, cyanophages. This model will maintain the system’s applicability to real-world problems and techniques, but the overall focus will be on elucidating general principles of detecting, assessing, and surveilling molecular interaction, adaptation, and coevolution that are system agnostic and therefore extensible to other viral-host interactions. Our overall objectives are to (1) identify the molecular complexes that comprise the cyanobacteria redox macromolecular subsystem and how they dynamically change with bacteriophage infection in situ, using cryo-electron tomography; (2) profile regulatory changes during infection using proteomics, multiomics, and experimental validation, and integrate the data with in situ structures; (3) use genomics and metagenomics to determine environmental and population factors across time scales that impact the interactions between marine cyanobacteria and their cyanophage parasites, predicting the evolutionary origins of in situ structural and functional interactions, convergence and coevolution; and (4) develop a data integration and transformation platform that facilitates the integration of in situ, proteomic, and evolutionary measurements of molecular interactions to surveil diverse hosts and parasites in various environmental contexts. These objectives address Focus Area 2 Reveal Molecular Interactions Across Biological Scales for Design of Targeted Interventions. Our powerful and user-friendly platform will enhance connections between the often-siloed fields of structure, molecular phenotype, and evolutionary genomics that are key to biopreparedness, but in need of integration (Figure 1). We will build an integrated navigation tool to facilitate the effective use of globally distributed experimental data for integrated analysis and predictive modeling. The project will develop, implement, and test a platform to assess host-pathogen molecular interactions, adaptation to hosts and host shifts, and coevolution between hosts and pathogens, successfully impacting the research community by revolutionizing abilities to study any host-pathogen interaction, encourage diverse community contributions, and gain fundamental insights into how proteins adapt to new contexts. This ability will be critical for designing early interventions to address future threats. We will build surveillance training capability, aiming for a fair and equitable response to future pandemics and biothreats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Lensing of Fast Radio Bursts by Plasma Structures in Host Galaxies

The amplitudes of fast radio bursts (FRBs) can be strongly modulated by plasma lenses in their host galaxies, including that of the repeating FRB 121102 at ∼1 Gpc luminosity distance. Caustics require the lens’ dispersion measure depth (DM{sub ℓ}), scale size (a), and distance from the source (d{sub sl}) to satisfy DM{sub ℓ}d{sub sl}/a{sup 2}≳0.65 pc{sup 2} au{sup −2} cm{sup −3}. Caustics produce strong magnifications (≲10{sup 2}) on short timescales (≲ hours to days) that appear as narrow spectral peaks (0.1–1 GHz). They also suppress the flux density in longer-duration (∼months) troughs. Multiply imaged bursts will arrive differentially by <1 μs to tens of ms with different apparent dispersion measures, δDM∼1 pc cm{sup −3}. When differing by less than the burst width, interference effects in dynamic spectra will be seen. Larger arrival time perturbations may mask any underlying periodicity with period ≲1 s. Strong lensing requires sources smaller than (Fresnelscale){sup 2}/a, which includes compact objects such as neutron star magnetospheres but excludes active galactic nuclei. We discuss constraints on densities, magnetic fields, and locations of plasma lenses related to the conditions needed for lensing to occur. Much of the phenomenology of the repeating FRB source FRB 121102 can be accounted for in this picture, which can be tested by obtaining wideband spectra of bursts (from <1 to 10 GHz and possibly higher) that will also help characterize the plasma environment near FRB sources. A rich variety of phenomena is expected from an ensemble of lenses near an FRB source.

79 ASTRONOMY AND ASTROPHYSICS↗