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At least 163 records · Page 9

Solar Flare Termination Shock and the Synthetic Fe XXI 1354.08 Å Line

Solar flares are one of the most energetic phenomena occurred in the solar system. In the standard solar flare model, a fast mode shock, which is often referred to as the flare termination shock (TS), can exist above the loop-top source of hard X-ray emissions. The existence of the termination shock has been recently related to spectral hardening of flare hard X-ray spectrum at energies > 300 keV. Observations of the Fe XXI 1354.08 Å line during solar flares by the IRIS spacecraft have found significant redshift with >100 km/s, which is consistent with a reconnection downflow. The ability to identify such a redshift by IRIS is made possible by IRIS's high time resolution, high spatial resolution, high sensitivity and cadence spectral observations. The ability to identify such a redshift by IRIS suggests that one may be able to use IRIS observations to identify flare termination shocks. Using a MHD simulation to model magnetic reconnection of a solar flare and assuming the existence of a TS in the downflow of the reconnection plasma, we model the synthetic emission of the Fe XXI 1354.08 Å line in this work. We show that the existence of the TS in the solar flare may manifest itself from the Fe XXI 1354.08 Å line.Plain Language SummaryA solar flare is a brief eruption of intense high-energy radiation from the sun's surface, associated with sunspots and causing electromagnetic disturbances on the earth, as with radio frequency communications and power line transmissions. The standard solar flare model proposes that magnetic reconnection drives solar flares and fast mode shock, which is often referred to as the flare termination shock (TS), can exist at the reconnection outflows. The existence of the termination shock has been recently related to spectral hardening of flare hard X-ray spectrum.

Guo, Lijia↗

Kimberlina 1.2 Velocity Models and Seismic Data

Kimberlina 1.2 Velocity model and synthetic seismic data, produced in collaboration of teams at the National Energy Technology Laboratory, Los Alamos National Laboratory, and Lawrence Livermore National Laboratory through the National Risk Assessment Partnership. Data is associated with the following publication: Zheng Zhou, Youzuo Lin, Zhongping Zhang, Yue Wu, Zan Wang, Robert Dilmore, and George Guthrie, "A Data-Driven CO2 Leakage Detection Using Seismic Data and Spatial-Temporal Densely Connected Convolutional Neural Networks," International Journal of Greenhouse Gas Control, Vol 90, 2019. The Kimberlina 1.2 Velocity models were produced by Zan Wang, Robert Dilmore, William Harbert, and Lianjie Huang at NETL. The following citations are directly related to the creation of the velocity models: Wang, Z. Harbert, W., Dilmore, R., Huang, L. Modeling of time-lapse seismic monitoring using CO2 leakage simulations for a model CO2 storage site with realistic geology: Application in assessment of early leak-detection capabilities. International Journal of Greenhouse Gas Control. V. 76, September 2018, Pages 39-52. https://doi.org/10.1016/j.ijggc.2018.06.011 Wang, Z., Dilmore, R., Harbert, W. Inferring CO2 saturation from synthetic surface seismic and downhole monitoring data using machine learning for leakage detection at CO2 sequestration sites. International Journal of Greenhouse Gas Control, V. 100, September 2020. https://doi.org/10.1016/j.ijggc.2020.103115 The velocity models were built based on the Kimberlina 1.2 aquifer impact data which is associated with the following publications: Buscheck, T.A., Mansoor, K., Yang, X., Wainwright, H., and Carroll, S. (2019). Downhole pressure and chemical monitoring for CO2 and brine leak detection in aquifers above a CO2 storage reservoir. International Journal of Greenhouse Gas Control. 91. 102812. 10.1016/j.ijggc.2019.102812. Xianjin Yang, Thomas A. Buscheck, Kayyum Mansoor, Zan Wang, Kai Gao, Lianjie Huang, Delphine Appriou, Susan A. Carroll, Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, Volume 90, 2019, 102803, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2019.102803 The synthetic seismic data was produced by Youzuo Lin and team at LANL, and are associated with the following citations: Jordan, P. D., and J. L. Wagoner. Characterizing Construction of Existing Wells to a CO2 Storage Target: The Kimberlina Site, California. Zheng Zhou, Youzuo Lin, Zhongping Zhang, Yue Wu, Zan Wang, Robert Dilmore, and George Guthrie, "A Data-Driven CO2 Leakage Detection Using Seismic Data and Spatial-Temporal Densely Connected Convolutional Neural Networks," International Journal of Greenhouse Gas Control, Vol 90, 2019.

CO2 Leakage↗

A Reduced-Order Model For Zero-Mass Synthetic Jet Actuators

Accurate details of the general performance of fluid actuators is desirable over a range of flow conditions, within some predetermined error tolerance. Designers typically model actuators with different levels of fidelity depending on the acceptable level of error in each circumstance. Crude properties of the actuator (e.g., peak mass rate and frequency) may be sufficient for some designs, while detailed information is needed for other applications (e.g., multiple actuator interactions). This work attempts to address two primary objectives. The first objective is to develop a systematic methodology for approximating realistic 3-D fluid actuators, using quasi-1-D reduced-order models. Near full fidelity can be achieved with this approach at a fraction of the cost of full simulation and only a modest increase in cost relative to most actuator models used today. The second objective, which is a direct consequence of the first, is to determine the approximate magnitude of errors committed by actuator model approximations of various fidelities. This objective attempts to identify which model (ranging from simple orifice exit boundary conditions to full numerical simulations of the actuator) is appropriate for a given error tolerance.

Yamaleev, Nail K.↗

Resolution experiments for NW Pacific subduction zone tomography

Results are reported from an investigation of the resolving power of ISC/NEIC P travel-time data in tomographic inversions for the geometry of the subduction zones in the NW Pacific. From thermal models for the Kurile, Janan, Izu-Bonin, Mariana, and Ryukyu slabs, three-dimensional synthetic velocity anomalies for subducting slabs are generated and projected onto a cell model for the uppermost 1400 km of the mantle. These synthetic models are used to compute synthetic delay times for ray paths corresponding to the source and receiver locations used for the actual data, add Gaussian noise, invert the synthetic data, and compare the resulting velocity structure to the initial synthetic models. This comparison is illustrated for sections through the Kuriles and the Mariana arcs. A variety of resolution artifacts are observed, which in many cases resemble features visible in the tomographic results obtained from inverting the actual ISC/NEIC data.

Spakman, Wim↗

The derivation of sub-canopy surface terrain models of coastal forests using synthetic aperture radar

Radar data acquired by the Shuttle Imaging Radar-B mission covering a portion of the Mouths of the Ganges forests were used to create a terrain model for use in determining tidal flow and eventual nutrient transport from the forest to the marine habitat. Results show that good digital topographic terrain models of wet coastal forests can be generated using multiple sets of L-band SAR and ancillary tide elevation data. The dominance of the interaction phenomenon in the radar backscatter of flooded forests can be used to create sub-canopy inundation maps which when merged with tide surface data can be used to generate reasonable topographic models. Ideally models could be improved by using multiple sets of data at a constant incidence angle over the total tide range. The optimal angle for the SAR depends upon the characteristics of the forest. The range of 46 to 57 deg seems applicable to the 12.5 m tall closed canopy in this example. Such models can be an extremely valuable tool for studying and mapping the mangal ecosystem.

Imhoff, M. L.↗

A VLSI implementation for synthetic aperture radar image processing

A simple physical model for the Synthetic Aperture Radar (SAR) is presented. This model explains the one dimensional and two dimensional nature of the received SAR signal in the range and azimuth directions. A time domain correlator, its algorithm, and features are explained. The correlator is ideally suited for VLSI implementation. A real time SAR architecture using these correlators is proposed. In the proposed architecture, the received SAR data is processed using one dimensional correlators for determining the range while two dimensional correlators are used to determine the azimuth of a target. The architecture uses only three different types of custom VLSI chips and a small amount of memory.

Premkumar, A.↗

Relating multifrequency radar backscattering to forest biomass: Modeling and AIRSAR measurement

During the last several years, significant efforts in microwave remote sensing were devoted to relating forest parameters to radar backscattering coefficients. These and other studies showed that in most cases, the longer wavelength (i.e. P band) and cross-polarization (HV) backscattering had higher sensitivity and better correlation to forest biomass. This research examines this relationship in a northern forest area through both backscatter modeling and synthetic aperture radar (SAR) data analysis. The field measurements were used to estimate stand biomass from forest weight tables. The backscatter model described by Sun et al. was modified to simulate the backscattering coefficients with respect to stand biomass. The average number of trees per square meter or radar resolution cell, and the average tree height or diameter breast height (dbh) in the forest stand are the driving parameters of the model. The rest of the soil surface, orientation, and size distributions of leaves and branches, remain unchanged in the simulations.

Sun, Guo-Qing↗

Observational Effects of Magnetism in O Stars: Surface Nitrogen Abundances

Aims. We investigate the surface nitrogen content of the six magnetic O stars known to date as well as of the early B-type star Tau Sco.. We compare these abundances to predictions of evolutionary models to isolate the effects of magnetic field on the transport of elements in stellar interiors. Methods. We conduct a quantitative spectroscopic analysis of the ample stars with state-of-the-art atmosphere models. We rely on high signal-to-noise ratio, high resolution optical spectra obtained with ESPADONS at CFHT and NARVAL at TBL. Atmosphere models and synthetic spectra are computed with the code CMFGEN. Values of N/H together with their uncertainties are determined and compared to predictions of evolutionary models. Results. We find that the magnetic stars can be divided into two groups: one with stars displaying no N enrichment (one object); and one with stars most likely showing extra N enrichment (5 objects). For one star (Ori C) no robust conclusion can be drawn due to its young age. The star with no N enrichment is the one with the weakest magnetic field, possibly of dynamo origin. It might be a star having experienced strong magnetic braking under the condition of solid body rotation, but its rotational velocity is still relatively large. The five stars with high N content were probably slow rotators on the zero age main sequence, but they have surface N/H typical of normal O stars, indicating that the presence of a (probably fossil) magnetic field leads to extra enrichment. These stars may have a strong differential rotation inducing shear mixing. Our results shOuld be viewed as a basis on which new theoretical simulations can rely to better understand the effect of magnetism on the evolution of massive stars.

Martins, F.↗

MIRO Observation of Comet C/2002 T7 (LINEAR) Water Line Spectrum

Comet C/2002 T7 (LINEAR) was observed with the Microwave Instrument for Rosetta Orbiter (MIRO) on April 30, 2004, between 5 hr and 16 hr UT. The comet was 0.63AU distance from the Sun and 0.68AU distance from the MIRO telescope at the time of the observations. The water line involving the two lowest rotational levels at 556.936 GHz is observed at 557.070 GHz due to a large Doppler frequency shift. The detected water line spectrum is interpreted using a non local thermal equilibrium (Non-LTE) molecular excitation and radiative transfer model. Several synthetic spectra are calculated with various coma profiles that are plausible for the comet at the time of observations. The coma profile is modeled with three characteristic parameters: outgassing rate, a constant expansion velocity, and a constant gas temperature. The model calculation result shows that for the distant line observation where contributions from a large coma space is averaged, the combination of the outgassing rate and the gas expansion velocity determines the line shape while the gas temperature has a negligible effect. The comparison between the calculated spectra and the MIRO measured spectrum suggests that the outgassing rate of the comet is about 2.0x1029 molecules/second and its gas expansion velocity about 1.2 km/s at the time of the observations.

spectral line↗

Modeling of bottom-related surface patterns imaged by synthetic aperture radar

A hydrodynamic electromagnetic model is developed in order to provide a qualitative and quantitative description of the relationship between Seasat synthetic aperture radar (SAR) signatures and the bottom topography of the ocean in the English Channel region of the North Sea. The model is based on environmental data for winds, currents, and depth changes, and the SAR parameters of frequency polarization, incidence angle, and resolution cell size. The data are used as inputs and SAR backscatter changes are predicted for individual topographic changes on the ocean floor. It is found that the model estimates of backscatter values are in good agreement with actual Seasat SAR-observed backscatter values. A comparison of the model and actual data shows agreement to be within 1.5 dB. The model is considered to be valid for only shallow water areas (less than 50 meters in depth). It is suggested that for bottom features to be visible on SAR imagery at greater depths, a moderate-to-high velocity current of at least 0.4 m/s and a moderate wind no more than 7.5 m/sec must be present.

Lyzenga, D. R.↗

A deep learning approach to programmable RNA switches

Engineered RNA elements are programmable tools capable of detecting small molecules, proteins, and nucleic acids. Predicting the behavior of these synthetic biology components remains a challenge, a situation that could be addressed through enhanced pattern recognition from deep learning. Here, we investigate Deep Neural Networks (DNN) to predict toehold switch function as a canonical riboswitch model in synthetic biology. To facilitate DNN training, we synthesize and characterize in vivo a dataset of 91,534 toehold switches spanning 23 viral genomes and 906 human transcription factors. DNNs trained on nucleotide sequences outperform (R 2 = 0.43–0.70) previous state-of-the-art thermodynamic and kinetic models (R 2 = 0.04–0.15) and allow for human-understandable attention-visualizations (VIS4Map) to identify success and failure modes. This work shows that deep learning approaches can be used for functionality predictions and insight generation in RNA synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

Community Modeling and Flux Balance Analysis of Synthetic Bacterial Community in MOPS Medium

This narrative was used for the 4-member community modeling using MOPS medium for the bacteria isolated from Populus deltoides (PD). 10 bacterial strains isolated from PD were co-cultured as a synthetic microbial community in MOPS minimal medium. After 15 passages there were 4 members survived in MOPS medium. The genome of each community member was sequenced and uploaded into KBase for genome annotation and metabolic modeling. To simulate the metabolic interactions among the finally surviving community members, the individual metabolic models of each strain were merged into a compartmentalized community model, and then the community model was gapfilled using MOPS medium. The FBA modeling was performed and the metabolites exchange among community members was proposed. The publication by Jia Wang, Dana L. Carper, Leah H. Burdick, Him Shrestha, Manasa Appidi, Paul E. Abraham, Collin M. Timm, Robert L. Hettich, Dale A. Pelletier, Mitchel J. Doktycz can be found here: https://doi.org/10.​1016/​j.​csbj.​2021.​03.​034

59 BASIC BIOLOGICAL SCIENCES↗

Community Modeling and Flux Balance Analysis of Synthetic Bacterial Community in R2A Medium

This narrative was used for the 3-member community modeling using R2A medium for the bacteria isolated from Populus deltoides (PD). 10 bacteiral strains isolated from PD were co-cultured as a synthetic microbial community in R2A complex medium. After 15 passages, there were 3 members survived in R2A medium. The genome of each community member was sequenced and uploaded into KBase for genome annotation and metabolic modeling. To simulate the metabolic interactions among the finally surviving community members, the individual metabolic models of each strain were merged into a compartmentalized community model, and then the community model was gapfilled using R2A medium. The FBA modeling was performed and the metabolites exchange among community members was proposed. The publication by Jia Wang, Dana L. Carper, Leah H. Burdick, Him Shrestha, Manasa Appidi, Paul E. Abraham, Collin M. Timm, Robert L. Hettich, Dale A. Pelletier, Mitchel J. Doktycz can be found here: https://doi.org/10.​1016/​j.​csbj.​2021.​03.​034

59 BASIC BIOLOGICAL SCIENCES↗

Man‐in‐the‐middle attacks and defence in a power system cyber‐physical testbed

Abstract Man‐in‐The‐Middle (MiTM) attacks present numerous threats to a smart grid. In a MiTM attack, an intruder embeds itself within a conversation between two devices to either eavesdrop or impersonate one of the devices, making it appear to be a normal exchange of information. Thus, the intruder can perform false data injection (FDI) and false command injection (FCI) attacks that can compromise power system operations, such as state estimation, economic dispatch, and automatic generation control (AGC). Very few researchers have focused on MiTM methods that are difficult to detect within a smart grid. To address this, we are designing and implementing multi‐stage MiTM intrusions in an emulation‐based cyber‐physical power system testbed against a large‐scale synthetic grid model to demonstrate how such attacks can cause physical contingencies such as misguided operation and false measurements. MiTM intrusions create FCI, FDI, and replay attacks in this synthetic power grid. This work enables stakeholders to defend against these stealthy attacks, and we present detection mechanisms that are developed using multiple alerts from intrusion detection systems and network monitoring tools. Our contribution will enable other smart grid security researchers and industry to develop further detection mechanisms for inconspicuous MiTM attacks.

Wlazlo, Patrick↗

Synthetic-aperture-radar imaging of the ocean surface using the slightly-rough facet model and a full surface-wave spectrum

A new model of synthetic-aperture-radar (SAR) imaging of ocean waves is described. The model is based on mapping individual, slightly-rough surface facets through the SAR processor into the image and responses of the facets in the image domain are added together coherently to give the composite image. A windowing technique allows both the orbital motion and the phase velocity of the long waves to be included. It is determined that the azimuthal cut-off is due to a smearing of the response of the facets in the image induced by the random orbital motion of the intermediate large-scale waves and that the focus adjustment that gives the greatest image contrast is half the phase velocity of the dominant long wave. The optimal processing technique, however, may consist of spatially offsetting the multiple looks on the image domain to compensate the propagation of long waves during the integration time of the SAR.

West, James C.↗

Probing interspecies metabolic interactions within a synthetic binary microbiome using genome-scale modeling

Metabolic interactions within a microbial community play a key role in determining the structure, function, and composition of the community. However, due to the complexity and intractability of natural microbiomes, limited knowledge is available on interspecies interactions within a community. In this work, using a binary synthetic microbiome, a methanotroph-photoautotroph (M-P) coculture, as the model system, we examined different genome-scale metabolic modeling (GEM) approaches to gain a better understanding of the metabolic interactions within the coculture, how they contribute to the enhanced growth observed in the coculture, and how they evolve over time. Using batch growth data of the model M-P coculture, we compared three GEM approaches for microbial communities. Two of the methods are existing approaches: SteadyCom, a steady state GEM, and dynamic flux balance analysis (DFBA) Lab, a dynamic GEM. We also proposed an improved dynamic GEM approach, DynamiCom, for the M-P coculture. SteadyCom can predict the metabolic interactions within the coculture but not their dynamic evolutions; DFBA Lab can predict the dynamics of the coculture but cannot identify interspecies interactions. DynamiCom was able to identify the cross-fed metabolite within the coculture, as well as predict the evolution of the interspecies interactions over time. A new dynamic GEM approach, DynamiCom, was developed for a model M-P coculture. Constrained by the predictions from a validated kinetic model, DynamiCom consistently predicted the top metabolites being exchanged in the M-P coculture, as well as the establishment of the mutualistic N-exchange between the methanotroph and cyanobacteria. The interspecies interactions and their dynamic evolution predicted by DynamiCom are supported by ample evidence in the literature on methanotroph, cyanobacteria, and other cyanobacteria-heterotroph cocultures.

59 BASIC BIOLOGICAL SCIENCES↗

A Numerical Climate Observing Network Design Study

This project was concerned with three related questions of an optimal design of a climate observing system: 1. The spatial sampling characteristics required from an ARGO system. 2. The degree to which surface observations from ARGO can be used to calibrate and test satellite remote sensing observations of sea surface salinity (SSS) as it is anticipated now. 3. The more general design of an climate observing system as it is required in the near future for CLIVAR in the Atlantic. An important question in implementing an observing system is that of the sampling density required to observe climate-related variations in the ocean. For that purpose this project was concerned with the sampling requirements for the ARGO float system, but investigated also other elements of a climate observing system. As part of this project we studied the horizontal and vertical sampling characteristics of a global ARGO system which is required to make it fully complementary to altimeter data with the goal to capture climate related variations on large spatial scales (less thanAttachment: 1000 km). We addressed this question in the framework of a numerical model study in the North Atlantic with an 1/6 horizontal resolution. The advantage of a numerical design study is the knowledge of the full model state. Sampled by a synthetic float array, model results will therefore allow to test and improve existing deployment strategies with the goal to make the system as optimal and cost-efficient as possible. Attachment: "Optimal observations for variational data assimilation".

Stammer, Detlef↗

Doppler Backscattering Data Analysis and Integrated Modeling with OMFIT

One Modeling Framework for Integrated Tasks (OMFIT) is a widely used software tool in the magnetic fusion research community. OMFIT provides magnetic fusion energy researchers with a framework for the development of special-purpose physics modules. This paper describes an OMFIT physics module pertaining to the Doppler Backscattering (DBS) fusion plasma diagnostic. DBS measures density fluctuations and flow velocity through plasma scattering of electromagnetic waves. The OMFIT DBS module was developed to analyze experimental DBS data and facilitate modeling of DBS systems installed on multiple tokamak devices. The OMFIT DBS module is designed to support several analysis workflows: detailed analysis of experimental data, experimental planning, and theory-based synthetic diagnostic modeling. The DBS module uses integrated modeling by leveraging other OMFIT physics modules to perform tasks related to DBS, e.g. ray/beam–tracing simulations, edge-localized mode–synchronized data analysis, magnetic equilibrium reconstruction, and fitting kinetic profile data. Furthermore, this paper describes several supported workflows and serves a reference for the OMFIT DBS module.

Doppler backscattering↗