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Luminous Blue Variables (LBVs) are believed to be evolved, extremely massive stars close to the Eddington Limit and hence prone to bouts of large-scale, unstable mass loss. I discuss current understanding of the evolutionary state of these objects, the role duplicity may play and known physical characteristics of these stars using the X-ray luminous LBVs Eta Carinae and HD 5980 as test cases.
JEM-EUSO space observatory is planned with a very large exposure factor which will exceed the critical exposure factor required for observing the most of the sources within the propagational horizon of about one hundred Mpc. The main science objective of JEM-EUSO is the source-identifying astronomy in particle channel with extremey-high-energy particles. Quasi-linear tracking of the source objects through galactic magnetic field should become feasible at energy > 10(exp 20) eV for all-sky. The individual GZK profile in high statistics experiments should differ from source to source due to different distance unless Lorentz invariance is somehow limited. hi addition, JEM-EUSO has three exploratory test observations: (i), extremely high energy neutrinos beginning at E > 10(exp 19) eV: neutrinos as being expected to have a slowly increasing cross section in the Standard Model, and in particular, hundreds of times more in the extra-dimension models. (ii). fundamental physics at extreme Super LHC (Large Hadronic Collider) energies with the hierarchical unified energy much below the GUT scale, and (iii). global atmospheric observation, including large-scale and local plasma discharges, night-glow, meteorites, and others..
A circuit topography is presented which is used to create usable digital logic gates using N (negatively doped) channel Junction Field Effect Transistors (JFETs) and load resistors, level shifting resistors, and supply rails whose values are based on the direct current (DC) parametric distributions of those JFETs. This method has direct application to the current state of the art in high temperature, for example 300.degree. C. to 500.degree. C. and higher, silicon carbide (SiC) device production. The ability to produce inverting and combinatorial logic enables the production of pulse and edge triggered latches. This scale of logic synthesis would bring digital logic and state machine capabilities to devices operating in extremely hot environments, such as the surface of Venus, near hydrothermal vents, within nuclear reactors (SiC is inherently radiation hardened), and within internal combustion engines. The basic logic gate can be configured as a driver for oscillator circuits allowing for time bases and simple digitizers for resistive or reactive sensors. The basic structure of this innovation, the inverter, can be reconfigured into various analog circuit topographies through the use of feedback structures.
Interplanetary dust particles (IDPs) collected in the Earth s stratosphere and NASA Stardust mission samples constitute direct samples of diverse cometary bodies. These materials are among the least altered remnants of the original building blocks of the Solar System. Both cometary materials and primitive meteorites contain a broad diversity of organic compounds that appear to have formed in a range of environments, including the presolar cold molecular cloud, the solar nebula, asteroids and comet nuclei. Isotopic anomalies in H, C, and N are commonly observed in meteoritic organic matter, reflecting chemical processes at extremely low temperatures. These isotopic anomalies are also very heterogeneous on micrometer and even smaller spatial scales, suggesting that some presolar organic grains have survived the formation of the Solar System. Most recently, coordinated transmission electron microscopy and isotopic imaging studies have shown that isotopically anomalous organic globules having rounded and often hollow structures are abundant and widespread amongst the most primitive components of meteoritic materials. These studies suggest that such organic grains were among the most important primary building blocks of the Solar System.
As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The GCD PSI Project, planned to be accomplished over a four year period, contains a Predictive Simulation Capability (PSC) Element focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the PSC Element, the PSI Project also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper describes the activities and accomplishments in the past year for the Prediction of Plume Flow in low pressure environments component of the PSI Project. While the Loci/Chem Computational fluid dynamics (CFD) application has been validated and used extensively for simulating launch environments in atmospheric conditions, use of this tool for simulating supersonic plumes at Mars-like ambient pressure requires further validation. CFD simulations of underexpanded jets have been performed using Loci/Chem for Mars-like conditions to predict several metrics for steady laminar, turbulent, and impinging plumes. The CFD results are compared with an experimental data set for low Reynolds number plumes at these conditions in order to evaluate the current capability of the Loci/Chem tool for these types of environments. The CFD validation results to date show reasonable agreement with the experimental data across all of the metrics of interest for the configurations considered. The Loci/Chem-Boltzmann CFD application is a hybrid continuum/rarefied flow solver which extends modeling capabilities to very low pressure environments such as those on the Moon. The Loci/Chem-Boltzmann solver uses a gradient-based continuum breakdown criterion to restrict solution of the computationally expensive Boltzmann equation to only a subset of the domain, while using the Navier-Stokes equations elsewhere. This CFD application is under active development, and current efforts toward establishing production ready capability for evaluating Lunar plume surface interactions are well under way. Initial simulations of an Apollo LEM indicate that several regions of the flow require solving the Boltzmann equations due to extreme rarefaction. Early simulations are promising, indicating reasonable overall computational time for a full 3D human scale lander simulation.
While the Loci/Chem Computational fluid dynamics (CFD) application has been validated and used extensively for simulating launch environments in atmospheric conditions, use of this tool for simulating supersonic plumes at much lower ambient pressure requires further validation. Simulations of underexpanded plumes have been performed using Loci/Chem at Martian pressure to predict several metrics for laminar, turbulent, and impinging plumes. The CFD results are compared with an experimental data set for low Reynolds number plumes at these conditions in order to evaluate the current capability of the Loci/Chem tool for these types of environments. The CFD validation results to date show reasonable agreement with the experimental data across all the metrics of interest for the configurations considered. The Loci/Chem-Boltzmann tool is a hybrid continuum/rarefied flow solver which extends modeling capabilities to very low-pressure environments such as those on the Moon. The Loci/Chem-Boltzmann solver uses a gradient-based continuum breakdown criterion to restrict solution of the computationally expensive Boltzmann equation to only a subset of the domain, while using the Navier-Stokes equations elsewhere. This CFD application is under active development, and current efforts toward establishing production ready capability for evaluating Lunar plume surface interactions are well under way. Initial simulations of an Apollo Lunar excursion module indicate that several regions of the flow require solving the Boltzmann equations due to extreme rarefaction. Early simulations are promising, indicating reasonable overall computational time for a full 3D human scale lander simulation.
Abstract. We consider the problem of estimating the ensemble sizes required to characterize the forced component and the internal variability of a number of extreme metrics. While we exploit existing large ensembles, our perspective is that of a modeling center wanting to estimate a priori such sizes on the basis of an existing small ensemble (we assume the availability of only five members here). We therefore ask if such a small-size ensemble is sufficient to estimate accurately the population variance (i.e., the ensemble internal variability) and then apply a well-established formula that quantifies the expected error in the estimation of the population mean (i.e., the forced component) as a function of the sample size n, here taken to mean the ensemble size. We find that indeed we can anticipate errors in the estimation of the forced component for temperature and precipitation extremes as a function of n by plugging into the formula an estimate of the population variance derived on the basis of five members. For a range of spatial and temporal scales, forcing levels (we use simulations under Representative Concentration Pathway 8.5) and two models considered here as our proof of concept, it appears that an ensemble size of 20 or 25 members can provide estimates of the forced component for the extreme metrics considered that remain within small absolute and percentage errors. Additional members beyond 20 or 25 add only marginal precision to the estimate, and this remains true when statistical inference through extreme value analysis is used. We then ask about the ensemble size required to estimate the ensemble variance (a measure of internal variability) along the length of the simulation and – importantly – about the ensemble size required to detect significant changes in such variance along the simulation with increased external forcings. Using the F test, we find that estimates on the basis of only 5 or 10 ensemble members accurately represent the full ensemble variance even when the analysis is conducted at the grid-point scale. The detection of changes in the variance when comparing different times along the simulation, especially for the precipitation-based metrics, requires larger sizes but not larger than 15 or 20 members. While we recognize that there will always exist applications and metric definitions requiring larger statistical power and therefore ensemble sizes, our results suggest that for a wide range of analysis targets and scales an effective estimate of both forced component and internal variability can be achieved with sizes below 30 members. This invites consideration of the possibility of exploring additional sources of uncertainty, such as physics parameter settings, when designing ensemble simulations.
A novel geodetic laser radar rangefinder (GLRR) unit utilizing a pair of synchronized 10-psec streak camera systems was developed for displacement measurements of the earth's plates. In order to achieve minimum computing error and assure extremely high spatial resolution, an optical pulse registration clock was developed and used to register a fiducial mark on the time scale of the system. Conventional optical rangefinders have been limited to a relative resolution of 10(exp -6) even for short distances. The system to be reported on today has the capability of measuring a 50km range with an accuracy of 4mm corresponding to a relative resolution of 10(exp -7). With a gain of greater than 3 x 10(exp 3), the system has the capability of detecting extremely weak signals on the order of photon counting. This combined with temporal gating makes daytime measurements comparable in signal-to-noise ratio to nighttime viewing. This is useful for measuring faint signals returning over a range of several tens of kilometers. The present ranging system was designed to observe the mutual displacement of geodetic plates and was employed to measure the boundary between the Philippine and Asian geodetic plates that pass beneath the Suruga Bay near Hamamatsu City, Japan. The system has been in operation for over 3 years. In addition, the system has the ability of producing and detecting optical ranging pulses of several wavelengths simultaneously, making this a complete multicolor system. The basic GLRR system consists of a frequency stabilizing crystal, optical clock, YAG laser, KDP doubling crystal, DK*P tripling crystal, two matched streak cameras (A and B), a control computer, and an output/input periscope system.
Context. Giant radio galaxies (GRGs, or colloquially ‘giants’) are the Universe’s largest structures generated by individual galaxies. They comprise synchrotron-radiating active galactic nucleus ejecta and attain cosmological (megaparsec-scale) lengths. However, the main mechanisms that drive their exceptional growth remain poorly understood. Aims. To deduce the main mechanisms that drive a phenomenon, it is usually instructive to study extreme examples. If there exist host galaxy characteristics that are an important cause for GRG growth, then the hosts of the largest GRGs are likely to possess them. Similarly, if there exist particular large-scale environments that are highly conducive to GRG growth, then the largest GRGs are likely to reside in them. For these reasons, we aim to perform a case study of the largest GRG available. Methods. We reprocessed the LOFAR Two-Metre Sky Survey DR2 by subtracting compact sources and performing multi-scale CLEAN de-convolutions at 60" and 90" resolution. The resulting images constitute the most sensitive survey yet for radio galaxy lobes, whose diffuse nature and steep synchrotron spectra have allowed them to evade previous detection attempts at higher resolution and shorter wavelengths. We visually searched these images for GRGs. Results. We have discovered Alcyoneus, a low-excitation radio galaxy with a projected proper length l p = 4.99 ± 0.04 Mpc. Both its jets and lobes are detected at very high significance, and the SDSS-based identification of the host, at spectroscopic redshift z spec = 0.24674 ± 6 × 10 -5 , is unambiguous. The total luminosity density at ν = 144 MHz is L ν = 8 ± 1 × 10 25 W Hz -1 , which is below average, though near median (percentile 45 ± 3%) for GRGs. The host is an elliptical galaxy with a stellar mass M* = 2.4 ± 0.4 × 10 11 M ⊙ and a super-massive black hole mass M• = 4 ± 2 × 10 8 M ⊙ , both of which tend towards the lower end of their respective GRG distributions (percentiles 25 ± 9% and 23 ± 11%). The host resides in a filament of the Cosmic Web. Through a new Bayesian model for radio galaxy lobes in three dimensions, we estimate the pressures in the megaparsec-cubed-scale northern and southern lobes to be P min,1 = 4.8 ± 0.3 × 10 -16 Pa and P min,2 = 4.9 ± 0.6 × 10 -16 Pa, respectively. The corresponding magnetic field strengths are B min,1 = 46 ± 1 pT and B min,2 = 46 ± 3 pT. Conclusions. We have discovered what is in projection the largest known structure made by a single galaxy – a GRG with a projected proper length l p = 4.99 ± 0.04 Mpc. The true proper length is at least l min = 5.04 ± 0.05 Mpc. Beyond geometry, Alcyoneus and its host are suspiciously ordinary: the total low-frequency luminosity density, stellar mass, and super-massive black hole mass are all lower than, though similar to, those of the medial GRG. Thus, very massive galaxies or central black holes are not necessary to grow large giants, and, if the observed state is representative of the source over its lifetime, neither is high radio power. A low-density environment remains a possible explanation. The source resides in a filament of the Cosmic Web, with which it might have significant thermodynamic interaction. The pressures in the lobes are the lowest hitherto found, and Alcyoneus therefore represents the most promising radio galaxy yet to probe the warm–hot inter-galactic medium.
The past two decades have witnessed natural disasters and extreme weather events that affect millions of people. At the same time, the data volume from high-resolution climate models, satellite, in-situ and ground-based measurements have substantially increased to petabyte scales. These new and readily accessible datasets create the previously missing pipeline required for scientific machine learning (ML) and therefore new opportunities for improved understanding and prediction capability of climate extreme events. This project developed a deep latent variable model framework to discover physically meaningful hidden structures from high-dimensional, spatiotemporal climate extreme data.
The frequency and severity of spruce bark beetle outbreaks are increasing in boreal forests leading to widespread tree mortality and fuel conditions promoting extreme wildfire. Detection of beetle infestation is a forest health monitoring (FHM) priority but is hampered by the challenges of detecting early stage (“green”) attack from the air. There is indication that green stage might be detected from vertical gradients of spectral data or from shortwave infrared information distributed within a single crown. To evaluate the efficacy of discriminating “non-infested”, “green”, and “dead” health statuses at the landscape scale in Alaska, USA, this study conducted spectral and structural fusion of data from: (1) Unoccupied aerial vehicle (UAV) multispectral (6 cm) + structure from motion point clouds (~700 pts per sq. m); and (2) Goddard Lidar Hyperspectral Thermal (G-LiHT) hyperspectral (400 to 1000 nm, 0.5 m) + SWIR-band lidar (~32 pts per sq.m). We achieved 78% accuracy for all three health statuses using spectral + structural fusion from either UAV or G-LiHT and 97% accuracy for non-infested/dead using G-LiHT. We confirm that UAV 3D spectral (e.g., greenness above versus below median height in crown) and lidar apparent reflectance metrics (e.g., mean reflectance at 99th percentile height in crown), are of high value, perhaps capturing the vertical gradient of needle degradation. In most classification exercises, UAV accuracy was lower than G-LiHT indicating that collecting ultra-high spatial resolution data might be less important than high spectral resolution information. While the value of passive optical spectral information was largely confined to the discrimination of non-infested versus dead crowns, G-LiHT hyperspectral band selection (~400, 675, 755, and 940 nm) could inform future FHM mission planning regarding optimal wavelengths for this task. Interestingly, the selected regions mostly did not align with the band designations for our UAV multispectral data but do correspond to, e.g., Sentinel-2 red edge bands, suggesting a path forward for moderate scale bark beetle detection when paired with suitable structural data.
Extreme precipitation poses a major challenge for local governments, including the City and County of San Francisco, California, as flooding can damage and destroy infrastructure and property. As the climate continues to warm, reliable future precipitation projections are needed to provide the best possible information to decision makers. However, future changes in the magnitude of extreme precipitation are uncertain, as current state-of-the-art global climate models are typically run at relatively coarse horizontal resolutions that require the use of convective parameterization and have difficulty simulating observed extreme rainfall rates. Here, we performed ensembles of convection-permitting regional climate model simulations to investigate how five historically impactful extreme precipitation events over the San Francisco Bay Area could change if similar events occurred in future climates. We found that changes in storm-total precipitation depend strongly on storm type. Precipitation associated with an atmospheric river (AR) accompanied by an extratropical cyclone (ETC) is projected to increase at a rate exceeding (by up to 1.5 times) the theoretical Clausius Clapeyron scaling of 6–7% per °C warming. On the other hand, future precipitation changes are weak or negative for events characterized by an AR only, despite increases in precipitable water and integrated vapor transport that are similar to those of the co-occurring AR and ETC events. The differences in the sign of future precipitation change between AR-only events and co-occurring AR and ETC events is instead linked with changes in mid-tropospheric vertical velocity. Given that the majority of observed ARs are associated with an ETC, this research has important implications for future precipitation impacts over the Bay Area, as it indicates that storm-total precipitation associated with the most common type of storm event may increase by up to 26–37% in 2100 relative to historical.
Gas accreting ont,o black holes and neutron stars form a dynamic system generating X-rays with spectroscopic signatures and varying on time scales determined by the system. The radiation from various parts of these systems is surely polarized and compact sources have been calculated to give rise to net polarization from the unresolved sum of the radiation from the systems. Polarization has been looked to for some time as also bearing the imprint of strong gravity and providing complementary information that could resolve ambiguities between the physical models that can give rise to frequencies, time delays, and spectra. In the cases of both stellar black holes and supermassive black holes the net polarizations predicted for probable disk and corona models are less than 10 needed. This sensitivity can be achieved, even for sources as faint as 1 milliCrab, in the Gravity and Extreme Magnetism SMEX (GEMS) mission that uses foil mirrors and Time Projection Chamber detectors. Similarities have been pointed out between the timing and the spectral characteristics of low mass X-ray binaries and stellar black hole sources. Polarization measurements for these sources could play a role in determining the configuration of the disk and the neutron star.
A fan-in-wing model with a 1.07-meter span was tested in seven different test sections with cross-sectional areas ranging from 2.2 sq meters to 265 sq meters. The data from the different test sections are compared both with and without correction for wall interference. The results demonstrate that extreme care must be used in interpreting uncorrected VTOL data since the wall interference may be so large as to invalidate even trends in the data. The wall interference is particularly large at the tail, a result which is in agreement with recently published comparisons of flight and large scale wind tunnel data for a propeller-driven deflected-slipstream configuration. The data verify the wall-interference theory even under conditions of extreme interference. A method yields reasonable estimates for the onset of Rae's minimum-speed limit. The rules for choosing model sizes to produce negligible wall effects are considerably in error and permit the use of excessively large models.
Plasma-surface interactions (PSI) play a crucial role in microelectronics fabrication; however, their multiscale nature and array of complex, often unknown interactions make computational modeling of PSIs extremely difficult. To this end, we propose a general neural master equation (NME) framework that uses master equations to describe the dynamics of a molecular process, wherein neural networks learned from atomistic simulations represent unknown transitions between different system states. By leveraging the physics-based structure of master equations and data-driven state transitions, the NME framework promotes generalizability and physics interpretability, and can bridge disparate length and time scales. The framework is demonstrated for multiscale modeling of Si atomic layer etching and reactive ion etching, where the learned NME-based surface kinetic models exhibit good predictive and extrapolative capabilities for predicting experimentally relevant observables as a function of process parameters. The NME-based surface kinetic models obey physical constraints, which are violated in models based on neural ordinary differential equations. The proposed NME framework for multiscale modeling of molecular processes can pave the way for the discovery of new chemistries and materials in atomic-scale plasma processes.
The study of waves and turbulence is vital to the development of future reactor-grade plasma devices developed in the quest for fusion energy. These fluctuations are responsible for moving heat and particles across the magnetic field, and a predictive understanding of them is needed to achieve the density and temperature required to sustain a plasma fusion reaction. While many techniques have been developed for measuring waves and fluctuations, every measurement method has limitations. There are relatively few techniques for measuring very high frequency fluctuations, such as radio frequency waves injected to heat the plasma, unstable waves driven by suprathermal particles, or short wavelength electrostatic waves driven by electron temperature or density gradients. The present project builds upon the proven phase contrast imaging (PCI) technique to extend the response of the diagnostic by orders of magnitude in frequency and almost a factor of ten in spatial resolution. PCI provides a measurement of electron density based on small angle scattering of a CO-2 laser beam by using optical techniques to render a phase shift as an intensity change on a detector. Due to the telecommunications revolution, technological development by manufacturers has focused on components in the near -infrared, so that high- quality lasers and detectors at 1.55 µm are readily available. Shifting PCI design to a new, shorter wavelength has numerous advantages and challenges. Similar detector performance is available with room-temperature arrays with GHz bandwidth, while the detector arrays for 10.6 µm required liquid nitrogen cooling and were therefore limited to a bandwidth of about 1 MHz. Shifting to a shorter wavelength reduces the angle at which the laser beam scatters off of plasma waves, allowing more such scattered components to pass through the aperture of the vacuum vessel port and be collected by the PCI, which increases the spatial resolution. Concomitant with these benefits, various questions of performance arise. At shorter laser wave- length, the sensitivity to mirror and lens quality is increased, the contribution of the laser to the overall system noise is increased, and the sensitivity to vibrations is increased. The custom optical components at the heart of the PCI technique were required to be properly scaled for the shorter wavelength, so fabrication technologies needed to be explored. This project was designed to show that a low noise, high response PCI system at 1.55 µm could be constructed and operated, and then to quantify potential issues to allow extrapolation to a full-size production system providing physics measurements on a large plasma device. The first stage, producing the custom optical component called a Phase Plate, was successfully achieved using two methods. First, an easily reproduced masking and coating technique was able to produce good phase plates with the required parameters. Second, a nanofabrication technique was found to produce extremely high quality phase plates at a competitive price. The PCI constructed with the new phase plates and 1.55 µm laser was found to provide excellent wavelength measurements with the theoretically expected response. The sensitivity to optical surface quality was found to be in line with previous measurements at 10.6 µm. The observed signal-to-noise ratio was similar to the theoretically expected value. The effect of vibrations on PCI was studied with the first measurement of the effect of beam motion on PCI response and comparison to theory, allowing for a quantitative prediction of the effect of vibrations on a production PCI system and the requirements for improved beam stabilization. PCI is an extremely cost-effective method to provide a low noise, absolutely calibrated measurement of plasma fluctuations across a wide spatial scale. This project has shown that a 1.55 µm PCI using modern techniques and components is less expensive than the 10.6 µm PCI of a few years ago, with the largest savings in phase plate fabrication and the infrared detector array.
The main objective of this TOPEX/POSEIDON project is to integrate the accurately measured sea surface topography, as resolved by both TOPEX/POSEIDON radar altimeters, into the above-mentioned quantitative studies of the short- and long-term variations in the mesoscale ocean dynamics of the Nordic Seas south of 66 deg N. This implies: (1) comparison and validation of the capability to resolve the general basin-scale circulation and the mesoscale variability by, respectively, radar altimeters and numerical ocean circulation models; (2) calibration and validation of the altimeter-derived sea surface topography against in situ measurements from research vessels and moorings, particularly under extreme wind and wave conditions; and (3) improved monitoring and understanding of the flux variations between the North Atlantic and the Nordic Seas, both on the short and seasonal time scales.
Electricity grid operators around the world face a dual challenge; withstanding increasingly severe weather and the longer term impacts of climate change, while simultaneously decarbonizing. Extreme weather events such as heat waves and droughts are rising in both severity and frequency, which is threatening the reliability of electricity grids through increased demand, generation capacity losses, and equipment failures. Consequently, incorporating hydrometeorological stressors into computational power systems analysis is becoming an even more critical tool in long term planning and short term operations. However, there is a general lack of open-source customizable grid simulation software capable of exhaustively stress testing the grid under hydrometeorological uncertainty, and/or examining potential risk mitigation pathways. A related, persistent challenge for power system modelers is striking an appropriate balance between model fidelity (e.g. spatial scale and time resolution) and computational tractability (wall clock run-time). In this study, we are proposing a solution to this problem with open-source software that allows users to seamlessly customize the scale and track the accuracy of grid operations models. Our approach allows users to search over numerous model parameters (network topology, mathematical formulation, economic hurdle rates, and transmission line scaling) to identify model instantiations that accommodate experimental design. Further, we use this approach to demonstrate the importance of including extreme weather events in model validation and model selection. Focusing on the occurrence of heatwaves and droughts in the U.S. Western Interconnection, we examine role of extreme events in balancing tradeoffs between model fidelity and run-time at the model design stage.