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NASA NTRS2019

High Angular Resolution Astrophysics: Resolving Stellar Surface Features

We are now in an era where we can image details on the surfaces of stars. When resolving stellar surfaces, we see that every surface is uniquely complicated. Each imaged star provides insight into not only the stellar surface structures, but also the stellar interiors suggesting constraints on evolution and dynamo models. As more resources become operational in the coming years, imaging stellar surfaces should become commonplace for revealing the true nature of stars. Here, we discuss the main types of stars for which imaging surface features is currently useful and what improved observing techniques would provide for imaging stellar surface features.

Rachael M. Roettenbacher↗

NASA NTRS2020

Measurements of Turbulent Convection Speeds in Multistream Jets Using Time-Resolved PIV

Convection speeds of turbulent velocities in jets, including multi-stream jets with and without flight stream, were measured using an innovative application of time-resolved particle image velocimetry. The paper describes the unique instrumentation and data analysis that allows the measurement to be made. Extensive data is shown that relates convection speed, mean velocity, and turbulent velocities for multiple jet cases. These data support the overall observation that the local turbulent convection speed is roughly that of the local mean velocity, biased by the relative intensity of turbulence.

Particle Image Velocimetry; Convective Velocity; J↗

NASA NTRSDate not supplied

Scale resolving simulations of the NASA Juncture Flow Model using the LAVA solver

Two distinct simulation methodologies: Delayed Detached Eddy Simulation (DDES) and stress based Wall-modelled Large Eddy Simulation (WMLES) are evaluated using structured overset curvilinear grids for the NASA juncture flow model. While both methodologies are shown to mitigate the primary shortcomings of steady state Reynolds Averaged Navier Stokes(RANS) simulations, several unresolved aspects are identified. Strong sensitivity to RANS-typegrid refinement is observed in the DDES with a substantial deterioration of the solution quality with increasing spatial resolution associated with deficiencies in the shielding function. Mean profiles for attached boundary layers on the fuselage show spurious inflections suggesting modelled stress depletion on finer grids. Lower numerical dissipation in terms of spatial discretization and time step size is seen to improve the solution quality, and the advantage of using RC and QCR2000 corrections in the underlying RANS closure is demonstrated for DDES on RANS-type meshes. Equilibrium Wall-Modelled LES used grids that resolved the tripping dots over the fuselage nose and the wing leading edge, consistent with the experiment setup. These simulations resulted in a cost-competitive approach compared to DDES on RANS-type grids. Although the agreement between WMLES predictions of first and second order single point statistics with experimental measurements is promising, a fundamental shortcoming is noted in terms of an overshoot in streamwise momentum in corner regions of the wing-fuselage juncture. This excess momentum subsequently delays the onset of separation,thereby resulting in an underprediction in length of the separation bubble. Some quantitative sensitivity to numerical discretization is observed; lowering of numerical dissipation shows better agreement with the experiment.

T^3↗

NASA NTRS2021

An Evaluation of Size-Resolved Cloud Microphysics Scheme Numerics for use with Radar Observations Part II: Condensation and Evaporation

Accurate numerical modeling of clouds and precipitation is essential for weather forecasting and climate change research. While size-resolved (bin) cloud microphysics models predict particle size distributions without imposing shapes, results are subject to artificial size distribution broadening owing to numerical diffusion associated with various processes. Whereas Part 1 addressed collision-coalescence, here we investigate numerical diffusion that occurs in solving condensation and evaporation. In a parcel model framework, all of the numerical schemes examined converge to one solution of condensation and evaporation as the mass grid is refined, and the advection-based schemes are recommended over the reassigning schemes. Including Eulerian vertical advection in a column limits the convergence to some extent, but that limitation occurs at a sufficiently fine mass grid, and the number of iterations in solving vertical advection should be minimized to reduce numerical diffusion. Insubstantial numerical diffusion in solving condensation can be amplified if collision-coalescence is also active, which in turn can be substantially diminished if turbulence effects on collision are incorporated. Large-eddy simulations of a drizzling stratocumulus field reveal that changes in moments of Doppler spectra obtained using different mass grids are consistent with those obtained from the simplified framework, and that spectral moments obtained using a mass grid designed to effectively reduce numerical diffusion are generally closer to observations. Notable differences between the simulations and observations still exist, and our results suggest a need to consider whether factors other than numerical diffusion in the fundamental process schemes employed can cause such differences.

Cloud microphysics↗

NASA NTRS2020

The HadGEM3-GA7.1 radiative kernel: the importance of a well-resolved stratosphere

We present top-of-atmosphere and surface radiative kernels based on the atmospheric component (GA7.1) of the HadGEM3 general circulation model developed by the UK Met Office. We show that the utility of radiative kernels for forcing adjustments in idealised CO2 perturbation experiments is greatest where there is sufficiently high resolution in the stratosphere in both the target climate model and the radiative kernel. This is because stratospheric cooling to a CO2 perturbation continues to increase with height, and low-resolution or low-top kernels or climate model output are unable to fully resolve the full stratospheric temperature adjustment. In the sixth phase of the Coupled Model Intercomparison Project (CMIP6), standard atmospheric model data are available up to 1 hPa on 19 pressure levels, which is a substantial advantage compared to CMIP5. We show in the IPSL-CM6A-LR model where a full set of climate diagnostics are available that the HadGEM3-GA7.1 kernel exhibits linear behaviour and the residual error term is small, as well as from a survey of kernels available in the literature that in general low-top radiative kernels underestimate the stratospheric temperature response. The HadGEM3-GA7.1 radiative kernels are available at https://doi.org/10.5281/zenodo.3594673 (Smith, 2019).

radiative kernels↗

NASA NTRS2020

Resolving the Soft X-Ray Ultrafast Outflow in PDS 456

Past X-ray observations of the nearby luminous quasar PDS 456 (at z = 0.184) have revealed a wide-angle accretion disk wind with an outflow velocity of ∼−0.25c, as observed through observations of its blueshifted iron K-shell absorption line profile. Here we present three new XMM-Newton observations of PDS 456: one in 2018 September where the quasar was bright and featureless and two in 2019 September, 22 days apart, occurring when the quasar was five times fainter and where strong blueshifted lines from the wind were present. During the second 2019 September observation, three broad (σ = 3000 km s(exp -1)) absorption lines were resolved in the high-resolution Reflection Grating Spectrometer spectrum that are identified with blueshifted O VIII Lyα, Ne IX Heα, and Ne X Lyα. The outflow velocity of this soft X-ray absorber was found to be v/c = -0.258 ± 0.003, fully consistent with an iron K absorber with v/c = -0.261 ± 0.007. The ionization parameter and column density of the soft X-ray component (log ξ = 3.4, N(sub H) = 2 × 10(exp 21) cm(exp -2)) outflow was lower by about 2 orders of magnitude when compared to the high-ionization wind at iron K (log ξ = 5, N(sub H) = 7 × 10(exp 23) cm(exp -2). Substantial variability was seen in the soft X-ray absorber between the 2019 observations, declining from N(sub H) = 10(exp 23) to 10(exp 21) cm(exp -2) over 20 days, while the iron K component was remarkably stable. We conclude that the soft X-ray wind may originate from an inhomogeneous wind streamline passing across the line of sight that, due to its lower ionization, is located further from the black hole, on parsec scales, than the innermost disk wind

Active galactic nuclei↗

NASA NTRS2021

Second Time-Resolved Observations of Precipitation Structure and Storm Intensity With a Constellation of Smallsats (TROPICS) Mission Applications Workshop

The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission is a constellation of state-of-the-science observing platforms that will measure temperature and humidity soundings and precipitation with spatial resolution comparable to current operational passive microwave (PMW) sounders but with unprecedented temporal resolution (Mission Website).1 TROPICS is a cost-capped ($30.2 million), Venture-class mission funded by the NASA Earth Science Division (ESD) and led by Principal Investigator Dr. William Blackwell from the Massachusetts Institute of Technology Lincoln Laboratory (MIT LL). The mission consists of a constellation of six, three-unit (3U) CubeSats (approximately 10×10×34 cm), each hosting a 12-channel PMW spectrometer based on the Micro-sized Microwave Atmospheric Satellite-2 (MicroMAS-2) developed at MIT LL, but with a substantially improved design. TROPICS will provide imagery near 91 and 205 GHz, temperature sounding near 118 GHz, and moisture sounding near 183 GHz. Spatial resolution at nadir will be around 27 km for temperature and 17 km for moisture and precipitation with a swath width of approximately 2,000 km from a 550-km orbit altitude. Both the spatial resolution and swath width are similar to the Advanced Technology Microwave Sounder (ATMS) that is being flown as part of the Suomi National Polar-orbiting Partnership (SNPP) and National Oceanic and Atmospheric Administration (NOAA) Joint Polar Satellite System (JPSS). In addition, TROPICS meets many of the requirements outlined in the 2007 Decadal Survey for the Precision and All-Weather Tempera-ture and Humidity (PATH) mission, which was originally envisioned as a microwave instrument in geostationary orbit. TROPICS enables temporal resolution approaching that of geostationary orbit but at a much lower cost, demonstrating a technology that could impact the design of future Earth-observing missions. The satellites for the TROPICS mission were delivered to NASA in 2019 for launches planned in the 2021–2022 timeframe. The primary mission objective of TROPICS is to relate temperature, humidity, and precipitation structure to the evolution of tropical cyclone (TC) intensity.

remote sensing↗

NASA NTRSDate not supplied

Scale-Resolving Simulations of a Supersonic Retro-Propulsion Concept For Mars Entry, Descent, and Landing

Supersonic retro-propulsion (SRP) is a deceleration technology that could enable largerpayloads and potentially humans to be brought from space to the surface of Mars safely.Accurate and reliable CFD predictions are needed to help design future Mars entry, descent,and landing (EDL) vehicles due to the cost and limitations of wind tunnel tests. TypicalCFD approaches struggle at points along the Mars EDL trajectory with high enough altitude(low enough ambient pressure) that the SRP motor plumes are over-expanded. This workdemonstrates how high-order scale-resolving simulations on Cartesian AMR grids can provideaccurate and reliable time-averaged aerodynamic loads on the vehicle for this challengingflow regime. Greater than second order convergence in the time-averaged integrated axialforce𝐶𝐴is obtained across the three finest mesh resolutions simulated, and the estimateduncertainty is smaller than the unsteady standard deviation – demonstrating the accuracy andreliability of the method. Although costly, this approach can yield higher confidence in𝐶𝐴thanpreviously obtained in a reasonable turnaround time and is within reach for a few points in thetrajectory (i.e. Mach 2.4, 2.52, and 2.78). Further computational performance and numericalmethods improvements are needed to reduce the cost enough to bring this method into the EDLengineering design cycle.

S&M↗

NASA NTRS2021

Precise Timing and Phase-resolved Spectroscopy of the Young Pulsar J1617-5055 with NuSTAR

We report on a Nuclear Spectroscopic Telescope Array (NuSTAR) observation of the young, energetic pulsar PSR J1617-5055. Parkes Observatory 3 GHz radio observations of the pulsar (taken about 7 yr before the NuSTAR observations) are also reported here. NuSTAR detected pulsations at a frequency of f ≍ 14.4 Hz (P ≍ 69.44 ms) and, in addition, the observation was long enough to measure the source's frequency derivative, ḟ ≈ -2.8 X10^(-11) Hz/s. We find that the pulsar shows one peak per period at both hard X-ray and radio wavelengths, but that the hard X-ray pulse is broader (having a duty cycle of ~0.7), than the radio pulse (having a duty cycle of ~0.08). Additionally, the radio pulse is strongly linearly polarized. J1617's phase-integrated hard X-ray spectrum is well fit by an absorbed power-law model, with a photon index Γ = 1.59 ± 0.02. The hard X-ray pulsations are well described by three Fourier harmonics, and have a pulsed fraction that increases with energy. We also fit the phase-resolved NuSTAR spectra with an absorbed power-law model in five phase bins and find that the photon index varies with phase from Γ = 1.52 ± 0.03 at phases around the flux maximum to Γ = 1.79 ± 0.06 around the flux minimum. Last, we compare our results with other pulsars whose magnetospheric emission is detected at hard X-ray energies and find that, similar to previous studies, J1617's hard X-ray properties are more similar to the MeV pulsars than the GeV pulsars.

Neutron Stars↗

NASA NTRS2020

Spectroscopy of the first resolved strongly lensed Type Ia supernova iPTF16geu

We report the results from spectroscopic observations of the multiple images of the strongly lensed Type Ia supernova (SN Ia), iPTF16geu, obtained with ground-based telescopes and the Hubble Space Telescope (HST). From a single epoch of slitless spectroscopy with HST, we resolve spectra of individual lensed supernova images for the first time. This allows us to perform an independent measurement of the time-delay between the two brightest images, Δt = 1.4 ± 5.0 d, which is consistent with the time-delay measured from the light curves. We also present measurements of narrow emission and absorption lines characterizing the interstellar medium in the SN Ia host galaxy at z = 0.4087, as well as in the foreground lensing galaxy at z = 0.2163. We detect strong Na ID absorption in the host galaxy, indicating that iPTF16geu belongs to a subclass of SNe Ia displaying ‘anomalously’ large Na ID column densities compared to dust extinction derived from light curves. For the lens galaxy, we refine the measurement of the velocity dispersion, σ = 129 ± 4 km/s, which significantly constrains the lens model. We use ground-based spectroscopy, boosted by a factor ∼70 from lensing magnification, to study the properties of a high-z SN Ia with unprecedented signal-to-noise ratio. The spectral properties of the supernova, such as pseudo-Equivalent widths of several absorption features and velocities of the Si II-line, indicate that iPTF16geu is a normal SN Ia. We do not detect any significant deviations of the SN spectral energy distribution from microlensing of the SN photosphere by stars and compact objects in the lensing galaxy.

J Johansson↗

NASA NTRS2022

Probing the High-energy Gamma-Ray Emission Mechanism in the Vela Pulsar via Phase-resolved Spectral and Energy-dependent Light-curve Modeling

Recent kinetic simulations sparked a debate regarding the emission mechanism responsible for pulsed GeV γ-ray emission from pulsars. Some models invoke curvature radiation, while other models assume synchrotron radiation in the current sheet. We interpret the curved spectrum of the Vela pulsar as seen by H.E.S.S. II (up to ∼100 GeV) and the Fermi Large Area Telescope to be the result of curvature radiation due to primary particles in the pulsar magnetosphere and current sheet. We present phase-resolved spectra and energy-dependent light curves using an extended slot gap and current-sheet model, invoking a step function for the accelerating electric field as motivated by kinetic simulations. We include a refined calculation of the curvature radius of particle trajectories in the lab frame, impacting the particle transport, predicted light curves, and spectra. Our model reproduces the decrease of the flux of the first peak relative to the second one, evolution of the bridge emission, near-constant phase positions of peaks, and narrowing of pulses with increasing energy. We can explain the first of these trends because we find that the curvature radii of the particle trajectories in regions where the second γ-ray light-curve peak originates are systematically larger than those associated with the first peak, implying that the spectral cutoff of the second peak is correspondingly larger. However, an unknown azimuthal dependence of the E field, as well as uncertainty in the precise spatial origin of the GeV emission, precludes a simplistic discrimination of emission mechanisms.

Monica Barnard↗

NASA NTRSDate not supplied

ArcjetCV: a new machine learning application for extracting time-resolved recession measurements from arc jet test videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession, sting arm motion, and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials.

machine learning↗

NASA NTRSDate not supplied

Progress Toward Evaluating Roughness-Resolved Aerothermodynamic Simulations for the Mars Sample Return Earth Entry System

This work pursues the efficient Navier-Stokes simulation, using NASA’s standard LAURA and DPLR simulation tools, of the flowfield and convective heating resulting from the patterned-roughness surface of the Mars Sample Return (MSR) Earth Entry System (EES). This type of simulation has been infeasible for past NASA missions. However, for EES, the combination of a patterned roughness heatshield approximated with a sinusoidal pattern, the zero degrees angle of attack nominal flow, and the supersonic boundary layer edge Mach number, all combine to make these roughness resolved grid simulations feasible. The patterned roughness and zero degrees angle of attack nominal flow allow the simulation domain to be reduced to a thin axial flowfield slice that captures a minimum of single period of the roughness pattern. With a periodic boundary condition applied along the boundaries of this slice, simulation on the reduced domain is identical to the full domain but with significant cost saving. The supersonic boundary layer edge Mach number prevents the upstream influence, which allows the smooth stagnation region to be frozen. This freezing of the stagnation region flow is required because of the numerical instability resulting from the tight spacing of the grid in the axial direction as the stagnation point is approached. Applying the developed analysis approach to a peak heating EES case results in a roughness augmentation factor for the convective heating of 1.32, which agrees well with correlations that predict values between 1.30 and 1.37. Analysis approach developed in this work provides the framework for future studies of turbulence modeling impacts and the influence of an ablating surface.

Earth Entry System↗

NASA NTRS2021

Stokes resolved differential temperature: an important metric of polarimetric precision in the long-wave infrared

In remote sensing, radiometric measurements taken in the mid-wave infrared and beyond (λ >3μm) are commonly reported in units of Kelvin by utilizing Planck’s radiation law to relate measured radiance and target brightness temperature (Tb). Thus, it is desirable to match this formalism in thermal polarimetry and report the unnormalized Stokes parameters in units of K instead of radiance (Wm−2sr−1). This approach also al-lows common performance metrics in long-wave infrared (LWIR) imaging such as Noise Equivalent DifferentialTemperature (NEDT) to be modified and extended to metrics of polarimetric accuracy and precision. However, since the relationship between measured radiance and Tb are non-linear, the conversion of I, Q, and U in units of radiance to Tb,Tb,Q, and Tb,U in K is ambiguous. As a solution a metric of performance for thermal linear Stokes polarimetry, the Stokes resolved differential temperature (SRDT), is introduced.

polarimetry↗

NASA NTRSDate not supplied

ArcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

machine learning↗

NASA NTRSDate not supplied

Spectrally Resolving High Redshift Dual AGNs with the Line Emission Mapper

The Line Emission Mapper (LEM) is an X-ray Probe-class Mission concept which combines 1-2 eV spectral resolution in the soft X-ray band (0.2-2 keV) with an effective area of ~2600 cm^2 at 1 keV, and 10’’ HPD over a large 30'x30' field of view. The mission will directly address the Astro2020 Decadal Report’s Priority Area of Unveiling the Drivers of Galaxy Growth through the study of merging galaxies, which offer one of the most dramatic channels for galaxy growth and evolution and can potentially trigger both star formation and supermassive black hole (SMBH) growth. Dual and binary AGNs in late-stage mergers are predicted to be a critical stage of merger-induced SMBH growth and coincide with the most transformative period for the host galaxies. Thus, dual and binary AGNs represent ideal laboratories for studying examples of SMBH-galaxy co-evolution. Recent discoveries of dual AGNs at redshifts of z~>2 have been made via optical observations, but such dual AGNs are inaccessible to current X-ray observatories due to a lack of instrumental capabilities, including sensitivity, spectral and spatial resolution. LEM will be uniquely suited to study AGNs at z > 3, where the intrinsic X-ray power law continuum and Iron K alpha emission line - a nearly ubiquitous signpost for AGN accretion – are redshifted into the LEM bandpass. In this poster, we present a simulation-based study on LEM’s ability to discern dual, binary, and/or clustered AGNs at high redshift. We demonstrate the unique capabilities of LEM to spectrally resolve Iron K-alpha lines emitted by distinct AGNs with sufficient line-of-sight velocity differences, even in cases of convolved point sources. Using a suite of simulations probing a range of velocity differences, line strengths, and column densities, we demonstrate LEM’s ability to constrain the spectral properties of dual AGNs at z>3 for a variety of physically realistic pairings. LEM will uniquely provide crucial constraints on dual AGN environments and activity as a function of redshift and will complement optical and infrared observations from upcoming Extremely Large Telescopes.

Ryan W Pfeifle↗

NASA NTRS2023

A SmallSat Concept to Resolve Diurnal and Vertical Variations of Aerosols, Clouds, and Boundary Layer Height

A SmallSat mission concept is formulated here to carry out Time-varying Optical Measurements of Clouds and Aerosol Transport (TOMCAT) from space while embracing low-cost opportunities enabled by the revolution in Earth science observation technologies. TOMCAT’s “around-the-clock” measurements will provide needed insights and strong synergy with existing Earth observation satellites to 1) statistically resolve diurnal and vertical variation of cirrus cloud properties (key to Earth’s radiation budget), 2) determine the impacts of regional and seasonal planetary boundary layer (PBL) diurnal variation on surface air quality and low-level cloud distributions, and 3) characterize smoke and dust emission processes impacting their long-range transport on the subseasonal to seasonal time scales. Clouds, aerosol particles, and the PBL play critical roles in Earth’s climate system at multiple spatiotemporal scales. Yet their vertical variations as a function of local time are poorly measured from space. Active sensors for profiling the atmosphere typically utilize sun-synchronous low-Earth orbits (LEO) with rather limited temporal and spatial coverage, inhibiting the characterization of spatiotemporal variability. Pairing compact active lidar and passive multiangle remote sensing technologies from an inclined LEO platform enables measurements of the diurnal and vertical variability of aerosols, clouds, and aerosol-mixing-layer (or PBL) height in tropical-to-midlatitude regions where most of the world’s population resides. TOMCAT is conceived to bring potential societal benefits by delivering its data products in near–real time and offering on-demand hazard-monitoring capabilities to profile fire injection of smoke particles, the frontal lofting of dust particles, and the eruptive rise of volcanic plumes.

John E. Yorks↗

NASA NTRSDate not supplied

ArcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

machine learning↗