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At least 1,171 records · Page 65

The Habitability of Proxima Centauri b: I. Irradiation, Rotation and Volatile Inventory From Formation to the Present

Proxima b is a planet with a minimum mass of 1.3 M(sub ⨁) orbiting within the habitable zone (HZ) of Proxima Centauri, a very low-mass, active star and the Sun’s closest neighbor. Here we investigate a number of factors related to the potential habitability of Proxima b and its ability to maintain liquid water on its surface. We set the stage by estimating the current high-energy irradiance of the planet and show that the planet currently receives 30 times more extreme-UV radiation than Earth and 250 times more X-rays. We compute the time evolution of the star’s spectrum, which is essential for modeling the flux received over Proxima b’s lifetime. We also show that Proxima b’s obliquity is likely null, and its spin is either synchronous or in a 3:2 spin-orbit resonance, depending on the planet’s eccentricity and level of triaxiality. Next, we consider the evolution of Proxima b’s water inventory. We use our spectral energy distribution to compute the hydrogen loss from the planet with an improved energy-limited escape formalism. Despite the high level of stellar activity, we find that Proxima b is likely to have lost less than an Earth ocean’s worth of hydrogen (EO(sub H)) before it reached the HZ 100–200 Myr after its formation. The largest uncertainty in our work is the initial water budget, which is not constrained by planet formation models. We conclude that Proxima b is a viable candidate habitable planet.

Proxima Cen↗

New Insights into the First Two PSP Solar Encounters Enabled by Modeling Analysis with ADAPT-WSA

Parker Solar Probe's (PSP's) unique orbital path allows us to observe the solar wind closer to the Sun than ever before. Essential to advancing our knowledge of solar wind and energetic particle formation is identifying the sources of PSP observations. We report on results for the first two PSP solar encounters derived using the Wang–Sheeley–Arge (WSA) model driven by Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model maps. We derive the coronal magnetic field and the 1 R⊙ source regions of the PSP-observed solar wind. We validate our results with the solar wind speed and magnetic polarity observed at PSP. When modeling results are very reliable, we derive time series of model-derived spacecraft separation from the heliospheric current sheet, magnetic expansion factor, coronal hole boundary distance, and photospheric field strength along the field lines estimated to be connected to the spacecraft. We present new results for Encounter 1, which show time evolution of the far-side mid-latitude coronal hole that PSP corotates with. We discuss how this evolution coincides with solar wind speed, density, and temperature observed at the spacecraft. During Encounter 2, a new active region emerges on the solar far side, making it difficult to model. We show that ADAPT-WSA output agrees well with PSP observations once this active region rotates onto the near side, allowing us to reliably estimate the solar wind sources retrospectively for most of the encounter. We close with ways in which coronal modeling enables scientific interpretation of these encounters that would otherwise not have been possible.

Solar wind↗

Dayside Transient Phenomena and Their Impact on the Magnetosphere and Ionosphere

Dayside transients, such as hot flow anomalies, foreshock bubbles, magnetosheath jets, flux transfer events, and surface waves, are frequently observed upstream from the bow shock, in the magnetosheath, and at the magnetopause. They play a significant role in the solar wind-magnetosphere-ionosphere coupling. Foreshock transient phenomena, associated with variations in the solar wind dynamic pressure, deform the magnetopause, and in turn generates field-aligned currents (FACs) connected to the auroral ionosphere. Solar wind dynamic pressure variations and transient phenomena at the dayside magnetopause drive magnetospheric ultra low frequency (ULF) waves, which can play an important role in the dynamics of Earth’s radiation belts. These transient phenomena and their geoeffects have been investigated using coordinated in-situ spacecraft observations, spacecraft-borne imagers, ground-based observations, and numerical simulations. Cluster, THEMIS, Geotail, and MMS multi-mission observations allow us to track the motion and time evolution of transient phenomena at different spatial and temporal scales in detail, whereas ground-based experiments can observe the ionospheric projections of transient magnetopause phenomena such as waves on the magnetopause driven by hot flow anomalies or flux transfer events produced by bursty reconnection across their full longitudinal and latitudinal extent. Magnetohydrodynamics (MHD), hybrid, and particle-in-cell (PIC) simulations are powerful tools to simulate the dayside transient phenomena. This paper provides a comprehensive review of the present understanding of dayside transient phenomena at Earth and other planets, their geoeffects, and outstanding questions.

Bow shock↗

Large-Eddy Simulations of Marine Boundary Layer Clouds Associated with Cold-Air Outbreaks during the ACTIVATE Campaign. Part II: Aerosol–Meteorology–Cloud Interaction

Aerosol effects on micro/macrophysical properties of marine stratocumulus clouds over the western North Atlantic Ocean (WNAO) are investigated using in situ measurements and large-eddy simulations (LES) for two cold-air outbreak (CAO) cases (28 February and 1 March 2020) during the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). The LES is able to reproduce the vertical profiles of liquid water content (LWC), effective radius reff and cloud droplet number concentration Nc from fast cloud droplet probe (FCDP) in situ measurements for both cases. Furthermore, we show that aerosols affect cloud properties (N c , r eff , and LWC) via the prescribed bulk hygroscopicity of aerosols (¯k) and aerosol size distribution characteristics. N c , r eff , and liquid water path (LWP) are positively correlated to ¯κ and aerosol number concentration (N a ) while cloud fractional cover (CFC) is insensitive to ¯κ and aerosol size distributions for the two cases. The realistic changes to aerosol size distribution (number concentration, width, and the geometrical diameter) with the same meteorology state allow us to investigate aerosol effects on cloud properties without meteorological feedback. We also use the LES results to evaluate cloud properties from two reanalysis products, ERA5 and MERRA-2. Compared to LES, the ERA5 is able to capture the time evolution of LWP and total cloud coverage within the study domain during both CAO cases while MERRA-2 underestimates them.

Cloud forcing↗

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided valuable insight on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus were segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution available for capturing cloud initiation, growth, and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool and its results for cloud fields sampled throughout CAMP2EX by the airborne P-3. Cloud tracks were selected from about 10 flights to form ensembles, specific groups of tracks occurring in a region with airborne sampling. Cloud lifecycle properties, including duration and maximum area, are calculated for all ensemble members, and analyzed for cloud behavior and P-3 coincidences. By following this strategy, we quantitatively assess the degree of airborne sampling for specific cloud classes defined by the lifecycle calculations. We can summarize which cloud classes had more sampling, the stage of development during sampling, and general differences in character (e.g., isolated congestus vs. cold-pool producer).

Cloud Tracking↗

A Machine Learning-Based Approach to Time-Series Wave Identification in the Solar Wind

The Wind spacecraft has yielded several decades of high-resolution magnetic field data, a large fraction of which displays small-scale structures. In particular, the solar wind is full of wavelike fluctuations that appear in both the field magnitude and its components. The nature of these fluctuations can be tied to the properties of other structures in the solar wind, such as shocks, that have implications for the time evolution of the solar wind. As such, having a large collection of wave events would facilitate further study of the effects that these fluctuations have on solar wind evolution. Given the large volume of magnetic field data available, machine learning is the most practical approach to classifying the myriad small-scale structures observed. To this end, a subset of Wind data is labeled and used as a training set for a multi-branch 1D convolutional neural network aimed at classifying circularly polarized wave modes. Using this algorithm, a preliminary statistical study of one year of data is performed, yielding about 300,000 wave intervals out of about 5,000,000 solar wind intervals. The wave intervals come about more often in the fast solar wind and at higher temperatures, and the number of waves per day is highly periodic. This machine learning-based approach to wave detection has the potential to be a powerful, inexpensive way to catalog waves throughout decades of spacecraft data.

Samuel Fordin↗

Solidification Furnace for In Situ Observation of Bulk Transparent Systems and Image Analysis Methods

This paper aims to describe the experimental framework of the Directional Solidification Insert (DSI), installed onboard the International Space Station (ISS), dedicated to the in situ and real-time characterization of the dynamic selection of the solid-liquid interface morphology in bulk samples of transparent materials under diffusive growth conditions. The in situ observation of the solid-liquid interface is an invaluable tool for gaining knowledge on the time-evolution of the interface pattern because the initial morphological instability evolves nonlinearly and undergoes a reorganization process. The result of each experiment, characterized by the sample concentration, a thermal gradient and a pulling rate, is a large number of images. Interpretation of these images necessitates a robust identification of each cell/dendrite position and size during the entire solidification. Several image analysis methods have been developed to achieve this goal reliably despite varying contrast and noise levels, and are described in details. Typical solidification experiments are presented and the dynamics of the pattern formation are analyzed to illustrate the application of the image analysis methods.

Programming languages↗

Preferential Acceleration of Heavy Ions in a Spontaneously Fragmenting Flare Current Sheet

We study the ion acceleration in a mesoscale, spontaneously fragmenting flare current sheet (SFCS) characterized by the presence of a plasmoid cascade. The main subject of our investigation is to determine whether and how plasmoid cascades at intermediate scales in a fragmented current sheet of a solar flare can impact the (preferential) acceleration of specific ions. The time evolution of the SFCS is obtained from high-resolution 2.5D MHD simulations. The ion trajectories (in the background fields resulting from the MHD model), energies, and pitch angles are calculated using a relativistic test-particle code based on the half-acceleration–rotation–half-acceleration method. For light ions, the main acceleration effects of electromagnetic fields within the SFCS are analyzed using the guiding center approximation. We identify regions with the most-efficient ion acceleration within the SFCS, the accelerator efficiency, and spectra of the accelerated ions. The influence of the charge-to-mass ratio on ion behavior is also studied and resulting ion abundances are compared with observational data. The main ion acceleration takes place in the regions with a strong polarization term, which is part of the first-order Fermi acceleration. Because the term is mass dependent, heavier ions undergo preferential acceleration. The ion energy spectra, abundance-enhancement factors, and differential fluxes, obtained from the model, exhibit power-law profiles, in agreement with observed solar energetic particle events. Nonetheless, the obtained slopes for the abundance-enhancement factor do not exactly match the observed data. The computed slopes and profiles are not sensitive to changes in the initial plasma temperature.

David Kramoliš↗

Supersonic Free-Flight Dynamics Testing in the Stratosphere

A new technique for obtaining stratospheric free-flight dynamics data for atmospheric entry capsules is described. The Stratospheric Projectile Experiment of Entry Dynamics (SPEED) represents a new approach to characterizing the free-flight dynamics of vehicles in the supersonic and transonic regime of flight. The SPEED test architecture leverages a stratospheric balloon and 3D-printed flight system in a novel two-stage configuration to deliver test articles to supersonic conditions in the atmosphere which achieve dynamic similitude with a full-scale vehicle. Designed to address the limitations of existing test facilities, SPEED captures the complete time evolution of a vehicle’s dynamic state while producing a statistically significant number of observed flight trajectories to address the stochastic nature of the wake-driven dynamic stability phenomenon. SPEED was developed over two years at NASA Ames Research Center. The inaugural flight of the SPEED test platform was conducted in the summer of 2024 where scaled capsules of the Mars Sample Return Earth Entry System and Dragonfly entry vehicle were tested. This paper describes the motivation for a new test architecture, operational constraints and achievable flight test envelopes, the design and development of the SPEED concept, and results from the demonstration flight. Techniques for estimating the dynamic aerodynamic characteristics and atmospheric conditions for each test article individually and as a collective are also discussed.

Entry Vehicle↗

Design and Technology Maturation of the Stratospheric Projectile Experiment of Entry Dynamics

A new technique for obtaining stratospheric free-flight dynamics data for atmospheric entry capsules is described. The Stratospheric Projectile Experiment of Entry Dynamics (SPEED) represents a new approach to characterizing the free-flight dynamics of vehicles in the supersonic and transonic regime of flight. The SPEED test architecture leverages a stratospheric balloon and 3D-printed flight system in a novel two-stage configuration to deliver test articles to supersonic conditions in the atmosphere which achieve dynamic similitude with a full-scale vehicle. Designed to address the limitations of existing test facilities, SPEED captures the complete time evolution of a vehicle’s dynamic state while producing a statistically significant number of observed flight trajectories to address the stochastic nature of the wake-driven dynamic stability phenomenon. SPEED was developed over two years at NASA Ames Research Center. This presentation describes the motivation for a new test architecture, operational constraints and achievable flight test envelopes, the design, and development of the SPEED concept.

Dynamic Stability↗

Science Applications From NAST-I Measurements: PBL Thermodynamic Characterization and Variation

The National Airborne Sounder Testbed-Interferometer (NAST‑I) suborbital system serves as a spaceborne instrument simulator and pathfinder for future satellite capabilities and airborne science experiments. The NAST‑I measurements are made to advance understanding of science critical for weather, climate, chemistry, and radiation applications. NAST‑I provides high-spatial linear resolution equal to 13% of the aircraft altitude at nadir, and high-spectral resolution (0.25 cm -1 ) measurements within the spectral region of 645–2700 cm ‑1 . NAST-I measurements and corresponding geophysical retrievals and their potential benefits toward improved atmospheric state and composition characterizations needed for air quality, wildfire, and other science applications have been published in many Peer-reviewed papers. NAST-I capabilities could be of particular importance toward enhancing characterization and understanding of the Planetary Boundary Layer (PBL). Initial results of PBL thermodynamic characterization and variation with its time evolution from NAST-I measurements will also be presented.

PBL↗

PBL Thermodynamic Characterization and Its Variability From NAST-I During the Wh2yMSIE Field Campaign

The National Airborne Sounder Testbed-Interferometer (NAST‑I) suborbital system (<2.6 km IFOV; 0.25 cm-1 within 645–2700 cm‑1) serves as a spaceborne instrument simulator and pathfinder for future satellite capabilities and airborne science experiments. The NAST‑I measurements are made to advance understanding of science critical for weather, climate, chemistry, and radiation applications. Here we present some groundbreaking capabilities of NAST-I measurements and corresponding geophysical retrievals and their potential benefits toward improved atmospheric state and composition characterizations needed for science applications of particular importance toward enhancing characterization and understanding of the Planetary Boundary Layer (PBL). Initial results of PBL height estimation and thermodynamic characterization and their time evolution from NAST-I measurements during the WH2yMSIE field campaign are presented.

Daniel K Zhou↗

Global Magnetic Reconnection with Weakly Shocked Solar Wind During Geomagnetic Storms

The solar wind and magnetic field emanating from the sun typically reaches Earth moving at a super-Alfvénic velocity (multiple times the local Alfvén wave speed). This leads to the formation of a bow shock upstream of the planet where the plasma is slowed and heated and the interplanetary magnetic field is compressed before it interacts with Earth's magnetic field. However, a number of recent geomagnetic storm events have been associated with sustained intervals of nearly or indeed fully sub-Alfvénic flows. A weakly- or un-shocked magnetosheath changes the conditions for magnetic reconnection at the magnetopause and subsequently the storm-time evolution of the magnetosphere. We perform Multiscale Atmosphere-Geospace Environment (MAGE) simulations of three different geomagnetic storms each containing a period of nearly or fully sub-Alfvénic solar wind driving and examine the properties of global reconnection. The structure of the night-side magnetosphere and polar cusps are also examined. The dynamical evolution of the global magnetosphere during strong driving represents a key science target for the NASA Heliophysics System Observatory, particularly Magnetospheric Multiscale (MMS) targeting magnetotail/magnetopause reconnection and Tandem Reconnection and Cusp Electrodynamics Reconnaissance Satellites (TRACERS) observing ion dispersion in the cusps.

Brandon Burkholder↗

Systems and methods for determining optimal parameters for dynamic quantum clustering analyses

In the present work, quantum clustering is extended to provide a dynamical approach for data clustering using a time-dependent Schrodinger equation. To expedite computations, we can approximate the time-dependent Hamiltonian formalism by a truncated calculation within a set of Gaussian wave-functions (coherent states) centered around the original points. This allows for analytic evaluation of the time evolution of all such states, opening up the possibility of exploration of relationships among data points through observation of varying dynamical-distances among points and convergence of points into clusters. This formalism may be further supplemented by preprocessing, such as dimensional reduction through singular value decomposition and/or feature filtering. Additionally, the parameters of the analysis can be modified in order to improve the efficiency of the dynamic quantum clustering processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantum Simulation of Field Theories Without State Preparation

We propose an algorithm for computing real-time observables using a quantum processor while avoiding the need to prepare the full quantum state. This reduction in quantum resources is achieved by classically sampling configurations in imaginary-time using standard lattice field theory. These configurations can then be passed to quantum processor for time-evolution. This method encounters a signal-to-noise problem which we characterize, and we demonstrate the application of standard lattice QCD methods to mitigate it.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

From Atom to Engine: Understanding Fundamental Effects of Structure on Combustion Using Tandem Experiment and Computation

The ability to tie structural features to a fuel candidate’s ignition properties provides a path for rational design of advantaged fuels that facilitate higher-efficiency, lower-emitting combustion in engines. The time evolution of a fuel’s radical population directly correlates with global combustion parameters, and because the generated radicals depend on the initial structure and reaction pathways of the fuel molecule, it follows that the molecular structure of a fuel has a direct impact on this cascade, and therefore salient ignition-tied fuel properties. This work aims to understand the impact of structural features in the context of global combustion properties for direct application to emerging engine technologies. Specifically, we highlight the ability to identify potential fuel blendstocks for specific engine strategies by examining and elucidating the radical cascade tied to ignition. A representative subset of alcohols possessing a variety of structural features (e.g. branching, chain length) was selected for study using a robust combination of experimental and computational methods. The approach begins with identifying short-lived radicals and likely abstraction sites upon pyrolysis in a microreactor coupled with photoionization mass spectrometry for direct detection of product species. In tandem, electronic structure calculations were performed to calculate the relevant potential energy surfaces for fuel pyrolysis as well as the subsequent O2 addition-isomerization reactions, which govern ignition behavior. Furthermore, the theoretical energetic and ro-vibrational data are used to calculate rate constants for direct ignition modeling to explore how structural effects impact NTC behavior. The microreactor data combined with electronic structure theory calculations provide a well-informed picture of the reactions relevant to ignition for each fuel in this study, as well as the most likely radicals generated under engine conditions. This thorough fundamental picture of fuel decomposition and ignition chemistry is used to correlate the observed ignition behavior to molecular structural effects.

advanced biofuels↗

CHEMNODE: CHEMICAL KINETICS SOLVER APPROACH BASED ON NEURAL ORDINARY DIFFERENTIAL EQUATIONS

This software contains an algorithm to model and predict the time evolution of chemical kinetics in reacting flow simulations using neural ordinary differential equations (NODEs). The approach works by using artificial neural networks to predict the chemical source terms. It achieves this by using forward-mode automatic differentiation and the Levenberg-Marquardt algorithm to adjust the neural network parameters, such that the discrepancies between the actual and predicted species profiles are minimized.

OWOYELE, OPEOLUWA↗

Molecular Dynamics Study of Creep Deformation in Nickel-based Superalloy

The present study employs molecular dynamics simulations of Ni-based superalloy to investigate the creep behavior under uniaxial compression test. Dislocation dynamics is analyzed for the nickel-based single crystal superalloy with the presence of void and with varying the distribution of gamma-prime phase The results show that multiple-void systems are more prone to yield than single-void systems and single-void systems are more prone to yield than the system withoutvoid. From the simulations, it has been determined that the creep mechanism in Ni/Ni3Al is subject to change on the applied stress depending on the distribution of gamma-prime phases change. Dislocation behavior is also observed in addition to the time evolution of dislocation nucleation and growth to quantify the propensity and mechanism of creep in nickel-based single crystal superalloy. The studies confirmed that dislocation length prior to plastic deformation decreased as the number of voids increased. In addition, the deformation behavior for finegrained nickel-based polycrystalline superalloy upon grain size variation is also investigated. Our findings show that both the movement mechanisms of the grains and grain boundaries and the relationship between grain size and yield strength are highly affected by the grain size of the materials. All the databases have then been classified to accurately predict the target class vi machine learning using the data mining tool WEKA.

creep, nickel-based superalloy, molecular dynamics↗