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Nonlinear Fast Magnetosonic Waves in Solar Prominence Pillars

We investigate the properties of nonlinear fast magnetosonic (NFM) waves in a solar prominence, motivated by recent high-resolution and high-cadence Hinode/SOT observations of small-scale oscillations in a prominence pillar. As an example, we analyze the details of the 2012 February 14 Hinode/SOT observations of quasi-periodic propagating features consistent with NFM waves, imaged in emission in Ca II and in the far blue wing of Hα. We perform wavelet analysis and find oscillations in the 1-3 min period range. Guided by these observations, we model the NFM waves with a three-dimensional magnetohydrodynamics (3D MHD) model, extending previous 2.5D MHD studies. The new model includes the structure of the high-density, low-temperature material of the prominence pillar embedded in the hot corona, in both potential and non-force-free sheared magnetic field configurations. The nonlinear model demonstrates the effects of mode coupling and the propagating density compressions associated with linear and NFM waves. The guided fast magnetosonic waves, together with density compressions and currents, are reproduced in the 3D pillar structure. We demonstrate or the first time the dynamic effects of the Lorentz force due to the magnetic shear in the non-force-free field on the pillar structure and on the propagation of the waves. The insights gained from the 3D MHD modeling are useful for improving coronal seismology of prominence structures that exhibit fast MHD wave activity.

Leon Ofman↗

Observations and 3D MHD Modeling of Small-scale Solar Prominence Oscillations

Small scaleoscillations were recently observed in prominences with high resolution Hinode/SOT and IRIS SJI in unprecedented detailand identified as fast magnetosonic waves. The high-resolution observations provide evidence of flows of cool material, fluid instabilities such as Kelvin-Helmholtz and Rayleigh-Taylor, and the spectroscopic information provides evidence of Doppler shifts, heating, and cooling of the prominence material. Recently nonlinear fast magnetosonic waves were observed withperiods in the range of 5–11 minutes and wavelengths in the plane of the sky (POS) of ~2000kmand flows, and the flows in narrow threads withPOS speed ∼16–46 km/s. Thenonlinear fast magnetosonic waves and flows were modeled using 2.5D MHD (Ofman & Kucera 2020). Here, we extend the studyof the nonlinear fast magnetosonic waves using more realistic 3D MHD model. The model includes the 3D structure of the density and the magnetic fieldas well as mode coupling anddemonstrate the propagating density compressions associated with the nonlinear fast magnetosonicwaves, as well as the guided modesin the pillar. The 3DMHD modelingimprove understanding ofthe POSeffects in limb prominence oscillations observations.The results of the modeling are useful for coronal seismology of the prominence structure.

Leon Ofman↗

In-Situ Scanning Electron Microscope Experiments for Microscale Mechanical Testing and Validated Modeling of Fiber Reinforced Thermoplastics

A novel, in-situ, scanning electron microscope (SEM) mechanical testing capability for materials at the microscale which provides experimental validation to a machine learning (ML) toolset for full-field validation of physics-based micromechanics models is being developed by researchers at NASA Glenn Research Center. These are enabling technologies for the integration of multiscale digital twins for materials into system level models which will result in the improved performance, material discovery, reduced production cost and time, rapid characterization, and prognostic structural health monitoring (SHM) for materials and structures for extreme environments in support of NASA space exploration missions. In order to bridge the material structure-to-system gap for digital twins, physics-based models must be experimentally validated at multiple length scales. Seminal microscale experiments, conducted at the Air Force Research Laboratory (AFRL), were limited to transverse compression of single-layer, unidirectional thermoset polymer matrix composite (PMC) micropillar specimens [1]. The early phases of the current project followed those initial results and setup to reproduce the compression testing of PMC material on the custom-built piezoelectric actuated micromechanical testing rig built by MicroTesting Solutions LLC. In this work, samples of thermoplastic PMC material were first machined into 3 mm cubes, and then further machining and final milling was done using a Focused Ion Beam (FIB). The initial experiment was done on a pillar roughly 20 µm x 20 µm x 40 µm tall. Additional pillars were milled with final sizes ranging from 20 µm x 20 µm x 40 µm tall to 40 µm x 40 µm x 65 µm tall. A speckle pattern for in-situ full-field measurements using Digital Image Correlation (DIC) was applied with platinum, which was coated on the surface, and then the FIB was used to mill away some of the coating to produce an irregular pattern of Pt on the pillar surface. The samples were loaded into the custom testing rig and placed into the SEM and loaded under compression until failure. Images were collected in the SEM during testing. Post-processing of the images was conducted using DIC to obtain full-field displacement and strain measurements elucidating the role of the matrix as well as fiber-fiber interaction at the microscale within the composite subjected to compression loading well into the non-linear regime of the material. Moreover, the evolution of fiber-matrix debonding and matrix cracking is observed in-situ at the microscale. This data, along with images segmented with a newly developed ML toolset [2], was used to create and validate physics-based micromechanics models. An image of the failed micropillar is shown in Figure 1. The techniques developed in the initial compression experiment was tailored to the validation needs of the models and expanded to include different sized samples as well as possibly tension and fatigue.

Laura Wilson↗

Fabrication of a Silicon Backshort Assembly for Waveguide-Coupled Superconducting Detectors

The Cosmology Large Angular Scale Surveyor (CLASS) is a ground-based instrument that will measure the polarization of the cosmic microwave background to search for evidence for gravitational waves from a posited epoch of inflation early in the Universe s history. This measurement will require integration of superconducting transition-edge sensors with microwave waveguide inputs with excellent control of systematic errors, such as unwanted coupling to stray signals at frequencies outside of a precisely defined microwave band. To address these needs we present work on the fabrication of micromachined silicon, producing conductive quarter-wave backshort assemblies for the CLASS 40 GHz focal plane. Each 40 GHz backshort assembly consists of three degeneratively doped silicon wafers. Two spacer wafers are micromachined with through-wafer vias to provide a 2.04 mm long square waveguide delay section. The third wafer terminates the waveguide delay in a short. The three wafers are bonded at the wafer level by Au-Au thermal compression bonding then aligned and flip chip bonded to the CLASS detector at the chip level. The micromachining techniques used have been optimized to create high aspect ratio waveguides, silicon pillars, and relief trenches with the goal of providing improved out of band signal rejection. We will discuss the fabrication of integrated CLASS superconducting detector chips with the quarter-wave backshort assemblies.

Crowe, Erik J.↗

Fabrication of Silicon Backshorts with Improved Out-of-Band Rejection for Waveguide-Coupled Superconducting Detectors

The Cosmology Large Angular Scale Surveyor (CLASS) is a ground-based instrument that will measure the polarization of the cosmic microqave background to search for gravitational waves form a posited epoch of inflation early in the universe's history. This measurement will require integration of superconducting transition-edge sensors with microwave waveguide inputs with good conrol of systematic errors, such as unwanted coupling to stray signals at frequencies outside of a precisely defined microwave band. To address these needs we will present work on the fabrication of silicon quarter-wave backshorts for the CLASS 40GHz focal plane. The 40GHz backshort consists of three degeneratively doped silicon wafers. Two spacer wafers are micromachined with through wafer vins to provide a 2.0mm long square waveguide. The third wafer acts as the backshort cap. The three wafers are bonded at the wafer level by Au-Au thermal compression bonding then aligned and flip chip bonded to the CLASS detector at the chip level. The micromachining techniques used have been optimized to create high aspect ratio waveguides, silicon pillars, and relief trenches with the goal of providing improved out of band signal rejection. We will discuss the fabrication of integrated CLASS superconducting detectors with silicon quarter wave backshorts and present current measurement results.

Crowe, Erik J.↗

Towards Probablistic Assessment of Hypobaric Decompression Sickness Treatment

INTRODUCTION: Pressure, oxygen (O2), and time are the pillars to effective treatment of decompression sickness (DCS). The NASA DCS Treatment Model links a decrease in computed bubble volume to the resolution of a symptom. The decrease in volume is realized in two stages: a) during the Boyle's Law compression and b) during subsequent dissolution of the gas phase by the O2 window. METHODS: The cumulative distribution of 154 symptoms that resolved during repressurization was described with a log-logistic density function of pressure difference (deltaP as psid) associated with symptom resolution and two other explanatory variables. The 154 symptoms originated from 119 cases of DCS during 969 exposures in 47 different altitude tests. RESULTS: The probability of symptom resolution [P(symptom resolution)] = 1 / (1+exp(- (ln(deltaP) - 1.682 + 1.089×AMB - 0.00395×SYMPTOM TIME) / 0.633)), where AMB is 1 when the subject ambulated as part of the altitude exposure or else 0 and SYMPTOM TIME is the elapsed time in min from start of the altitude exposure to recognition of a DCS symptom. The P(symptom resolution) was estimated from computed deltaP from the Tissue Bubble Dynamics Model based on the "effective" Boyle's Law change: P2 - P1 (deltaP, psid) = P1×V1/V2 - P1, where V1 is the computed volume of a spherical bubble in a unit volume of tissue at low pressure P1 and V2 is computed volume after a change to a higher pressure P2. V2 continues to decrease through time at P2, at a faster rate if 100% ground level O2 was breathed. The computed deltaP is the effective treatment pressure at any point in time as if the entire deltaP was just from Boyle's Law compression. DISCUSSION: Given the low probability of DCS during extravehicular activity and the prompt treatment of a symptom with options through the model it is likely that the symptom and gas phase will resolve with minimum resources and minimal impact on astronaut health, safety, and productivity.

Conkin, J.↗

Continuous Electrode Inertial Electrostatic Confinement Fusion

The NIAC Phase I project on Inertial Electrostatic Confinement was a continuation of early stage research that was funded by an NSTRF. The student on the project, Andrew Chap, was funded by the NSTRF from Fall 2013 through the Summer of 2017, and then was funded on the NIAC through the completion of his PhD. A significant amount of work targeting the plasma confinement physics was the focus of his NSTRF, and over the course of that effort he developed a number of analyses and computational tools that leveraged GPU parallelization. A detailed discussion of these models can be found in his dissertation, which has been included as Appendix D in this report. As a requirement for the NSTRF, Andrew's full dissertation was submitted at the end of the program.Having developed the computational tools, a substantial amount of simulation and analyses leveraging those tools were conducted during the Fall of 2017, under the auspices of the NIAC funded research. Much of this work targeted optimization of the confinement fields, investigating their structure and the possible advantages of having them be time-varying. The results of these simulations can also be found in Appendix D.One of the main results from this research is that the density of ions electrostatically confined within the system can indeed be increased by several orders of magnitude by optimizing the radial potential distribution, and by dynamically varying these fields to maintain compressed ion bunches. An electron population can also be confined within the core by a static radial cusped magnetic field,which helps to support a greater ion density within the core. The issue with the confinement mechanism is that as the ion densities are increased toward fusion-relevant levels, the electrostatic forces generated by the confined electron population become so great that the ions are no longer energetic enough to leave the device core. As their excursions into the outer channels are diminished, the mechanism that is used to maintain their non-thermal velocity distributions becomes ineffective, and eventually the ions become fully confined within the core, where they thermalize. A possible fix to the problem comes by discarding the active ion control (a main pillar of the concept)but retaining the structure of the permanent magnet confinement of the electron population. Such cusped field confinement has been the focus of other IEC approaches (e.g. Polywell), but the high transparency of the permanent magnet structure lends itself to better ion extraction and power conversion (a second pillar of the concept). The question then becomes whether any influence on the ion evolution within the core can be achieved to slow the thermalization of the ions. Such approaches have been studied in highly idealized analytic models, but face major criticisms within the literature. While this is a possible path forward, the uncertainty in the approach did not warrant committing NIAC Phase II resources to investigating the concept at this time.

Sedwick, Raymond↗

A New Era of H-O-C-S Magma Solubility Modeling: Better, Faster, Stronger

H 2 O, CO 2 , and S are the most abundant volatiles in magmatic systems and are critical to understanding magma storage, phase equilibria, and volcanic eruptions. Models that consider all three of these components, however, may not allow for critical examination and adjustment of assumptions underlying the model, or provide benchmark testing or extensible interfaces. Thus, understanding why models produce different results can be challenging. We have gathered authors of established (D-Compress) and recent (VolFe, EVo, Sulfur_X, MAGEC) H-O-C-S volatile solubility models to work together to understand how and why our models diverge. We present a series of benchmark basalt degassing scenarios revealing that often understated model assumptions such as fO 2 buffer equations, fO 2 -Fe 3+ /ΣFe relationships, and even major element normalization routines have outsized effects on model results. All models consider S 2- and S 6+ melt species but with different approaches to sulfate/sulfide capacities, partition coefficients, and species fugacities, leading to divergence in the evolution of modeled gas compositions, melt S and Fe speciation, and fO 2 , with the extent of divergence depending on melt composition. Such scenarios enable meaningful intercomparison of existing models and lay the groundwork for a user-friendly yet powerful solubility modeling framework. Given our wealth of existing solubility literature, we suggest that the field of magmatic volatiles should focus now on the creation of modern tools and the modular implementation of existing model equations or methods, and that the evaluation of code usability, transparency, and benchmarking should be codified pillars of the peer-review process. As an example of such an endeavor, we present early work coupling these sulfur solubility models with VESIcal, an extensible and rigorously tested python library containing seven existing H 2 O-CO 2 solubility models. VESIcal includes the ability to extract, edit, and even interchange assumptions underlying any model. For example, users may combine or swap separately published H 2 O, CO 2 , and S models, as well as underlying model choices, such as Equations of State and redox models.

volatiles in magmas↗

Bubble Combustion

A method of energy production that is capable of low pollutant emissions is fundamental to one of the four pillars of NASA s Aeronautics Blueprint: Revolutionary Vehicles. Bubble combustion, a new engine technology currently being developed at Glenn Research Center promises to provide low emissions combustion in support of NASA s vision under the Emissions Element because it generates power, while minimizing the production of carbon dioxide (CO2) and nitrous oxides (NOx), both known to be Greenhouse gases. and allows the use of alternative fuels such as corn oil, low-grade fuels, and even used motor oil. Bubble combustion is analogous to the inverse of spray combustion: the difference between bubble and spray combustion is that spray combustion is spraying a liquid in to a gas to form droplets, whereas bubble combustion involves injecting a gas into a liquid to form gaseous bubbles. In bubble combustion, the process for the ignition of the bubbles takes place on a time scale of less than a nanosecond and begins with acoustic waves perturbing each bubble. This perturbation causes the local pressure to drop below the vapor pressure of the liquid thus producing cavitation in which the bubble diameter grows, and upon reversal of the oscillating pressure field, the bubble then collapses rapidly with the aid of the high surface tension forces acting on the wall of the bubble. The rapid and violent collapse causes the temperatures inside the bubbles to soar as a result of adiabatic heating. As the temperatures rise, the gaseous contents of the bubble ignite with the bubble itself serving as its own combustion chamber. After ignition, this is the time in the bubble s life cycle where power is generated, and CO2, and NOx among other species, are produced. However, the pollutants CO2 and NOx are absorbed into the surrounding liquid. The importance of bubble combustion is that it generates power using a simple and compact device. We conducted a parametric study using CAVCHEM, a computational model developed at Glenn, that simulates the cavitational collapse of a single bubble in a liquid (water) and the subsequent combustion of the gaseous contents inside the bubble. The model solves the time-dependent, compressible Navier-Stokes equations in one-dimension with finite-rate chemical kinetics using the CHEMKIN package. Specifically, parameters such as frequency, pressure, bubble radius, and the equivalence ratio were varied while examining their effect on the maximum temperature, radius, and chemical species. These studies indicate that the radius of the bubble is perhaps the most critical parameter governing bubble combustion dynamics and its efficiency. Based on the results of the parametric studies, we plan on conducting experiments to study the effect of ultrasonic perturbations on the bubble generation process with respect to the bubble radius and size distribution.

Corrigan, Jackie↗