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At least 1,441 records · Page 80

Flutter and Divergence Analysis using the Generalized Aeroelastic Analysis Method

The Generalized Aeroelastic Analysis Method (GAAM) is applied to the analysis of three well-studied checkcases: restrained and unrestrained airfoil models, and a wing model. An eigenvalue iteration procedure is used for converging upon roots of the complex stability matrix. For the airfoil models, exact root loci are given which clearly illustrate the nature of the flutter and divergence instabilities. The singularities involved are enumerated, including an additional pole at the origin for the unrestrained airfoil case and the emergence of an additional pole on the positive real axis at the divergence speed for the restrained airfoil case. Inconsistencies and differences among published aeroelastic root loci and the new, exact results are discussed and resolved. The generalization of a Doublet Lattice Method computer code is described and the code is applied to the calculation of root loci for the wing model for incompressible and for subsonic flow conditions. The error introduced in the reduction of the singular integral equation underlying the unsteady lifting surface theory to a linear algebraic equation is discussed. Acknowledging this inherent error, the solutions of the algebraic equation by GAAM are termed 'exact.' The singularities of the problem are discussed and exponential series approximations used in the evaluation of the kernel function shown to introduce a dense collection of poles and zeroes on the negative real axis. Again, inconsistencies and differences among published aeroelastic root loci and the new 'exact' results are discussed and resolved. In all cases, aeroelastic flutter and divergence speeds and frequencies are in good agreement with published results. The GAAM solution procedure allows complete control over Mach number, velocity, density, and complex frequency. Thus all points on the computed root loci can be matched-point, consistent solutions without recourse to complex mode tracking logic or dataset interpolation, as in the k and p-k solution methods.

Edwards, John W.↗

The Python’s Lunch: geometric obstructions to decoding Hawking radiation

According to Harlow and Hayden [ arXiv:1301.4504 ] the task of distilling information out of Hawking radiation appears to be computationally hard despite the fact that the quantum state of the black hole and its radiation is relatively un-complex. We trace this computational difficulty to a geometric obstruction in the Einstein-Rosen bridge connecting the black hole and its radiation. Inspired by tensor network models, we conjecture a precise formula relating the computational hardness of distilling information to geometric properties of the wormhole — specifically to the exponential of the difference in generalized entropies between the two non-minimal quantum extremal surfaces that constitute the obstruction. Due to its shape, we call this obstruction the ‘Python’s Lunch’, in analogy to the reptile’s postprandial bulge.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Characteristics and mechanisms of hydrogen-induced quasi-cleavage fracture of lath martensitic steel

Here this study presents an in-depth characterization of the microstructures, crystallographic orientations, and dislocation characteristics beneath hydrogen-induced quasi-cleavage fracture features of an as-quenched, lath martensitic (α') 22MnB5 steel. The fracture surfaces of gaseous hydrogen-embrittled martensitic specimens were analyzed by a combination of multiple analytical tools: scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), transmission electron microscopy (TEM), and transmission Kikuchi diffraction (TKD). The dominant fracture mode in the hydrogen-affected zones was quasi-cleavage fracture, which involved significant plasticity, evidenced by plastic zones near tear ridges and a high density of dislocations beneath the quasi-cleavage facets. The martensite constituent sizes, variant orientations, and boundaries influenced the quasi-cleavage surface morphologies. Fractography revealed the occurrence of {100} α' -type cleavage across martensitic laths, developing relatively “flat” quasi-cleavage surfaces, in addition to {110} α' -type cracking likely along lath and block boundaries, and fracture along non-cleavage planes. The likelihood of the formation of the relatively “flat” quasi-cleavage surfaces increased with increasing martensitic constituent sizes. Substantial dislocation bands formed on intersecting {112} α' slip planes within a martensite block below the hydrogen-induced cleavage fractures on {100} α' planes. River markings on the quasi-cleavage surfaces were found to originate from the complex, hierarchical lath martensitic microstructure. Steps and ridges on the quasi-cleavage facets generally linked with the various martensitic boundaries, suggesting that they were produced as a result of crack deviations at those boundaries. The fracture paths and martensite quasi-cleavage mechanisms are discussed in the context of the role of hydrogen and Cottrell cleavage model.

36 MATERIALS SCIENCE↗

Crust and Upper Mantle Structure Beneath the Eastern United States

Abstract The Eastern United States (EUS) has a complex geological history and hosts several seismic active regions. We investigate the subsurface structure beneath the broader EUS. To produce reliable images of the subsurface, we simultaneously invert smoothed P‐wave receiver functions, Rayleigh‐wave phase and group velocity measurements, and Bouguer gravity observations for the 3D shear‐wave speed. Using surface‐wave observations (3–250 s) and spatially smoothed receiver functions, our velocity models are robust, reliable, and rich in detail. The shear‐wave velocity models fit all three types of observations well. The resulting velocity model for the eastern U.S. shows thinner crust beneath New England, the east coast, and the Mississippi Embayment (ME). A relatively thicker crust was found beneath the stable North America craton. A relatively slower upper mantle was imaged beneath New England, the east coast, and western ME. A comparison of crust thickness derived from our model against four recent published models shows first‐order consistency. A relatively small upper mantle low‐speed region correlates with a published P‐wave analysis that has associated the anomaly with a 75 Ma kimberlite volcanic site in Kentucky. We also explored the relationship between the subsurface structure and seismicity in the eastern U.S. We found that earthquakes often locate near regions with seismic velocity variations, but not universally. Not all regions of significant subsurface wave speed changes are loci of seismicity. A weak correlation between upper mantle shear velocity and earthquake focal mechanism has been observed.

58 GEOSCIENCES↗

cGAS-like receptors sense RNA and control 3'2'-cGAMP signalling in Drosophila

Cyclic GMP–AMP synthase (cGAS) is a cytosolic DNA sensor that produces the second messenger cG[2'–5']pA[3'–5']p (2'3'-cGAMP) and controls activation of innate immunity in mammalian cells. Animal genomes typically encode multiple proteins with predicted homology to cGAS, but the function of these uncharacterized enzymes is unknown. Here we show that cGAS-like receptors (cGLRs) are innate immune sensors that are capable of recognizing divergent molecular patterns and catalysing synthesis of distinct nucleotide second messenger signals. Crystal structures of human and insect cGLRs reveal a nucleotidyltransferase signalling core shared with cGAS and a diversified primary ligand-binding surface modified with notable insertions and deletions. We demonstrate that surface remodelling of cGLRs enables altered ligand specificity and used a forward biochemical screen to identify cGLR1 as a double-stranded RNA sensor in the model organism Drosophila melanogaster. We show that RNA recognition activates Drosophila cGLR1 to synthesize the novel product cG[3'–5']pA[2'–5']p (3'2'-cGAMP). A crystal structure of Drosophila stimulator of interferon genes (dSTING) in complex with 3'2'-cGAMP explains selective isomer recognition, and 3'2'-cGAMP induces an enhanced antiviral state in vivo that protects from viral infection. Similar to radiation of Toll-like receptors in pathogen immunity, our results establish cGLRs as a diverse family of metazoan pattern recognition receptors.

59 BASIC BIOLOGICAL SCIENCES↗

Comprehensive modeling of a liquid rocket combustion chamber

An analytical model for the simulation of detailed three-phase combustion flows inside a liquid rocket combustion chamber is presented. The three phases involved are: a multispecies gaseous phase, an incompressible liquid phase, and a particulate droplet phase. The gas and liquid phases are continuum described in an Eulerian fashion. A two-phase solution capability for these continuum media is obtained through a marriage of the Implicit Continuous Eulerian (ICE) technique and the fractional Volume of Fluid (VOF) free surface description method. On the other hand, the particulate phase is given a discrete treatment and described in a Lagrangian fashion. All three phases are hence treated rigorously. Semi-empirical physical models are used to describe all interphase coupling terms as well as the chemistry among gaseous components. Sample calculations using the model are given. The results show promising application to truly comprehensive modeling of complex liquid-fueled engine systems.

Liang, P.-Y.↗

Determining the composition of olivine on asteroidal surfaces

Olivine was remotely identified as a major component on many S- and A-type asteroids based on qualitative analyses of broad absorption features near 1.0 micron in their telescopic reflectance spectra. Laboratory studies showed that this diagnostic olivine absorption feature is composed of three individual absorption bands resulting from electronic transitions of Fe(+2) in distorted M1 and M2 sites. Both the overall absorption feature and each of the individual absorption bands are also known to vary systematically as a function of olivine composition. Thus, it should be possible to remotely determine the composition of olivine present on the surfaces of the various olivine-rich asteroids. However, extrapolation of laboratory studies to compositional interpretation of asteroid spectra is complicated by several factors: observational noise; lower spectral resolution; compositional heterogeneities (including the presence of other phases such as pyroxenes and/or metal); and the effects of alteration processes. In order to address such complex problems, a quantitative approach to spectral analysis, the modified Gaussian model (MGM) was developed by Sunshine et al., which deconvolves spectra into their constituent absorption bands. The MGM, a refinement of the Gaussian model, more accurately adheres to the physical processes involved in electronic transition absorptions. Under the MGM, each spectrum is modeled in log reflectance and energy as a sum of absorption bands superimposed onto a baseline or continuum. Each absorption band is described by three model parameters (center, width, and strength) which can be interpreted and used to infer composition. One of the strengths of the MGM is that it allows compositional information to be extracted directly from measured spectra and is therefore complementary to other approaches to modeling asteroid spectra which require the use of meteorites and/or terrestrial samples as spectral analogs. A quantitative understanding of the properties of olivine absorptions was established by using the MGM to analyze a laboratory suite of spectra spanning a full range of olivine compositions.

Sunshine, Jessica M.↗

Additional Development and Systems Analyses of Pneumatic Technology for High Speed Civil Transport Aircraft

In the Task I portion of this NASA research grant, configuration development and experimental investigations have been conducted on a series of pneumatic high-lift and control surface devices applied to a generic High Speed Civil Transport (HSCT) model configuration to determine their potential for improved aerodynamic performance, plus stability and control of higher performance aircraft. These investigations were intended to optimize pneumatic lift and drag performance; provide adequate control and longitudinal stability; reduce separation flowfields at high angle of attack; increase takeoff/climbout lift-to-drag ratios; and reduce system complexity and weight. Experimental aerodynamic evaluations were performed on a semi-span HSCT generic model with improved fuselage fineness ratio and with interchangeable plain flaps, blown flaps, pneumatic Circulation Control Wing (CCW) high-lift configurations, plain and blown canards, a novel Circulation Control (CC) cylinder blown canard, and a clean cruise wing for reference. Conventional tail power was also investigated for longitudinal trim capability. Also evaluated was unsteady pulsed blowing of the wing high-lift system to determine if reduced pulsed mass flow rates and blowing requirements could be made to yield the same lift as that resulting from steady-state blowing. Depending on the pulsing frequency applied, reduced mass flow rates were indeed found able to provide lift augmentation at lesser blowing values than for the steady conditions. Significant improvements in the aerodynamic characteristics leading to improved performance and stability/control were identified, and the various components were compared to evaluate the pneumatic potential of each. Aerodynamic results were provided to the Georgia Tech Aerospace System Design Lab. to conduct the companion system analyses and feasibility study (Task 2) of theses concepts applied to an operational advanced HSCT aircraft. Results and conclusions from these experimental evaluations are presented herein, as are recommendations for further development and follow-on investigations. Also provided as an Appendix for reference are the basic results from the previous pneumatic HSCT investigations.

Englar, Robert J.↗

Psychophysiological Monitoring of Aerospace Crew State

As next-generation space exploration missions necessitate increasingly autonomous systems, there is a critical need to better detect and anticipate crewmember interactions with these systems. The success of present and future autonomous technology in exploration spaceflight is ultimately dependent upon safe and efficient interaction with the human operator. Optimal interaction is particularly important for surface missions during highly coordinated extravehicular activity (EVA), which consists of high physical and cognitive demands with limited ground support. Crew functional state may be affected by a number of variables including workload, stress, and motivation. Real-time assessments of crew state that do not require a crewmember’s time and attention to complete will be especially important to assess operational performance and behavioral health during flight. In response to the need for objective, passive assessment of crew state, the aim of this work is to develop an accurate and precise prediction model of human functional state for surface EVA using multi-modal psychophysiological sensing. The psychophysiological monitoring approach relies on extracting a set of features from physiological signals and using these features to classify an operator’s cognitive state. This work aims to compile a non-invasive sensor suite to collect physiological data in real-time. Training data during cognitive and more complex functional tasks will be used to develop a classifier to discriminate high and low cognitive workload crew states. The classifier will then be tested in an operationally relevant EVA simulation to predict cognitive workload over time. Once a crew state is determined, further research into specific countermeasures, such as decision support systems, would be necessary to optimize the automation and improve crew state and operational performance.

Wusk, Grace C.↗

A comparison of global estimates of marine primary production from ocean color

The third primary production algorithm round robin (PPARR3) compares output from 24 models that estimate depth-integrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models. Here we compare the global primary production fields corresponding to eight months of 1998 and 1999 as estimated from common input fields of photosynthetically-available radiation (PAR), sea-surface temperature (SST), mixed-layer depth, and chlorophyll concentration. We also quantify the sensitivity of the ocean-color-based models to perturbations in their input variables. The pair-wise correlation between ocean-color models was used to cluster them into groups or related output, which reflect the regions and environmental conditions under which they respond differently. The groups do not follow model complexity with regards to wavelength or depth dependence, though they are related to the manner in which temperature is used to parameterize photosynthesis. Global average PP varies by a factor of two between models. The models diverged the most for the Southern Ocean, SST under 10 C, and chlorophyll concentration exceeding 1mg Chlm-3. Based on the conditions under which the model results diverge most, we conclude that current ocean-color-based models are challenged by high-nutrient low-chlorophyll conditions, and extreme temperatures or chlorophyll concentrations. The GCM-based models predict comparable primary production to those based on ocean color: they estimate higher values in the Southern Ocean, at low SST, and in the equatorial band, while they estimate lower values in eutrophic regions (probably because the area of high chlorophyll concentrations is smaller in the GCMs). Further progress in primary production modeling requires improved understanding of the effect of temperature on photosynthesis and better parameterization of the maximum photosynthetic rate.

Yamanaka, Yasuhiro↗

H20 Phase Characterization and Icing Mitigation Through Quantum Sensing in Silicon Carbide Non-Metal Defects

The primary focus of aircraft icing research has been on ice accretion on wings for its serious adverse consequences. When icing occurs on a wing, the change in airfoil shape results in a decrease in lift and an increase in drag, leading to potentially fatal accidents. Although the issue was recognized in the 1920s, the icing problem is still an area of ongoing research due to the complexity of the icing phenomena. A much-improved understanding of how certain weather conditions produce different icing characteristics will lead to new mitigation methods and a better quantification of current methods. This can be done by better understanding of the molecular bonding energy produced by ice polytype combinations when interacting with different surface materials in various environments. This work is currently developing both models that more accurately describe the quantum signatures of H2O states (i.e. supercooled, ice, liquid, glass phase...) and chip-based detectors to evaluate these signatures. These sensors utilize ion defects in Silicon Carbide (SiC) as extremely sensitive atomic magnetic detectors. This effort leverages both the decades-long SiC development expertise and infrastructure at NASA Glenn and its growing capabilities in quantum metrology.

Daniel R. Hart↗

Electrical and Seismic Response of Saline Permafrost Soil during Freeze - Thaw Transition: Supporting Data

These data were collected during a repeat freeze-thaw cycle on a saline permafrost portion of a core to understand mechanical and geophysical property changes over time. The core used for the experiment was collected from the NGEE-Arctic Site 0 transect site located in the Barrow Environmental Observatory (BEO) in Barrow, Alaska. This region features polygonal ground, and the core was collected in the center of a flat centered polygon. The saline permafrost portion of the core was at the bottom 260-280 cm below ground surface. Data files (*.csv) include: Electrical signal change during freeze-thaw-refreeze cycle at 1 Hz; Spectral data - Complex resistivity data during Freeze-thaw of the saline permafrost core; Seismic data; and CT cross sections (*.jpg) of the core sample from approximately the same location: (A, D) before the test (thawed), (B, E) after the test (frozen), and (C, F) after deep freeze (frozen).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Near surface defects: Cause of deficit between internal and external open-circuit voltage in solar cells

The presence of interface recombination in a complex multilayered thin-film solar structure causes a disparity between the internal open-circuit voltage (V OC,in ), measured by photoluminescence, and the external open-circuit voltage (V OC,ex ) i.e. an additional V OC deficit. Higher V OC,ex value aim require a comprehensive understanding of connection between V OC deficit and interface recombination. Here, a deep near-surface defect model at the absorber/buffer interface is developed for copper indium di-selenide solar cells grown under Cu excess conditions to explain the disparity between V OC ,in and V OC,ex . The model is based on experimental analysis of admittance spectroscopy and deep-level transient spectroscopy, which show the signature of deep acceptor defect. Further, temperature-dependent current-voltage measurements confirm the presence of near surface defects as the cause of interface recombination. The numerical simulations show strong decrease in the local V OC ,in near the absorber/buffer interface leading to a V OC deficit in the device. This loss mechanism leads to interface recombination without a reduced interface bandgap or Fermi level pinning. Further, these findings demonstrate that the V OC ,in measurements alone can be inconclusive and might conceal the information on interface recombination pathways, establishing the need for complementary techniques like temperature dependent current voltage measurements to identify the cause of interface recombination in the devices.

14 SOLAR ENERGY↗

Calibrating hypersonic turbulence flow models with the HIFiRE-1 experiment using data-driven machine-learned models.

In this paper we study the efficacy of combining machine-learning methods with projection-based model reduction techniques for creating data-driven surrogate models of computationally expensive, high-fidelity physics models. Such surrogate models are essential for many-query applications e.g., engineering design optimization and parameter estimation, where it is necessary to invoke the high-fidelity model sequentially, many times. Surrogate models are usually constructed for individual scalar quantities. However there are scenarios where a spatially varying field needs to be modeled as a function of the model’s input parameters. Here we develop a method to do so, using projections to represent spatial variability while a machine-learned model captures the dependence of the model’s response on the inputs. The method is demonstrated on modeling the heat flux and pressure on the surface of the HIFiRE-1 geometry in a Mach 7.16 turbulent flow. The surrogate model is then used to perform Bayesian estimation of freestream conditions and parameters of the SST (Shear Stress Transport) turbulence model embedded in the high-fidelity (Reynolds-Averaged Navier–Stokes) flow simulator, using shock-tunnel data. The paper provides the first-ever Bayesian calibration of a turbulence model for complex hypersonic turbulent flows. We find that the primary issues in estimating the SST model parameters are the limited information content of the heat flux and pressure measurements and the large model-form error encountered in a certain part of the flow.

42 ENGINEERING↗

Dual frequency comb spectroscopy of solid fuel pyrolysis and combustion: Quantifying the influence of moisture content in Douglas fir

As the fire research community develops multi-scale models to predict the spread of wildland fires, there is a need for well-controlled, small-scale experiments which provide benchmark data and fundamental understanding of the effects of key parameters on the combustion of wildland fuels. Here, we implement a unique suite of non-intrusive, quantitative diagnostics that simultaneously measure mass loss, surface temperature, in situ gas temperature and water vapor concentration, including the first implementation of dual frequency comb spectroscopy for the study of solid fuels. As a demonstration, we examine the effect of fuel moisture content on the burning of Douglas fir wood samples that are ignited under constant radiative heat flux from a cone calorimeter to provide benchmark data for multi-scale models. Peak flame temperatures 3 mm above the sample surface measured with the dual frequency comb laser spectrometer are in excess of 1200 K. The flame temperature decreases by over 150 K as fuel moisture content increases from 0.7% to 40%. This work demonstrates a platform for simultaneous, quantitative measurements of well-controlled small-scale experiments which provide benchmark data for the development of advanced modeling and simulations capable of capturing the complex physics present in wildland fire systems.

54 ENVIRONMENTAL SCIENCES↗

The nanocaterpillar's random walk: diffusion with ligand–receptor contacts

Particles with ligand–receptor contacts bind and unbind fluctuating “legs” to surfaces, whose fluctuations cause the particle to diffuse. Quantifying the diffusion of such “nanoscale caterpillars” is a challenge, since binding events often occur on very short time and length scales. Here, in this work, we derive an analytical formula, validated by simulations, for the long time translational diffusion coefficient of an overdamped nanocaterpillar, under a range of modeling assumptions. We demonstrate that the effective diffusion coefficient, which depends on the microscopic parameters governing the legs, can be orders of magnitude smaller than the background diffusion coefficient. Furthermore it varies rapidly with temperature, and reproduces the striking variations seen in existing data and our own measurements of the diffusion of DNA-coated colloids. Our model gives insight into the mechanism of motion, and allows us to ask: when does a nanocaterpillar prefer to move by sliding, where one leg is always linked to the surface, and when does it prefer to move by hopping, which requires all legs to unbind simultaneously? We compare a range of systems (viruses, molecular motors, white blood cells, protein cargos in the nuclear pore complex, bacteria such as Escherichia coli, and DNA-coated colloids) and present guidelines to control the mode of motion for materials design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Temperature distribution in a laser-heated diamond anvil cell as described by finite element analysis

Finite element analysis (FEA) is a powerful tool for numerically solving partial differential equations over complex geometries and is thus useful for analyzing heat transport in laser-heated diamond anvil cell (LHDAC) experiments. Our models expand on previously published simulations by calculating the volume-averaged temperatures of both the sample and insulation/pressure media under steady-state heating to determine the thermal pressure of the hot sample. Our goal is to produce an accurate relationship between the measured surface temperature of the absorbing sample and the temperature of the transparent insulating media, which is used to determine thermal pressure but susceptible to steep temperature gradients. We find that in doing so, our FEA models of temperature within the pressure/insulation media can differ from simplified estimates of temperature gradients by more than a factor of 2. We also explore temperature-dependent and temperature-independent thermal conductivity models and find that the volume-averaged temperatures differ by up to a factor of 1.3, forcing the predicted thermal pressures determined to also differ by up to a factor of 1.5 at a temperature of 2000 K at 50 GPa for neon. Higher temperatures exacerbate this difference. We also find that unintentional asymmetric sample insertion and sample heating, which are common in LHDAC experiments, do not have a first-order effect on volume-averaged temperatures. The FEA models, available in both Python and FlexPDE, are versatile across different sample geometries, materials, and heat source laser shapes.

Farah, Frederick↗

Pathways for Nucleation and Growth in Confined Spaces and at Interfaces

Mineral crystallization is central to myriad natural processes from the formation of snowflakes to stalagmites, but the molecular-scale mechanisms are often far more complex than models reflect. Feedbacks between the hydro-, bio-, and geo-spheres drive complex crystallization processes that challenge our ability to observe and quantify them, motivating an expansion of crystallization theories. Here, in this article, we discuss how the driving forces and timescales of nucleation are influenced by factors ranging from simple geometric confinement to distinct interfacial solution structures involving solvent organization, electrical double layers, and surface charging effects. Taken together, these ubiquitous natural phenomena can preserve metastable intermediates, drive precipitation of undersaturated phases, and modulate crystallization in time and space.

biosphere↗