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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

NACA0012 benchmark model experimental flutter results with unsteady pressure distributions

The Structural Dynamics Division at NASA Langley Research Center has started a wind tunnel activity referred to as the Benchmark Models Program. The primary objective of this program is to acquire measured dynamic instability and corresponding pressure data that will be useful for developing and evaluating aeroelastic type computational fluid dynamics codes currently in use or under development. The program is a multi-year activity that will involve testing of several different models to investigate various aeroelastic phenomena. This paper describes results obtained from a second wind tunnel test of the first model in the Benchmark Models Program. This first model consisted of a rigid semispan wing having a rectangular planform and a NACA 0012 airfoil shape which was mounted on a flexible two degree of freedom mount system. Experimental flutter boundaries and corresponding unsteady pressure distribution data acquired over two model chords located at the 60 and 95 percent span stations are presented.

Rivera, Jose A., Jr.↗
DOE OSTI2020

Non-destructive simulation of node defects in additively manufactured lattice structures

Additive Manufacturing (AM), commonly referred to as 3D printing, offers the ability to not only fabricate geometrically complex lattice structures but parts in which lattice topologies in-fill volumes bounded by complex surface geometries. However, current AM processes produce defects on the strut and node elements which make up the lattice structure. This creates an inherent difference between the as-designed and as-fabricated geometries, which negatively affects predictions (via numerical simulation) of the lattice’s mechanical performance. Although experimental and numerical analysis of an AM lattice’s bulk structure, unit cell and struts have been performed, there exists almost no research data on the mechanical response of the individual as-manufactured lattice node elements. Here we propose a methodology that, for the first time, allows non-destructive quantification of the mechanical response of node elements within an as-manufactured lattice structure. A custom-developed tool is used to extract and classify each individual node geometry from micro-computed tomography scans of an AM fabricated lattice. Voxel-based finite element meshes are generated for numerical simulation and the mechanical response distribution is compared to that of the idealised computer-aided design model. The method demonstrates compatibility with Uncertainty Quantification methods that provide opportunities for efficient prediction of a population of nodal responses from sampled data. Overall, the non-destructive and automated nature of the node extraction and response evaluation is promising for its application in qualification and certification of additively manufactured lattice structures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Enhancing Biopreparedness through a Model System to Understand the Molecular Mechanisms that Lead to Pathogenesis and Disease Transmission: NW-BRaVE

The science of biopreparedness to counter biological threats hinges on understanding the fundamental principles and molecular mechanisms that lead to pathogenesis and disease transmission. Our vision to address this challenge is to create a powerful and user-friendly platform to elucidate the fundamental principles of how molecular interactions drive pathogen-host relationships and host shifts. We will enable groundbreaking discoveries by integrating a wide range of structural, genomics, proteomics, and other advanced omics measurements, along with evolutionary and artificial intelligence predictions. To make sure the system is applicable to real-world problems, we will develop it in the context of a tractable model system, the small, abundant, and accessible photosynthetic cyanobacteria and their constantly co-adapting viral pathogens, cyanophages. This model will maintain the system’s applicability to real-world problems and techniques, but the overall focus will be on elucidating general principles of detecting, assessing, and surveilling molecular interaction, adaptation, and coevolution that are system agnostic and therefore extensible to other viral-host interactions. Our overall objectives are to (1) identify the molecular complexes that comprise the cyanobacteria redox macromolecular subsystem and how they dynamically change with bacteriophage infection in situ, using cryo-electron tomography; (2) profile regulatory changes during infection using proteomics, multiomics, and experimental validation, and integrate the data with in situ structures; (3) use genomics and metagenomics to determine environmental and population factors across time scales that impact the interactions between marine cyanobacteria and their cyanophage parasites, predicting the evolutionary origins of in situ structural and functional interactions, convergence and coevolution; and (4) develop a data integration and transformation platform that facilitates the integration of in situ, proteomic, and evolutionary measurements of molecular interactions to surveil diverse hosts and parasites in various environmental contexts. These objectives address Focus Area 2 Reveal Molecular Interactions Across Biological Scales for Design of Targeted Interventions. Our powerful and user-friendly platform will enhance connections between the often-siloed fields of structure, molecular phenotype, and evolutionary genomics that are key to biopreparedness, but in need of integration (Figure 1). We will build an integrated navigation tool to facilitate the effective use of globally distributed experimental data for integrated analysis and predictive modeling. The project will develop, implement, and test a platform to assess host-pathogen molecular interactions, adaptation to hosts and host shifts, and coevolution between hosts and pathogens, successfully impacting the research community by revolutionizing abilities to study any host-pathogen interaction, encourage diverse community contributions, and gain fundamental insights into how proteins adapt to new contexts. This ability will be critical for designing early interventions to address future threats. We will build surveillance training capability, aiming for a fair and equitable response to future pandemics and biothreats.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Venus: Geology of Beta Regio rift system

Beta Regio is characterized by the existence of rift structures. We compiled new geologic maps of Beta Regio according to Magellan data. There are many large uplifted tesserae on beta upland. These tesserae are partly buried by younger volcanic cover. We can conclude, using these observations, that Beta upland formed mainly due to lithospheric tectonic uplifting and was only partly constructed by volcanism. Theia Mons is the center of the Beta rift system. Many rift belts are distributed radially to Theia Mons. Typical widths of rifts are 40-160 km. Rift valleys are structurally represented by crustal grabens or half-grabens. There are symmetrical and asymmetrical rifts. Many rifts have shoulder uplifts up to 0.5-1 km high and 40-60 km wide. Preliminary analysis for rift valley structural cross sections lead to the conclusion that rifts originated due to 5-10 percent crustal extension. Many rifts traverse Beta upland and spread to the surrounding lowlands. We can assume because of these data that Beta rift system has an active-passive origin. It formed due to regional tectonic lithospheric extension. Rifting was accelerated by upper-mantle hot spot origination under the center of passive extension (under the Beta Regio).

Nikishin, A. M.↗
NASA NTRS2001

Applications of the Hilbert-Huang Transform

A new method, the Hilbert-Huang Transform, has been developed for analyzing nonlinear and nonstationary data. The key part of the method is the Empirical Mode Decomposition with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An M is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies'as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. With this technique we can examine the detailed dynamics characteristics of a nonlinear system through the instantaneous frequency rather than harmonics. Thus it constitutes a new view of the nonlinear dynamics. Examples of classic nonlinear equations and other nonlinear and nonstationary data sets will be used as examples to illustrate the advantage of the application of this new data analysis method.

Huang, Norden E.↗
DOE OSTI2026

Measurement of fifth- and sixth-order fluctuations of (net-)proton number in Au + Au collisions from phase II of the beam energy scan program at RHIC

We report high-statistics measurements of fifth- and sixth-order factorial cumulants and cumulant ratios of (net-)proton multiplicity distributions in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7–27GeV, using data from the STAR experiment collected during the Beam Energy Scan Phase II at RHIC. Protons and antiprotons are identified at midrapidity (|𝑦| < 0.5) with transverse momentum 0.4 < 𝑝 𝑇 < 2.0GeV/𝑐. The proton factorial cumulants 𝜅 4 , 𝜅 5 , and 𝜅 6 increase with order but exhibit no sign alternation within current uncertainties, offering no evidence for a two-component structure in the proton multiplicity distribution, as might be expected near a first-order phase transition. The cumulant ratios 𝐶 5 /𝐶 1 and 𝐶 6 /𝐶 2 fluctuate around zero in collisions at 0–40% centrality. The results are consistent with both the negative predictions from lattice QCD and the positive trends obtained from the ultrarelativistic quantum molecular dynamics (UrQMD) model. At $\sqrt{s_{NN}}$ ≳ 27GeV, the 𝐶 4 /𝐶 2 and 𝐶 5 /𝐶 1 results are compatible with predictions from lattice QCD, functional renormalization group (FRG), and hadron resonance gas (HRG) models, while UrQMD describes the data better at lower energies. Here, these measurements place constraints on baryon number fluctuations and offer valuable insights into the QCD phase structure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Understanding Formation of Young, Distributed Low-mass Stars and Clusters in the W4 Cloud Complex

It is well known that most of the stars form in rich clusters. However, recent Spitzer observations have shown that a significant number of stars also form in the distributed mode; their origin is not well understood. In this work, we aim to investigate clustered and distributed modes of star formation in the W4 complex. To do so, we identified and characterized the young stellar population associated with the region using homogeneous infrared data sets obtained from the Two Micron All Sky Survey, GLIMPSE, MIPS, and Wide-field Infrared Survey Explorer surveys. We make stellar surface density and minimum spanning tree maps to identify young clusters, and use Spitzer images to identify irradiated structures, such as elephant-trunk-like structures (ETLSs) and pillars in the region. The surface density distribution of the young stellar objects (YSOs) reveals three new clusterings and ~50% distributed protostars in the H ii region. The clusters are of low-mass nature but significantly younger than the central cluster IC 1805. We identified ~ 38 ETLSs in the region, a majority of which consist of one or a few stars at their tips. We find that these stars are low-mass (<2 M {sub ⊙}) YSOs, located at the outskirts (>17 pc) of the cluster IC 1805 and are part of the scattered distributed population. We argued that the star formation in the ETLSs of W4 is going on possibly due to the triggering effect of the expanding W4 bubble. Although high-resolution photometric and spectroscopic data would be required to confirm the scenario, nonetheless, we discuss the implications of this scenario for our understanding of distributed low-mass star formation in cloud complexes as opposed to other mechanisms such as turbulent fragmentation and dynamical ejection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Zero-truncated Poisson regression for sparse multiway count data corrupted by false zeros

Abstract We propose a novel statistical inference methodology for multiway count data that is corrupted by false zeros that are indistinguishable from true zero counts. Our approach consists of zero-truncating the Poisson distribution to neglect all zero values. This simple truncated approach dispenses with the need to distinguish between true and false zero counts and reduces the amount of data to be processed. Inference is accomplished via tensor completion that imposes low-rank tensor structure on the Poisson parameter space. Our main result shows that an $N$-way rank-$R$ parametric tensor $\boldsymbol{\mathscr{M}}\in (0,\infty )^{I\times \cdots \times I}$ generating Poisson observations can be accurately estimated by zero-truncated Poisson regression from approximately $IR^2\log _2^2(I)$ non-zero counts under the nonnegative canonical polyadic decomposition. Our result also quantifies the error made by zero-truncating the Poisson distribution when the parameter is uniformly bounded from below. Therefore, under a low-rank multiparameter model, we propose an implementable approach guaranteed to achieve accurate regression in under-determined scenarios with substantial corruption by false zeros. Several numerical experiments are presented to explore the theoretical results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A Decision Support Tool for Distributed Solar and Storage Investments: A Case Study in Austin, TX

This study builds a decision support tool to evaluate when it is a good economic decision (least cost with minimum discomfort) for the residential customer to invest in distributed energy resources (DERs) based on different electricity rate structures, DER ownership frameworks, and DER rebates offered by electric utilities. Here, the tool is demonstrated using empirical electricity consumption data from Pecan Street Inc. (a non-profit entity based on Austin, Texas), residential rates from Austin Energy (the municipal electric utility in Austin, Texas), DER ownership costs from various nationwide pilot programs, and incentives offered by electric utilities in the United States. Results show that for constant electricity rates, the overall expenditure is least when the customer owns solar panels without storage, while for time-varying pricing structures, the least expensive scenario is one where the customer does not own any DERs. As the capital costs for DERs decline, utilities incentivize customer ownership of DERs, and more residential customers face the decision of whether to invest in DERs, this study aims to be a key tool in aiding that decision-making process.

14 SOLAR ENERGY↗
NASA NTRS1984

High-resolution, far-ultraviolet study of Beta Draconis (G2 Ib-II) - Transition region structure and energy balance

High-resolution far ultraviolet spectra of the star Beta Draconis have been obtained with the IUE satellite. The observations and emission line data from the spectra are presented, the interpretation of the emission line widths and shifts is discussed, and the implications are given in terms of atmospheric properties. The emission measure distribution is derived, and density diagnostics involving both line ratios and line opacity arguments is investigated. The methods for calculating spherically symmetric models of the atmospheric structure are outlined, and several such models are presented. The extension of these models to log T(e) greater than 5.3 using the observed X-ray flux is addressed, the energy balance of an 'optimum' model is investigated, and possible models of energy transport and deposition are discussed.

Brown, A.↗
DOE OSTI2026

Enhancing weak lensing redshift distribution characterization by optimizing the Dark Energy Survey Self-Organizing Map Photo-z method

Characterization of the redshift distribution of ensembles of galaxies is pivotal for large scale structure cosmological studies. In this work, we focus on improving the Self-Organizing Map (SOM) methodology for photometric redshift estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year 6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the underlying redshift distribution. We investigate three strategies for enhancing the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM algorithm with one tailored for redshift estimation challenges; 2) Incorporating $\textit{g}$-band flux information to refine redshift estimates (i.e. using $\textit{griz}$ fluxes as opposed to only $\textit{riz}$); 3) Augmenting redshift data for galaxies where available. These methods are applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our analysis indicates significant improvements with the first two strategies, notably reducing the overlap between redshift bins. By combining strategies 1 and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by up to 66$\%$. Conversely, the third strategy, involving the addition of redshift data for selected galaxies as an additional feature in the method, yields inferior results and is abandoned. Our findings contribute to the advancement of weak lensing redshift characterization and lay the groundwork for better redshift characterization in DES Year 6 and future stage IV surveys, like the Rubin Observatory.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2016

Validation of a Cephalad Fluid Shift Countermeasure

INTRODUCTION: This project will provide critical data required to objectively determine how an optimized thigh cuff could be incorporated into the NASA integrated physiological countermeasure suite. This project will determine if thigh cuffs used during simulated spaceflight impact intracranial pressure (ICP), ocular structure and function, and intraocular pressure (IOP) using state of-the-art techniques. Additionally, some of the same methods, hardware, and protocols will be employed in the present investigation to enable direct comparisons to the International Space Station (ISS) "Fluid Shifts" experiment with Chibis-Lower Body Negative Pressure (LBNP). This study will determine the temporal physiological responses of thigh cuff application and removal on ocular and cerebral variables (including invasive ICP) in a microgravity analog. Furthermore, this proposed study will determine tissue pressure distribution applied by thigh cuffs in order to improve comfort, mobility, and efficacy of the countermeasure. Our specific aim is to determine the efficacy of a novel thigh cuff device to mitigate cephalad fluid shifts. We hypothesize that a thigh cuff countermeasure employed in a microgravity analog will temporarily reverse or attenuate ocular and cerebral-volume-pressure variables, approaching normal Earth-based seated posture, the most frequent posture assumed in daily life. In addition, we hypothesize that the magnitude of fluid and pressure redistribution using a thigh cuff countermeasure may require a longer exposure time than that of Chibis-LBNP (using ground-based data from our "Fluid Shifts" project). This project directly addresses Critical Path Roadmap Risks and Questions regarding "Risk of Spaceflight-Induced Intracranial Hypertension/Vision Alterations," and IRP Gap VIIP13: We need to identify preventative and treatment countermeasures to mitigate changes in ocular structure and function and intracranial pressure during spaceflight. METHODS: Noninvasive measures and tissue pressure distributions beneath thigh cuffs The objectives of this study are to: 1) determine the distribution of skin surface pressures beneath the advanced thigh cuff in ten subjects, 2) calibrate the built-in pressure measurement system of the advanced thigh cuff using an industry standard device, and 3) collect subjective feedback and data on the new cuff design to allow for further adjustments prior to invasive studies. A Tekscan Industrial Sensing (I-Scan) system will measure the pressure distribution of the advanced thigh cuff against the skin. In addition, we will measure blood pooling in the thigh and record the circumference of the thigh using Hokanson strain gauge plethysmography. The advanced thigh cuff will be adjusted to obtain a skin contact pressure of 30-50 mmHg as visualized on the Tekscan system. The built-in advanced thigh cuff pressure monitor will be recorded simultaneously to allow direct comparison to the Tekscan measurements. The volunteer will then remove the thigh cuff and remain at rest for five minutes with no legging applied. The thigh cuff will be donned again and pressure measurements will be taken in the same manner for up to 10 repetitions to show reproducibility of pressure after donning. At the conclusion of the study, subjects will be asked to flex their knee, stand, walk, and sit with the thigh cuff activated. During each of these maneuvers the subject will rate their pain/comfort using a modified Borg scale. Effect of thigh cuffs on ICP during simulated microgravity Ommaya reservoir patients will be recruited from the John Wayne Cancer Institute. Ommaya reservoirs provide safe and direct access for the measurement of ICP. Subjects will be instrumented for continuous blood pressure, ECG, and invasive ICP measures. The subjects will be positioned in the upright sitting posture for a 10-minute stabilization period. After the 10-minute stabilization period, imaging measures [ICP, Optical Coherence Tomography, IOP, ocular and vascular ultrasound] will be performed. Following baseline seated measures, the subject will be positioned randomly in the supine, 15deg head-down-tilt, and 15deg head-down-tilt with thigh cuffs and measures repeated. DISCUSSION: Tests to down-select thigh cuff designs will occur in early 2016. Invasive ICP and noninvasive eye imaging tests will begin in spring 2016. Supported by NSBRI through NCC 9-58.

Macias, B.↗
DOE OSTI2020

Propagating sample variance uncertainties in redshift calibration: simulations, theory, and application to the COSMOS2015 data

ABSTRACT Cosmological analyses of galaxy surveys rely on knowledge of the redshift distribution of their galaxy sample. This is usually derived from a spectroscopic and/or many-band photometric calibrator survey of a small patch of sky. The uncertainties in the redshift distribution of the calibrator sample include a contribution from shot noise, or Poisson sampling errors, but, given the small volume they probe, they are dominated by sample variance introduced by large-scale structures. Redshift uncertainties have been shown to constitute one of the leading contributions to systematic uncertainties in cosmological inferences from weak lensing and galaxy clustering, and hence they must be propagated through the analyses. In this work, we study the effects of sample variance on small-area redshift surveys, from theory to simulations to the COSMOS2015 data set. We present a three-step Dirichlet method of resampling a given survey-based redshift calibration distribution to enable the propagation of both shot noise and sample variance uncertainties. The method can accommodate different levels of prior confidence on different redshift sources. This method can be applied to any calibration sample with known redshifts and phenotypes (i.e. cells in a self-organizing map, or some other way of discretizing photometric space), and provides a simple way of propagating prior redshift uncertainties into cosmological analyses. As a worked example, we apply the full scheme to the COSMOS2015 data set, for which we also present a new, principled SOM algorithm designed to handle noisy photometric data. We make available a catalogue of the resulting resamplings of the COSMOS2015 galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

The latitudinal distribution of magnetic holes in the solar wind

A large number of magnetic holes have been found in the Ulysses data during its cruise in the ecliptic. They are interpreted as convecting structures, probably caused by the mirror instability which exists in high beta plasmas with anisotropic temperatures. The characteristics of the holes reflect the solar wind condition of the region in which the holes are formed, and the point of observation may be far removed from where the instability occurs. A preliminary survey appears to indicate that the number of holes has no significant radial dependence. However, the number of holes does appear to increase with increasing heliographic latitude. Yet the large scale solar wind structures with their compression regions disappeared at approximately 57 deg south latitude. Thus any causal relationship between the holes and large scale solar wind structures is questionable. The temperature anisotropy and high beta required by the mirror instability must be generated by other mechanisms. In order to tie the magnetic holes and the mirror instability to their cause, the evolution of their characteristics with heliocentric distance and latitude needs to be investigated. With the progression of Ulysses around the sun a survey will be conducted to ascertain the characteristics of the magnetic holes as a function of heliographic latitude and heliocentric distance. A comparison of the results with the solar wind conditions may lead to the identification of the magnetic hole generating mechanism(s).

Winterhalter, D.↗
NASA NTRSDate not supplied

Characterizing Spatiotemporal Uncertainty in Interpolated Meteorological Data

Interpolated meteorological data invariably contain errors. These errors have structure in time and space, particularly autocorrelation, which can cause the effects of errors to compound when model outputs are aggregated temporally or spatially. One way to account for this uncertainty is with a probabilistic model from which samples can be drawn that are coherent with respect to underlying spatial and temporal covariance structure. This work describes a probabilistic method for spatial interpolation of point-wise meteorological time series. Observational data from weather stations are generally sparse in space and dense in time (but sometimes missing). The method works by projecting time series onto orthogonal basis vectors and spatially interpolating each resulting component independently. Under suitable assumptions, and data transformations to better satisfy those assumptions, Gaussian process regression provides a complete description of the joint predictive distribution over a Gaussian random field. Spatiotemporally coherent realizations are generated as the sum of conditional (spatial) simulations of each orthogonal (temporal) component. Data-derived and generic orthogonal bases are considered. In addition to spatial interpolation, imputation of missing observational data is examined. The method is applied using near-surface air temperature over the Western United States and validated by comparing theoretical versus actual coverage of predictive distributions and analyzing the degree to which spatial and temporal covariance structure is reproduced. Computational considerations, relating to conditional simulation of random fields, are also addressed.

Conor T Doherty↗
NASA NTRSDate not supplied

Summary of the First AIAA Stability and Control Prediction Workshop

Results from the First AIAA Stability and Control Prediction Workshop are summarized in this paper. The workshop series was developed in support of three primary objectives: (1) to establish best practices for the prediction of stability and control derivatives using industry-standard Computational Fluid Dynamics (CFD) solvers, (2) to provide an impartial forum for evaluating the effectiveness of Reynolds-averaged-Navier-Stokes- and Detached-Eddy-Simulation-based modeling techniques, and (3) to identify areas in need of additional research and development. To address these objectives, the inaugural workshop focused on generating computational aerodynamic predictions for the ONERA version of the NASA/Boeing Common Research Model. The configuration includes the wing, body, horizontal tail, and a vertical tail designed by ONERA. While longitudinal wind tunnel test data for the model had been previously documented, unpublished lateral test data at small sideslip angles provided a unique opportunity for participants to generate blind computational predictions for wind tunnel data comparisons. Additional test cases included assessments of the Mach number effect on static lateral/directional stability and the impact of the wind tunnel sting on longitudinal stability. Participants were invited to generate solutions using two workshop-provided series of structured overset and unstructured grids, in addition to any participant custom grids of interest. Total and component-level breakdowns for the force and moment coefficients for each test case are presented, as well as sectional pressure distribution data on the wing and tail components, to assess the agreement between several different Reynolds-averaged Navier-Stokes CFD solvers.

CFD↗
NASA NTRS2011

Saturn's Magnetosphere Interaction with Titan for T9 Encounter: 3D Hybrid Modeling and Comparison with CAPS Observations

Global dynamics of ionized and neutral gases in the environment of Titan plays an important role in the interaction of Saturn s magnetosphere with Titan. Several hybrid simulations of this problem have already been done (Brecht et al., 2000; Kallio et al., 2004; Modolo et al., 2007a; Simon et al., 2007a, 2007b; Modolo and Chanteur, 2008). Observational data from CAPS for the T9 encounter (Sittler et al., 2009) indicates an absence of O(+) heavy ions in the upstream that change the models of interaction which were discussed in current publications (Kallio et al., 2004; Modolo et al., 2007a; Simon et al., 2007a, 2007b; Ma et al., 2007; Szego et al., 2007). Further analysis of the CAPS data shows very low density or even an absence of H(+) ions in upstream. In this paper we discuss two models of the interaction of Saturn s magnetosphere with Titan: (A) high density of H(+) ions in the upstream flow (0.1/cu cm), and (B) low density of H(+) ions in the upstream flow (0.02/cu cm). The hybrid model employs a fluid description for electrons and neutrals, whereas a particle approach is used for ions. We also take into account charge-exchange and photoionization processes and solve self-consistently for electric and magnetic fields. The model atmosphere includes exospheric H(+), H(2+), N(2+)and CH(4+) pickup ion production as well as an immobile background ionosphere and a shell distribution for active ionospheric ions (M(sub i)=28 amu). The hybrid model allows us to account for the realistic anisotropic ion velocity distribution that cannot be done in fluid simulations with isotropic temperatures. Our simulation shows an asymmetry of the ion density distribution and the magnetic field, including the formation of Alfven wing-like structures. The results of the ion dynamics in Titan s environment are compared with Cassini T9 encounter data (CAPS).

Lipatov, A. S.↗
DOE OSTI2021

Machine learning based inverse modeling of full-field strain distribution for mechanical characterization of a linear elastic and heterogeneous membrane

Heterogeneous membranes or films are thin and soft structures with spatial variations in material property and thickness. Mechanical behavior of heterogeneous membranes is not well understood, mainly due to the difficulty in obtaining accurate and reliable material property data. To understand the mechanical behavior of these materials, accurate and efficient characterization methods for heterogeneous membranes are needed. Here, in this paper, an inverse method based on machine learning is developed to efficiently extract mechanical properties from full-field strain distributions. This approach is demonstrated on a flat heterogeneous membrane with uniform thickness formed by up to four linear elastic synthetic materials in a grid arrangement, and deforming in a moderate strain range (true strain ~10%). The results show that the machine learning method achieves accuracy comparable to the traditional inverse finite element method, and is 6 orders of magnitude faster in the demonstrated case studies.

36 MATERIALS SCIENCE↗