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At least 55 records · Page 3

In-Flight Calibration Methods for Temperature-Dependent Offsets in the MMS Fluxgate Magnetometers

During the first dayside season of the Magnetospheric Multiscale (MMS) mission, the in-flight calibration process for the Fluxgate magnetometers (FGM) implemented an algorithm that selected a constant offset (zero-level) for each sensor on each orbit. This method was generally able to reduce the amplitude of residual spin tone to less than 0.2 nT within the region of interest. However, there are times when the offsets do show significant short-term variations. These variations are most prominent in the nighttime season (phase 1X), when eclipses are accompanied by offset changes as large as 1 nT. Eclipses are followed by a recovery period as long as 12 hours where the offsets continue to change as temperatures stabilize. Understanding and compensating for these changes will become critical during Phase 2 of the mission in 2017, when the nightside will become the focus of MMS science. Although there is no direct correlation between offset and temperature, the offsets are seen for the period of any given week to be well-characterized as function of instrument temperature. Using this property, a new calibration method has been developed that has proven effective in compensating for temperature-dependent offsets during phase 1X of the MMS mission and also promises to further refine calibration quality during the dayside season.

Magnetic field reconnection

In-Flight Calibration of the MMS Fluxgate Magnetometers

We present an overview of the approach to in-flight calibration, which is a coordinated effort between the University of California Los Angeles (UCLA), Space Research Institute, Graz, Austria (IWF) and the NASA Goddard Space Flight Center (GSFC). We present details of the calibration effort at GSFC. During the first dayside season of the Magnetospheric Multiscale (MMS) mission, the in-flight calibration process for the Fluxgate magnetometers (FGM) implemented an algorithm that selected a constant offset (zero-level) for each sensor on each orbit. This method was generally able to reduce the amplitude of residual spin tone to less than 0.2 nT within the region of interest. However, there are times when the offsets do show significant short-term variations. These variations are most prominent in the nighttime season (phase 1X), when eclipses are accompanied by offset changes as large as 1 nT. Eclipses are followed by a recovery period as long as 12 hours where the offsets continue to change as temperatures stabilize. Understanding and compensating for these changes will become critical during Phase 2 of the mission in 2017, when the nightside will become the focus of MMS science. Although there is no direct correlation between offset and temperature, the offsets are seen for the period of any given week to be well-characterized as function of instrument temperature. Using this property, a new calibration method has been developed that has proven effective in compensating for temperature-dependent offsets during phase 1X of the MMS mission and also promises to further refine calibration quality during the dayside season.

Magnetic field reconnection

Additive Manufacturing Model-Based Process Metrics: Reduced Order Modeling of the Laser Powder Bed Fusion Process

The multi-scale and complex process of printing additively manufactured (AM) parts can have unexpected, but predictable, build conditions that result in material microstructure variability. In this work, we describe a fully parallel reduced order modeling approach that has been developed to evaluate the evolution of AM processes, termed the AM moment measure method. This method couples the known sequence of the AM process with a physically informed nearest neighbors’ calculation to map the conditions of a part-scale build. The result is a map of the build that is derived directly from build files or in-situ process monitoring sensors. The methodology and terminology of the approach will be described, and computed build maps will be calculated and compared for various laser powder bed fusion (LPBF) builds of Ti-6Al-4V. Such comparative results develop understanding of how the sequential process actions can affect the LPBF-AM build quality and microstructure variability.

Laser Powder Bed Fusion

Fractals and Spatial Methods for Mining Remote Sensing Imagery

The rapid increase in digital remote sensing and GIS data raises a critical problem -- how can such an enormous amount of data be handled and analyzed so that useful information can be derived quickly? Efficient handling and analysis of large spatial data sets is central to environmental research, particularly in global change studies that employ time series. Advances in large-scale environmental monitoring and modeling require not only high-quality data, but also reliable tools to analyze the various types of data. A major difficulty facing geographers and environmental scientists in environmental assessment and monitoring is that spatial analytical tools are not easily accessible. Although many spatial techniques have been described recently in the literature, they are typically presented in an analytical form and are difficult to transform to a numerical algorithm. Moreover, these spatial techniques are not necessarily designed for remote sensing and GIS applications, and research must be conducted to examine their applicability and effectiveness in different types of environmental applications. This poses a chicken-and-egg problem: on one hand we need more research to examine the usability of the newer techniques and tools, yet on the other hand, this type of research is difficult to conduct if the tools to be explored are not accessible. Another problem that is fundamental to environmental research are issues related to spatial scale. The scale issue is especially acute in the context of global change studies because of the need to integrate remote-sensing and other spatial data that are collected at different scales and resolutions. Extrapolation of results across broad spatial scales remains the most difficult problem in global environmental research. There is a need for basic characterization of the effects of scale on image data, and the techniques used to measure these effects must be developed and implemented to allow for a multiple scale assessment of the data before any useful process-oriented modeling involving scale-dependent data can be conducted. Through the support of research grants from NASA, we have developed a software module called ICAMS (Image Characterization And Modeling System) to address the need to develop innovative spatial techniques and make them available to the broader scientific communities. ICAMS provides new spatial techniques, such as fractal analysis, geostatistical functions, and multiscale analysis that are not easily available in commercial GIS/image processing software. By bundling newer spatial methods in a user-friendly software module, researchers can begin to test and experiment with the new spatial analysis methods and they can gauge scale effects using a variety of remote sensing imagery. In the following, we describe briefly the development of ICAMS and present application examples.

Lam, Nina

Global Evolution of Solar Magnetic Fields and Prediction of Solar Activity Cycles

Prediction of solar activity cycles is challenging because the physical processes inside the Sun involve a broad range of multiscale dynamics that no model can reproduce, and the available observations are highly limited and cover mostly surface layers. Helioseismology makes it possible to probe solar dynamics in the convective zone, but variations in the differential rotation and meridional circulation are currently available for only two solar activity cycles. It has been demonstrated that sunspot observations, which cover over 400 years, can be used to calibrate the Parker-Kleeorin-Ruzmaikin model and that the Ensemble Kalman Filter (EnKF) method can be used to link the model magnetic fields to sunspot observations to make reliable predictions of a following cycle. However, for more accurate predictions, it is necessary to use actual observations of the solar magnetic fields, which are available for only four solar cycles. This raises the question of how limitations in observational data and model uncertainties affect predictive capabilities and implies the need for the development of new forecast methodologies and validation criteria. In this presentation, I will discuss the influence of the limited number of available observations on the accuracy of EnKF estimates of solar cycle parameters.

Kitiashvili, Irina N.

Statistical study of favorable foreshock ion properties for the formation of hot flow anomalies and foreshock bubbles

Hot flow anomalies (HFAs) and foreshock bubbles (FBs) are frequently observed in Earth's foreshock, which can significantly disturb the bow shock and therefore the magnetosphere-ionosphere system and can accelerate particles. Previous statistical studies have identified the solar wind conditions (high solar wind speed and high Mach number, etc.) that favor their generation. However, backstreaming foreshock ions are expected to most directly control how HFAs and FBs form, whereas the solar wind may partake in the formation process indirectly by determining foreshock ion properties. Using Magnetospheric Multiscale mission and Time History of Events and Macroscale Interactions during Substorms mission, we perform a statistical study of foreshock ion properties around 275 HFAs and FBs. We show that foreshock ions with a high foreshock-to-solar wind density ratio (>∼3%), high kinetic energy (>∼600 eV), large ratio of kinetic energy to thermal energy (>∼0.1), and large ratio of perpendicular temperature to parallel temperature (>∼1.4) favor HFA and FB formation. We also examine how these properties are related to solar wind conditions: high solar wind speed and oblique bow shock (angle between the interplanetary magnetic field and the bow shock normal 𝜃Bn∼45°) favor high kinetic energy of foreshock ions; foreshock ions have large ratio of kinetic energy to thermal energy at large 𝐴𝐴𝐴𝐴Bn (>30°); small 𝐴𝐴𝐴𝐴Bn (<30°), high Mach number, and closeness to the bow shock favor a high foreshock-to-solar wind density ratio. Our results provide further understanding of HFA and FB formation.

Terry Z. Liu

Environmental analysis using integrated GIS and remotely sensed data - Some research needs and priorities

This paper discusses some basic scientific issues and research needs in the joint processing of remotely sensed and GIS data for environmental analysis. Two general topics are treated in detail: (1) scale dependence of geographic data and the analysis of multiscale remotely sensed and GIS data, and (2) data transformations and information flow during data processing. The discussion of scale dependence focuses on the theory and applications of spatial autocorrelation, geostatistics, and fractals for characterizing and modeling spatial variation. Data transformations during processing are described within the larger framework of geographical analysis, encompassing sampling, cartography, remote sensing, and GIS. Development of better user interfaces between image processing, GIS, database management, and statistical software is needed to expedite research on these and other impediments to integrated analysis of remotely sensed and GIS data.

Davis, Frank W.

Materials Informatics at NASA GRC: Machine Learning Surrogate Modeling, Data Management, and Integrated Toolsets for Establishing/Maintaining the Digital Thread

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which heavily depend on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results that is findable and usable, along with integrated, efficient toolsets for effectively passing information across various length and time scales across such models. At the NASA Glenn Research Center under the Transformational Tools and Technologies Project, significant recent efforts have been directed towards establishing the required cyberinfrastructure to enable optimized ICME processes and the design of “fit-for-purpose” materials to achieve the goals outlined in the NASA Vision 2040 report. Such efforts include development of multiscale physics-based material models, which can be used to train highly efficient surrogate machine learning models, development of best practices and infrastructure for effective, traceable materials information management, and development of toolsets that integrate with physics-based codes, machine learning models, and an information management system to enable high throughput of materials data collection and analysis, establishment of digital twins and the digital thread, and automation of the ICME design process for material optimization.

Machine Learning

Multiscale Modeling of Solar Coronal Magnetic Reconnection

Magnetic reconnection is widely believed to be the primary process by which the magnetic field releases energy to plasma in the Sun's corona. For example, in the breakout model for the initiation of coronal mass ejections/eruptive flares, reconnection is responsible for the catastrophic destabilizing of magnetic force balance in the corona, leading to explosive energy release. A critical requirement for the reconnection is that it have a "switch-on' nature in that the reconnection stays off until a large store of magnetic free energy has built up, and then it turn on abruptly and stay on until most of this free energy has been released. We discuss the implications of this requirement for reconnection in the context of the breakout model for CMEs/flares. We argue that it imposes stringent constraints on the properties of the flux breaking mechanism, which is expected to operate in the corona on kinetic scales. We present numerical simulations demonstrating how the reconnection and the eruption depend on the effective resistivity, i.e., the effective Lundquist number, and propose a model for incorporating kinetic flux-breaking mechanisms into MHO calculation of CMEs/flares.

Antiochos, Spiro K.

Comparison of Magnetospheric Multiscale Ion Jet Signatures with Predicted Reconnection Site Locations at the Magnetopause

Magnetic reconnection at the Earths magnetopause is the primary process by which solar wind plasma and energy gains access to the magnetosphere. One indication that magnetic reconnection is occurring is the observation of accelerated plasma as a jet tangential to the magnetopause. The direction of ion jets along the magnetopause surface as observed by the Fast Plasma Instrument (FPI) and the Hot Plasma Composition Analyzer (HPCA) instrument on board the recently launched Magnetospheric Multiscale (MMS) set of spacecraft is examined. For those cases where ion jets are clearly discerned, the direction of origin compares well statistically with the predicted location of magnetic reconnection using convected solar wind observations in conjunction with the Maximum Magnetic Shear model.

Petrinec, S. M.

Advanced Modeling Techniques to Study Anthropogenic Influences on Atmospheric Chemical Budgets

This research work is a collaborative effort between research groups at MCNC and the University of North Carolina at Chapel Hill. The overall objective of this research is to improve the level of understanding of the processes that determine the budgets of chemically and radiatively active compounds in the atmosphere through development and application of advanced methods for calculating the chemical change in atmospheric models. The research performed during the second year of this project focused on four major aspects: (1) The continued development and refinement of multiscale modeling techniques to address the issue of the disparate scales of the physico-chemical processes that govern the fate of atmospheric pollutants; (2) Development and application of analysis methods utilizing process and mass balance techniques to increase the interpretive powers of atmospheric models and to aid in complementary analysis of model predictions and observations; (3) Development of meteorological and emission inputs for initial application of the chemistry/transport model over the north Atlantic region; and, (4) The continued development and implementation of a totally new adaptive chemistry representation that changes the details of what is represented as the underlying conditions change.

Mathur, Rohit

Magnetospheric Multiscale Observations of an Expanding Oxygen Wave in Magnetic Reconnection

Heavier plasma species such as oxygen ions can have a large impact on the magnetic reconnection process. It has been hypothesized that the acceleration of demagnetized oxygen ions by the Hall electric field will lead to the formation of an oxygen wave that expands into the exhaust. By comparing data from NASA's Magnetospheric Multiscale mission to a fully kinetic particle-in-cell simulation, we can for the first time provide observational evidence of such an expanding oxygen wave. The wave is characterized by an oxygen jet consisting of cold ions directed toward the neutral sheet associated with a density cavity. This density cavity forms as the EO are subject to collective acceleration by the Hall electric field leaving behind a region of low-density oxygen ions. Our results are important for the understanding of the role and effect of oxygen ions in magnetic reconnection.

Hakon Midthun Kolsto

Modeling and Characterization of Damage Processes in Metallic Materials

This paper describes a broad effort that is aimed at understanding the fundamental mechanisms of crack growth and using that understanding as a basis for designing materials and enabling predictions of fracture in materials and structures that have small characteristic dimensions. This area of research, herein referred to as Damage Science, emphasizes the length scale regimes of the nanoscale and the microscale for which analysis and characterization tools are being developed to predict the formation, propagation, and interaction of fundamental damage mechanisms. Examination of nanoscale processes requires atomistic and discrete dislocation plasticity simulations, while microscale processes can be examined using strain gradient plasticity, crystal plasticity and microstructure modeling methods. Concurrent and sequential multiscale modeling methods are being developed to analytically bridge between these length scales. Experimental methods for characterization and quantification of near-crack tip damage are also being developed. This paper focuses on several new methodologies in these areas and their application to understanding damage processes in polycrystalline metals. On-going and potential applications are also discussed.

Glaessgen, E. H.

Particle Acceleration by Dense Impulsive Structures Moving in Ambient Magnetospheric Plasma. 3-D Hybrid Kinetic Modeling and MMS Observations

High resolution observations of dense plasma impulsive structures moving through an ambient background magnetospheric flows were captured by the Magnetospheric Multiscale mission. The observations show particle heating and acceleration, shock-like wave formation, and whistler wave excitation inside the interface between the dense impulsive plasma structures and the ambient plasma. A multiscale hybrid kinetic simulation provides an explanation of the observed wave-particle interactions with the assumption that the dense plasma structures may be represented by plasma clouds which are formed at the magnetopause layer due to reconnection processes. Plain Language Summary: Dense, impulsive plasma structures moving through a background plasma were captured by the NASA Magnetospheric Multiscale mission. The observations show that the dense structures can generate strong perturbations in the electromagnetic field and shock-like waves. Interactions between these electromagnetic waves and the particles results in particle acceleration. 3-D hybrid kinetic modeling (particle description for ions and fluid description for electrons) was used to investigate the plasma physics of the observed structures. It was assumed that the plasma clouds were formed by magnetic field reconnection inside the magnetopause, which is the interface between the solar wind particles and the cold low-density magnetospheric plasma. The work helps us understand the plasma environment at the interface between the Earth and solar wind, near planetary moons, within astrophysical explosions, and possibly at the interface between the solar wind and local interstellar medium.

A. S. Lipatov

Modeling Images of Natural 3D Surfaces: Overview and Potential Applications

Generative models of natural images have long been used in computer vision. However, since they only describe the of 2D scenes, they fail to capture all the properties of the underlying 3D world. Even though such models are sufficient for many vision tasks a 3D scene model is when it comes to inferring a 3D object or its characteristics. In this paper, we present such a generative model, incorporating both a multiscale surface prior model for surface geometry and reflectance, and an image formation process model based on realistic rendering, the computation of the posterior model parameter densities, and on the critical aspects of the rendering. We also how to efficiently invert the model within a Bayesian framework. We present a few potential applications, such as asteroid modeling and Planetary topography recovery, illustrated by promising results on real images.

Jalobeanu, Andre

The Role of Auroral Imaging in Understanding Ionosphere-Inner Magnetosphere Interactions

The more ways we probe the ionosphere and inner magnetosphere, the better we can understand their interaction. For example, the multifaceted imaging of geospace with the IMAGE mission complements the more traditional in situ measurements made with many previous missions. Together they have enabled new knowledge of the ionosphere-magnetosphere (IM) coupling. The role of imaging the aurora in understanding this interaction has received renewed attention recently. Based on in situ data, such as FAST or DMSP, and our recent theories, we believe that imaging multiscale features of the aurora is a key component to gaining insight into the processes and mechanisms at work. This talk will explore how auroral imaging can be used to provide improved insight of the dynamics of IM interaction on micro and meso scales, with an emphasis on the current limitations and future possibilities of quantitative analyses.

Spann, Jim

Geometric Sensitivity of Residual Fields in Metal Additive Manufacturing

The sensitivity of geometrical parameters on the residual stress and distortion as computed by a metal additive manufacturing simulation is presented. A nozzle-like geometry was chosen with its length, wall thickness, and outer radius varied. A Latin hypercube sampling of 300 specimens produced the combinations of the geometrical parameters. Full thermomechanical simulations predicted the residual fields. Statistical analysis including regression curves shows that there is a strong correlation between these residual fields and the geometry, hinting that it may be possible to predictably influence the residual displacements and residual stresses by varying the overall geometry.

Multiscale Modeling

Comparison of Multiscale Method of Cells-Based Models for Predicting Elastic Properties of Filament Wound C/C-SiC

Three different multiscale models, based on the method of cells (generalized and high fidelity) micromechanics models were developed and used to predict the elastic properties of C/C-SiC composites. In particular, the following multiscale modeling strategies were employed: Concurrent multiscale modeling of all phases using the generalized method of cells, synergistic (two-way coupling in space) multiscale modeling with the generalized method of cells, and hierarchical (one-way coupling in space) multiscale modeling with the high fidelity generalized method of cells. The three models are validated against data from a hierarchical multiscale finite element model in the literature for a repeating unit cell of C/C-SiC. Furthermore, the multiscale models are used in conjunction with classical lamination theory to predict the stiffness of C/C-SiC plates manufactured via a wet filament winding and liquid silicon infiltration process recently developed by the German Aerospace Institute.

multiscale modeling