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At least 325 records · Page 18

SOFIA Program SE and I Lessons Learned

Once a "Troubled Project" threatened with cancellation, the Stratospheric Observatory for Infrared Astronomy (SOFIA) Program has overcome many difficult challenges and recently achieved its first light images. To achieve success, SOFIA had to overcome significant deficiencies in fundamental Systems Engineering identified during a major Program restructuring. This presentation will summarize the lessons learn in Systems Engineering on the SOFIA Program. After the Program was reformulated, an initial assessment of Systems Engineering established the scope of the problem and helped to set a list of priorities that needed to be work. A revised Systems Engineering Management Plan (SEMP) was written to address the new Program structure and requirements established in the approved NPR7123.1A. An important result of the "Technical Planning" effort was the decision by the Program and Technical Leadership team to re-phasing the lifecycle into increments. The reformed SOFIA Program Office had to quickly develop and establish several new System Engineering core processes including; Requirements Management, Risk Management, Configuration Management and Data Management. Implementing these processes had to consider the physical and cultural diversity of the SOFIA Program team which includes two Projects spanning two NASA Centers, a major German partnership, and sub-contractors located across the United States and Europe. The SOFIA Program experience represents a creative approach to doing "System Engineering in the middle" while a Program is well established. Many challenges were identified and overcome. The SOFIA example demonstrates it is never too late to benefit from fixing deficiencies in the System Engineering processes.

Ray, Ronald J.↗

A Briefing on Metrics and Risks for Autonomous Decision-Making in Aerospace Applications

Significant technology advances will enable future aerospace systems to safely and reliably make decisions autonomously, or without human interaction. The decision-making may result in actions that enable an aircraft or spacecraft in an off-nominal state or with slightly degraded components to achieve mission performance and safety goals while reducing or avoiding damage to the aircraft or spacecraft. Some key technology enablers for autonomous decision-making include: a continuous state awareness through the maturation of the prognostics health management field, novel sensor development, and the considerable gains made in computation power and data processing bandwidth versus system size. Sophisticated algorithms and physics based models coupled with these technological advances allow reliable assessment of a system, subsystem, or components. Decisions that balance mission objectives and constraints with remaining useful life predictions can be made autonomously to maintain safety requirements, optimal performance, and ensure mission objectives. This autonomous approach to decision-making will come with new risks and benefits, some of which will be examined in this paper. To start, an account of previous work to categorize or quantify autonomy in aerospace systems will be presented. In addition, a survey of perceived risks in autonomous decision-making in the context of piloted aircraft and remotely piloted or completely autonomous unmanned autonomous systems (UAS) will be presented based on interviews that were conducted with individuals from industry, academia, and government.

Frost, Susan↗

High-resolution Laboratory Measurements of K-shell X-ray Line Polarization and Excitation Cross Sections in Helium-like S XV Ions

We report measurements of electron-impact excitation cross sections for the strong K-shell n = 2 -> 1 transitions in S XV, using the LLNL EBIT-I electron beam ion trap, two crystal spectrometers, and the EBIT Calorimeter Spectrometer. The cross sections are determined by direct normalization to the well-known cross sections of radiative electron capture, measured simultaneously. Using contemporaneous polarization measurements with the two crystal spectrometers, whose dispersion planes are oriented parallel and perpendicular to the electron beam direction, the polarization of the direct excitation line emission is determined, and in turn the isotropic total cross sections are extracted. We further experimentally investigate various line-formation mechanisms, finding that radiative cascades and collisional inner-shell ionization dominate the degree of linear polarization and total line emission cross sections of the forbidden line, z.

atomic data↗

Interrogating Solar Flare Loop Models with IRIS Observations 2: Plasma Properties, Energy Transport, and Future Directions

During solar flares a tremendous amount of magnetic energy is released and transported through the Sun’s atmosphere and out into the heliosphere. Despite over a century of study, many unresolved questions surrounding solar flares are still present. Among those are how does the solar plasma respond to flare energy deposition, and what are the important physical processes that transport that energy from the release site in the corona through the transition region and chromosphere? Attacking these questions requires the concert of advanced numerical simulations and high spatial-, temporal-, and spectral-resolution observations. While flares are 3D phenomenon, simulating the NLTE flaring chromosphere in 3D and performing parameter studies of 3D models is largely outwith our current computational capabilities. We instead rely on state-of-the-art 1D field-aligned simulations to study the physical processes that govern flares. Over the last decade, data from the Interface Region Imaging Spectrograph (IRIS) have provided the crucial observations with which we can critically interrogate the predictions of those flare loop models. Here in Paper 2 of a two-part review of IRIS and flare loop models, I discuss how forward modelling flares can help us understand the observations from IRIS, and how IRIS can reveal where our models do well and where we are likely missing important processes, focussing in particular on the plasma properties, energy transport mechanisms, and future directions of flare modelling.

solar flares↗

Long-term persistence of solar activity

We examine the question of whether or not the non-periodic variations in solar activity are caused by a white-noise, random process. The Hurst exponent, which characterizes the persistence of a time series, is evaluated for the series of C-14 data for the time interval from about 6000 BC to 1950 AD. We find a constant Hurst exponent, suggesting that solar activity in the frequency range from 100 to 3000 years includes an important continuum component in addition to the well-known periodic variations. The value we calculate, H approximately 0.8, is significantly larger than the value of 0.5 that would correspond to variations produced by a white-noise process. This value is in good agreement with the results for the monthly sunspot data reported elsewhere, indicating that the physics that produces the continuum is a correlated random process and that it is the same type of process over a wide range of time interval lengths.

Ruzmaikin, Alexander↗

Long-term persistence of solar activity

The solar irradiance has been found to change by 0.1% over the recent solar cycle. A change of irradiance of about 0.5% is required to effect the Earth's climate. How frequently can a variation of this size be expected? We examine the question of the persistence of non-periodic variations in solar activity. The Huerst exponent, which characterizes the persistence of a time series (Mandelbrot and Wallis, 1969), is evaluated for the series of C-14 data for the time interval from about 6000 BC to 1950 AD (Stuiver and Pearson, 1986). We find a constant Huerst exponent, suggesting that solar activity in the frequency range of from 100 to 3000 years includes an important continuum component in addition to the well-known periodic variations. The value we calculate, H approximately equal to 0.8, is significantly larger than the value of 0.5 that would correspond to variations produced by a white-noise process. This value is in good agreement with the results for the monthly sunspot data reported elsewhere, indicating that the physics that produces the continuum is a correlated random process (Ruzmaikin et al., 1992), and that is is the same type of process over a wide range of time interval lengths. We conclude that the time period over which an irradiance change of 0.5% can be expected to occur is significantly shorter than that which would be expected for variations produced by a white-noise process.

Ruzmaikin, Alexander↗

Scan strategies in EBM-printed IN718 and the physics of bulk 3D microstructure development

Three-dimensional (3D) characterization provides opportunities for understanding processing-structure relationships in additively manufactured (AM) materials. Bulk samples of Inconel 718 were fabricated via electron beam melting (EBM) in order to study microstructural development as a function of energy input and beam scan strategy. TriBeam tomography of bulk Inconel 718 microstructures built under steady-state growth conditions reveals the sensitivity of microstructure formation and evolution to machine process parameters. Here, samples manufactured using a narrow range of energy input per unit build area result in varied grain morphologies and crystallographic textures. Using TRUCHAS, a thermal simulation software, the thermal history of bulk scan strategies was predicted, and combined with a calibrated microstructure-processing map to accurately predict bulk grain morphologies. The solidification parameters and the 3D measured nucleation density are used to predict the transition between columnar and equiaxed grain morphologies, providing a process map to guide AM parameter choices to locally control as-printed microstructure. A two-dimensional metric for characterizing bulk grain morphology was also found to agree well with predictions from the process map calibrated by 3D data. Combined with 3D tomography and thermal modelling, the physics of structure development were understood at a new level of detail with respect to the competing processes of grain nucleation and epitaxial growth.

36 MATERIALS SCIENCE↗

Impact of gel concentration on filter fluxes in microfiltration of Hanford tank wastes and simulants

Abstract Treatment processes have been proposed that will utilize crossflow filtration to concentrate sludge waste streams at the Department of Energy's Hanford Site. Challenges associated with solid–liquid separation of the waste streams drive a necessary evaluation of available Hanford high level waste (HLW) filtration data. Limiting flux conditions during crossflow filtration are elucidated with the formation of a cake layer on the membrane surface. A mass transfer coefficient between the gel and bulk concentrations plays a critical role in determining filter flux. A correlation between the gel concentration and mass transfer coefficient is made to assist in determining filter performance of select HLW streams. As a process alternative to crossflow filtration, gravity settling of waste streams may be deployed as a solid–liquid separation technique. However, this results in a contrasting performance with the centrifuged solids concentration. A method was developed to estimate expected filtration and settling performance based on physical characterization data for Hanford tank waste samples. By assessing the estimated processing performance of HLW, technical support can be provided during flowsheet planning.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

AOIPS water resources data management system

The text and computer-generated displays used to demonstrate the AOIPS (Atmospheric and Oceanographic Information Processing System) water resources data management system are investigated. The system was developed to assist hydrologists in analyzing the physical processes occurring in watersheds. It was designed to alleviate some of the problems encountered while investigating the complex interrelationships of variables such as land-cover type, topography, precipitation, snow melt, surface runoff, evapotranspiration, and streamflow rates. The system has an interactive image processing capability and a color video display to display results as they are obtained.

Vanwie, P.↗

DE 1 RIMS operational characteristics

The Retarding Ion Mass Spectrometer (RIMS) on the Dynamics Explorer 1 spacecraft observes both the thermal and superthermal (50 eV) ions of the ionosphere and inner magnetosphere. It is capable of measuring the detailed species distribution function of these ions in many cases. It was equipped with an integral electrometer to permit in-flight calibration of the detector sensitivities and variations thereof. A guide to understanding the RIMS data set is given. The reduction process from count rates to physical quantities is discussed in some detail. The procedure used to establish in-flight calibration is described, and results of a comparison with densities from plasma wave measurements are provided. Finally, a discussion is provided of various anomalies in the data set, including changes of channeltron efficiency with time, spin modulation of the axial sensor heads, apparent potential differences between the sensor heads, and failures of the radial head retarding potential sweep and of the -Z axial head aperture plane bias. Studies of the RIMS data set should be conducted only with a thorough awareness of the material presented here, or in collaboration with one of the scientists actively involved with RIMS data analysis.

Olsen, R. C.↗

Heterogeneous physicochemistry of the polar ozone hole

Processes occurring in the polar winter stratosphere, which involve polar stratospheric clouds (PSCs), are investigated using observations from the Airborne Antarctic Ozone Experiment. In particular, data on the properties of PSCs and their physical chemistry, the microphysical processes and time constants for cloud processes, the heterogeneous chemical processes and their time constants, and nonlinearities in the long-term ozone trend associated with physical and chemical processes are examined. The chemical reactions leading to the depletion of the inert chlorine reservoir in a presence of type I PSCs are established, and it is shown that type II PSCs contribute to chemical processing that sustains the chemical imbalance of the polar stratosphere. It is shown that, using a simple model, the decadal evolution of the Antarctic ozone hole may be understood through nonlinearities in the heterogeneous chemistry, with possible contributing effects of variations in stratospheric temperatures and water vapor concentrations.

Turco, Richard P.↗

Generation and physical characteristics of the Landsat 1 and 2 MSS computer compatible tapes

The generation and format is discussed of the Landsat 1 and 2 system corrected multispectral scanner computer compatible tapes. Included in the discussion are the spacecraft sensors, scene characteristics, the transmission of data, and the conversion of the data to computer compatible tapes at the NASA Data Processing Facility. Geometric and radiometric corrections, tape formats, and the physical characteristics of the tape are also described.

Thomas, V. L.↗

The 1980 eruptions of Mount St. Helens - Physical and chemical processes in the stratospheric clouds

The large and diverse set of observational data collected in the high-altitude plumes of the May 18, May 25, and June 13, 1980 eruptions is organized and analyzed with a view to discerning the processes at work. The data serve to guide and constrain detailed model simulations of the volcanic clouds. For this purpose, use is made of a comprehensive one-dimensional model of stratospheric sulfate aerosols, sulfur precursor gases, and volcanic ash and dust. The model takes into account gas-phase and condensed-phase (heterogeneous) chemistry in the clouds, aerosol nucleation and growth, and cloud expansion. Computational results are presented for the time histories of the gaseous species concentrations, aerosol size distributions, and ash burdens of the eruption clouds. Also investigated are the long-term buildup of stratospheric aerosols in the Northern Hemisphere and the persistent effects of injected chlorine and water vapor on stratospheric ozone. It is concluded that SO2, water vapor, and ash were probably the most important substances injected into the stratosphere by the Mount St. Helens volcano, both with respect to their widespread effects on composition and their effect on climate.

Turco, R. P.↗

A quasi-Lagrangian diagnostic case study of the effect of satellite sounding data assimilation on model cyclone prediction

A quasi-Lagrangian diagnostic study was performed to compare weather forecast accuracy with and without use of satellite data. Attention was focused on the mass and angular momentum budgets of the cyclone. The diagnostic study isolated the effects of physical processes within a cyclone and the effects of transport processes moving with the cyclone. Satellite data furnished different initialization values for horizontal mass and eddy angular momentum. Colder temperatures and weaker stabilities in the NW quadrant lower layers in the budget volume and increased stability in the middle and lower layers of another quadrant were obtained when the satellite data were considered. The addition of satellite data was concluded to have enhanced the accuracy of the forecast.

Vergin, J. M.↗

The Manufacturing Data and Machine Learning Platform: Enabling Real-time Monitoring and Control of Scientific Experiments via IoT

IoT devices and sensor networks present new opportunities for measuring, monitoring, and guiding scientific experiments. Sensors, cameras, and instruments can be combined to provide previously unachievable insights into the state of ongoing experiments. However, IoT devices can vary greatly in the type, volume, and velocity of data they generate, making it challenging to fully realize this potential. Indeed, synergizing diverse IoT data streams in near-real time can require the use of machine learning (ML). In addition, new tools and technologies are required to facilitate the collection, aggregation, and manipulation of sensor data in order to simplify the application of ML models and in turn, fully realize the utility of IoT devices in laboratories. Here we will demonstrate how the use of the Argonne-developed Manufacturing Data and Machine Learning (MDML) platform can analyze and use IoT devices in a manufacturing experiment. MDML is designed to standardize the research and operational environment for advanced data analytics and AI-enabled automated process optimization by providing the infrastructure to integrate AI in cyber-physical systems for in situ analysis. We will show that MDML is capable of processing diverse IoT data streams, using multiple computing resources, and integrating ML models to guide an experiment.

Machine Learning↗

Addressing GPU memory limitations for Graph Neural Networks in High-Energy Physics applications

Introduction Reconstructing low-level particle tracks in neutrino physics can address some of the most fundamental questions about the universe. However, processing petabytes of raw data using deep learning techniques poses a challenging problem in the field of High Energy Physics (HEP). In the Exa.TrkX Project, an illustrative HEP application, preprocessed simulation data is fed into a state-of-art Graph Neural Network (GNN) model, accelerated by GPUs. However, limited GPU memory often leads to Out-of-Memory (OOM) exceptions during training, due to the large size of models and datasets. This problem is exacerbated when deploying models on High-Performance Computing (HPC) systems designed for large-scale applications. Methods We observe a high workload imbalance issue during GNN model training caused by the irregular sizes of input graph samples in HEP datasets, contributing to OOM exceptions. We aim to scale GNNs on HPC systems, by prioritizing workload balance in graph inputs while maintaining model accuracy. Our paper introduces diverse balancing strategies aimed at decreasing the maximum GPU memory footprint and avoiding the OOM exception, across various datasets. Results Our experiments showcase memory reduction of up to 32.14% compared to the baseline. We also demonstrate the proposed strategies can avoid OOM in application. Additionally, we create a distributed multi-GPU implementation using these samplers to demonstrate the scalability of these techniques on the HEP dataset. Discussion By assessing the performance of these strategies as data loading samplers across multiple datasets, we can gauge their effectiveness in both single-GPU and distributed environments. Our experiments, conducted on datasets of varying sizes and across multiple GPUs, broaden the applicability of our work to various GNN applications that handle input datasets with irregular graph sizes.

Lee, Claire Songhyun↗

The Effect of the Saharan Air Layer on the Formation of Hurricane Isabel (2003) Simulated with AIRS Data

The crucial physics of how the atmosphere really accomplishes the tropical cyclogenesis process is still poorly understood. The presence of the Saharan Air Layer (SAL), an elevated mixed layer of warm and dry air that extends from Africa to the tropical Atlantic and contains a substantial amount of mineral dust, adds more complexity to the tropical cyclogenesis process in the Atlantic basin. The impact of the SAL on tropical cyclogenesis is still uncertain. Karyampudi and Carlson (1988) conclude that a strong SAL can potentially aid tropical cyclone development while Dunion and Velden (2004) argue that the SAL generally inhibits tropical cyclogenesis and intensification. Advancing our understanding of the physical mechanisms of tropical cyclogenesis and the associated roles of the SAL strongly depends on the improvement in the observations over the data-sparse ocean areas. After the Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU), and the microwave Humidity Sounder of Brazil (HSB) were launched with the NASA Aqua satellite in 2002, new data products retrieved from the AIRS suite became available for studying the effect of the warm, dry air mass associated with the SAL (referred to as the thermodynamic effect). The vertical profiles of the AIRS retrieved temperature and humidity provide an unprecedented opportunity to examine the thermodynamic effect of the SAL. The observational data can be analyzed and assimilated into numerical models, in which the model thermodynamic state is allowed to relax to the observed state from AIRS data. The objective of this study is to numerically demonstrate that the thermodynamic effect of the SAL on the formation of Hurricane Isabel (2003) can be largely simulated through nudging of the AIRS data.

Wu, iguang↗

Industry 4.0 and Intelligent Manufacturing Processes: A Review of Modern Sensing Technologies

Digital Manufacturing technologies have quickly become ubiquitous in the manufacturing industry. The transformation commonly referred to as the fourth industrial revolution, or Industry 4.0, has ushered in a wide range of communication technologies, connection mechanisms, and data analysis capabilities. These technologies provide powerful tools to create a more lean, profitable, and data-driven manufacturing processes. In this paper, we review modern communication technologies and connection architectures for Digital Manufacturing and Industry 4.0 applications. An introduction to Cyber-Physical Systems and a review of digital manufacturing trends is followed by an overview of data acquisition methods for manufacturing processes. Numerous communication protocols are presented and discussed for connecting disparate machines and processes. Flexible data architectures are discussed and examples of machine monitoring implementations are provided. Finally, select implementations of these communication protocols and architectures are surveyed with recommendations for future architecture implementations.

42 ENGINEERING↗