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At least 199 records · Page 11

Overview of the CDAW Events

In this paper, I present an overview of the solar and interplanetary characteristics of the events selected to be analyzed during the workshop. The events were selected based on the following criteria: 1. The events must be well observed in the interplanetary medium as shock-driving interplanetary coronal mass ejections (ICMEs), 2. The ICMEs should have corresponding CMEs near the Sun, observed in white-light coronal images, and 3. The heliographic coordinates of the solar sources must be within 15 degrees from the Sun Center. This presentation will set the stage for the rest of the discussion during the workshop

Gopalswamy, Nat↗

Constraints on CME Evolution from in situ Observations of Ionic Charge States

We present a novel procedure for deriving the physical properties of Coronal Mass Ejections (CMES) in the corona. Our methodology uses in-situ measurements of ionic charge states of C, O, Si and Fe in the heliosphere and interprets them in the context of a model for the early evolution of ICME plasma, between 2 - 5 R-solar. We find that the data can be fit only by an evolution that consists of an initial heating of the plasma, followed by an expansion that ultimately results in cooling. The heating profile is consistent with a compression of coronal plasma due to flare reconnect ion jets and an expansion cooling due to the ejection, as expected from the standard CME/flare model. The observed frozen-in ionic charge states reflect this time-history and, therefore, provide important constraints for the heating and expansion time-scales, as well as the maximum temperature the CME plasma is heated to during its eruption. Furthermore, our analysis places severe limits on the possible density of CME plasma in the corona. We discuss the implications of our results for CME models and for future analysis of ICME plasma composition.

Gruesbeck, Jacob R.↗

A Summary of the Flux-Rope CDAW events

In this paper, I summarize some of the results obtained during previous CDAW on the events selected for analysis. The events were selected based on the following criteria: 1. The events must be well observed in the interplanetary medium as shock-driving interplanetary coronal mass ejections (ICMEs), 2. The ICMEs should have corresponding CMEs near the Sun, observed in white-light coronal images, and 3. The heliographic coordinates of the solar sources must be within 15 degrees from the Sun Center. In all, 24 magnetic cloud (MC) events and 35 non-MC evens were analyzed. Of the 35 non-MC events selected for analysis, it was possible to fit flux ropes to 31/35 events if different boundaries and multiple flux ropes are used. The four events without flux rope structure seem to be poor events (short duration, poor magnetic and plasma signatures). Coronal flux rope fitting suggests (at least for a subset) that non-MC events become non-central during propagation. It was also found that MCs have high charge states; half of the non-MC events also have high charge states. The direction parameter of CMEs seems to be high for MCs. All these results are consistent with the idea that alll CMEs may be flux ropes.

Gopalswamy, Natchimuthuk↗

The Outer Limits of Galaxy Clusters: Observations to the Virial Radius with Suzaku, XMM,and Chandra

The outskirts of galaxy clusters, near the virial radius, remain relatively unexplored territory and yet are vital to our understanding of cluster growth, structure, and mass. In this presentation, we show the first results from a program to constrain the sate of the outer intra-cluster medium (ICM) in a large sample of galaxy clusters, exploiting the strengths of three complementary X-ray observatories: Suzaku (low, stable background), XMM-Newton (high sensitivity),and Chandra (good spatial resolution). By carefully combining observations from the cluster core to beyond r200, we are able to identify and reduce systematic uncertainties that would impede our spatial and spectral analysis using a single telescope. Our sample comprises nine clusters at z is approximately 0.1-0.2 fully covered in azimuth to beyond r200, and our analysis indicates that the ICM is not in hydrostatic equilibrium in the cluster outskirts, where we see clear azimuthal variations in temperature and surface brightness. In one of the clusters, we are able to measure the diffuse X-ray emission well beyond r200, and we find that the entropy profile and the gas fraction are consistent with expectations from theory and numerical simulations. These results stand in contrast to recent studies which point to gas clumping in the outskirts; the extent to which differences of cluster environment or instrumental effects factor in this difference remains unclear. From a broader perspective, this project will produce a sizeable fiducial data set for detailed comparison with high-resolution numerical simulations.

Miller, Eric D.↗

Sunyaev-Zeldovich Effect Studies of Galaxy Clusters with Bolocam (and Future Instrumentation)

Galaxy clusters are excellent laboratories for studying the astrophysics of gravitational collapse and the non-self-similar processes that can affect it. A number of different techniques allow us to study the distribution of the consituents of galaxy clusters. The thermal Sunyaev-Zeldovich effect measures the line-of-sight integral of the the pressure in the ICM plasma. Comparison to and combination with other probes enables a variety of studies of the ICM and of clusters: scaling relations, radial profiles, tests of hydrostatic equilibrium, etc. We report on the status of our program to image clusters in the thermal Sunyaev-Zeldovich effect at 150GHz using Bolocam and perform such tests. We also describe the upcoming MKIDCam long-wavelength multi-color facility camera for the CSO, which will provide new capabilities in thermal Sunyaev-Zeldovich effect imaging. We comment on the role Tom Phillips and the CSO have played in facilitating the development of mm-wave SZ observations.

Golwala, Sunil↗

Plasma Observations During the Mars Atmospheric Plume Event of March-April 2012

We present initial analysis and conclusions from plasma observations made during the reported Mars Dust plume event of March - April 2012. During this period, multiple independent amateur observers detected a localized, high-altitude plume over the Martian dawn terminator [Sanchez-Lavega7 et al., Nature, 2015, doi:10.1038nature14162], the origin of which remains to be explained. We report on in-situ measurements of ionospheric plasma density and solar wind parameters throughout this interval made by Mars Express, obtained over the surface region, but at the opposing terminator. We tentatively conclude that the formation and/or transport of this plume to the altitudes where it was observed could be due in part the result of a large interplanetary coronal mass ejection (ICME) encountering the Martian system. Interestingly, we note that a similar plume detection in May 1997 may also have been associated with a large ICME impact at Mars.

Plumes↗

Intelligent Contingency Management for Urban Air Mobility

The third aviation revolution is seeking to enable transportation where users have access to immediate and flexible air travel; the users dictate trip origin, destination and timing. One of the major components of this vision is urban air mobility (UAM) for the masses. UAM means a safe and efficient system for vehicles to move passengers and cargo within a city. In order to reach UAM’s full market potential the vehicle will have to be autonomous. One of the primary challenges of autonomous flight is dealing with off-nominal events, both common and unforeseen; thus, intelligent contingency management (ICM) is one of the enabling technologies. In this context, the vehicle has to be aware of its internal state and external environment at all times, ascertain its capability and make decisions about mission completion or modification. All of these functions require data to model and assess the environment and then take actions based on these models. Necessarily, there is uncertainty associated with the data and the models generated from it. Since we are dealing with safety-critical systems, one of the main challenges of ICM is to generate sufficient data and to minimize its uncertainty to enable practical and safe decision making. We propose an overall architecture that incorporates deterministic and learning algorithms together to assess vehicle capabilities, project these into the future and make decisions on mission management level. A layered approach allows for mature parts and technologies to be integrated into early highly automated vehicles before the final state of autonomy is reached.

data-driven systems↗

Intelligent Contingency Management for Urban Air Mobility

The third aviation revolution is seeking to enable transportation where users have access to immediate and flexible air travel; the users dictate trip origin, destination and timing. One of the major components of this vision is urban air mobility (UAM) for the masses. UAM means a safe and efficient system for vehicles to move passengers and cargo within a city. In order to reach UAM’s full market potential the vehicle will have to be autonomous. One of the primary challenges of autonomous flight is dealing with off-nominal events, both common and unforeseen; thus, intelligent contingency management (ICM) is one of the enabling technologies. This paper proposes an ICM architecture with associated tools that would help enable the UAM vision.

UAM↗

Intelligent Contingency Management for Urban Air Mobility

The third aviation revolution is seeking to enable transportation where users have access to immediate and flexible air travel; the users dictate trip origin, destination and timing. One of the major components of this vision is urban air mobility (UAM) for the masses. UAM means a safe and efficient system for vehicles to move passengers and cargo within a city. In order to reach UAM’s full market potential the vehicle will have to be autonomous. One of the primary challenges of autonomous flight is dealing with off-nominal events, both common and unforeseen; thus, intelligent contingency management (ICM) is one of the enabling technologies. This paper proposes an ICM architecture with associated tools that would help enable the UAM vision.

UAM;↗

Benchmark Problem Development for Testing Maturity of Intelligent Contingency Management Tools

Increasingly autonomous Advanced Air Mobility (AAM) vehicles will be required to handle diverse conditions with limited human intervention. Intelligent contingency management (iCM) approaches are under development to address how automated agents can handle unforeseen, unplanned, and unanticipated events. Benchmark scenario is needed to test the maturity of the developed iCM tools and techniques.

Jon Holbrook↗

Data Augmentation for Intelligent Contingency Management Using Generative Adversarial Neural Networks

Artificial intelligence (AI)-based techniques for intelligent contingency management (ICM) require that intelligent agents learn various aspects of system dynamics to create and execute contingencies. For high assurance contingency management, agents achieve the most compelling results through supervised or semi-supervised machine learning, for which agents require large datasets to learn the dynamics of the system. Unfortunately, data collection in aerospace applications can be costly, due to both time and resources. Presented work describes a framework for data augmentation of ICM databases containing training data for machine learning models. This framework populates the database with the outputs of generative adversarial network (GAN) models that were trained on flight data. Methods for evaluating the suitability of these models based on the equations of motion, as well as other physical constraints, are discussed. The paper demonstrates the utility of this database for training intelligent agents on the NASA T2 generic transport aircraft model and experimental vertical takeoff and landing (VTOL) simulation model.

Generative Machine Learning↗

Data Augmentation for Intelligent Contingency Management Using Generative Adversarial Neural Networks

Artificial intelligence (AI)-based techniques for intelligent contingency management (ICM) require that intelligent agents learn various aspects of system dynamics to create and execute contingencies. For high assurance contingency management, agents achieve the most compelling results through supervised or semi-supervised machine learning, for which agents require large datasets to learn the dynamics of the system. Unfortunately, data collection in aerospace applications can be costly, due to both time and resources. Presented work describes a framework for data augmentation of ICM databases containing training data for machine learning models. This framework populates the database with the outputs of generative adversarial network (GAN) models that were trained on flight data. Methods for evaluating the suitability of these models based on the equations of motion, as well as other physical constraints, are discussed. The paper demonstrates the utility of this database for training intelligent agents on the NASA T2 generic transport aircraft model and experimental vertical takeoff and landing (VTOL) simulation model.

Generative Machine Learning↗

Discrete Aurora on the Nightside of Mars: Occurrence Location and Probability

This paper represents the first attempt to predict the occurrence location and probability of discrete electron aurora on the nightside of Mars. We run a 3-D time-dependent magnetohydrodynamic model to characterize the spatial and temporal dynamics of magnetic field and plasma distributions over the course of one planetary rotation. We perform eight simulation cases under solar minimum quiet-solar-wind conditions (four equinox/solstice seasons, each with two interplanetary magnetic field polarities) and in an actual interplanetary coronal mass ejection (ICME) case to assess quiet and space weather situations, respectively. The occurrence of detectable discrete aurora is subject to the combination of the probabilities that (a) the ionosphere is magnetically connected with high altitudes through open field lines and (b) precipitating energy fluxes of >30 eV electrons exceed 0.1 erg/cm2/s. Our results show that during quiet solar activity, discrete aurora occurs likely on small-scale patches embedded inside strong crustal magnetic field regions (with a magnitude greater than 50 nT at 150 km), and the overall chance across the globe is ∼0.77%. The higher probability over strong crustal field regions is attributed to the stronger magnetic field convergence. Modeling shows the occurrence probability dramatically increases during the ICME event, particularly by more than an order of magnitude in weak crustal field regions. Our model results reasonably agree with NASA Mars Atmosphere and Volatile EvolutioN and Mars Express observations. Our study suggests that nightside discrete electron aurora is not caused by the direct entry of magnetosheath plasma in a cusp-like process but due to the recycling of nightside magnetospheric electrons.

Xiaohua Fang↗

Identification of Flux Rope Orientation via Neural Networks

Geomagnetic disturbance forecasting is based on the identification of solar wind structures and accurate determination of their magnetic field orientation. For nowcasting activities, this is currently a tedious and manual process. Focusing on the main driver of geomagnetic disturbances, the twisted internal magnetic field of interplanetary coronal mass ejections (ICMEs), we explore a convolutional neural network’s (CNN) ability to predict the embedded magnetic flux rope’s orientation once it has been identified from in situ solar wind observations. Our work uses CNNs trained with magnetic field vectors from analytical flux rope data. The simulated flux ropes span many possible spacecraft trajectories and flux rope orientations. We train CNNs first with full duration flux ropes and then again with partial duration flux ropes. The former provides us with a baseline of how well CNNs can predict flux rope orientation while the latter provides insights into real-time forecasting by exploring how accuracy is affected by percentage of flux rope observed. The process of casting the physics problem as a machine learning problem is discussed as well as the impacts of different factors on prediction accuracy such as flux rope fluctuations and different neural network topologies. Finally, results from evaluating the trained network against observed ICMEs from Wind during 1995–2015 are presented.

Thomas Narock↗

Advancement of Extreme Environment Additively Manufactured Alloys for Next Generation Space Propulsion Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000’s. Several efforts focused on the understanding of AM processes through material characterization and testing, standards development, component fabrication, and infusion into propulsion development and flight applications. NASA matured commonly used aerospace alloys from various alloy families (Nickel, Copper, Stainless and Steel, Aluminum, and Titanium-based) through detailed AM process and heat treatment characterization, in addition to mechanical and thermophysical testing. While these alloys are actively used in many propulsion applications, there is a need for ongoing AM optimized alloys using integrated computational materials engineering (ICME) and process development for high performance applications. The applications targeted are liquid rocket engines; advanced propulsion systems; and in-space propulsion with high heat fluxes, high pressure, and/or that use propellants that can degrade alloys (e.g., hydrogen). This paper highlights the characterization and physical properties of the more common AM alloys using laser powder bed fusion (L-PBF) and laser powder directed energy deposition (LP-DED) processes. Additionally, this paper discusses some of the ongoing novel alloy development and maturation using AM for use in these harsh environments, such as GRCop42, GRCop-84, NASA HR-1, GRX-810, and C-103. The results from these processes demonstrated that AM could enable rapid development and ongoing efforts for optimized alloys using ICME, yielding higher performances. These alloys have undergone modeling, fundamental metallurgical evaluations, heat treatment studies, detailed microstructure characterization, and mechanical testing campaigns. This, combined with direct application-specific component fabrication and hot-fire testing, enabled the increase of the Technology Readiness Level (TRL) through high duty-cycle testing. A background and overview of these novel AM-enabled alloys and AM processing developments including metallurgical and mechanical property studies is presented here. The latest advancement in the parallel component development and hot-fire testing and future developments for these alloys is also discussed.

Additive Manufacturing↗

Advancement of Extreme Environment Additively Manufactured Alloys for Next Generation Space Propulsion Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000’s. Several efforts focused on the understanding of AM processes through material characterization and testing, standards development, component fabrication, and infusion into propulsion development and flight applications. NASA matured commonly used aerospace alloys from various alloy families (Nickel, Copper, Stainless and Steel, Aluminum, and Titanium-based) through detailed AM process and heat treatment characterization, in addition to mechanical and thermophysical testing. While these alloys are actively used in many propulsion applications, there is a need for ongoing AM optimized alloys using integrated computational materials engineering (ICME) and process development for high performance applications. The applications targeted are liquid rocket engines; advanced propulsion systems; and in-space propulsion with high heat fluxes, high pressure, and/or that use propellants that can degrade alloys (e.g., hydrogen). This paper highlights the characterization and physical properties of the more common AM alloys using laser powder bed fusion (L-PBF) and laser powder directed energy deposition (LP-DED) processes. Additionally, this paper discusses some of the ongoing novel alloy development and maturation using AM for use in these harsh environments, such as GRCop-42, GRCop-84, NASA HR-1, GRX-810, and C-103. The results from these processes demonstrated that AM could enable rapid development and ongoing efforts for optimized alloys using ICME, yielding higher performances. These alloys have undergone modeling, fundamental metallurgical evaluations, heat treatment studies, detailed microstructure characterization, and mechanical testing campaigns. This, combined with direct application-specific component fabrication and hot-fire testing, enabled the increase of the Technology Readiness Level (TRL) through high duty-cycle testing. A background and overview of these novel AM-enabled alloys and AM processing developments including metallurgical and mechanical property studies is presented here. The latest advancement in the parallel component development and hot-fire testing and future developments for these alloys is also discussed.

Additive Manufacturing↗

Writhed Analytical Magnetic Flux Rope Model

Observations of magnetic clouds, within interplanetary coronal mass ejections (ICMEs), are often well described by flux rope models. Most of these assume either a cylindrical or toroidal geometry. In some cases, these models are also capable of accounting for non-axisymmetric cross-sections but they generally all assume axial invariance. It can be expected that any ICME, and its flux rope, will be deformed along its axis due to influences such as the solar wind. In this work, we aim to develop a writhed analytical magnetic flux rope model which would allow us to analytically describe a flux rope structure with varying curvature and torsion so that we are no longer constrained to a cylindrical or toroidal geometry. In this first iteration of our model we will solely focus on a circular cross-section of constant size. We describe our flux rope geometry in terms of a parametrized flux rope axis and a parallel transport frame. We derive expressions for the axial and poloidal magnetic field components under the assumption that the total axial magnetic flux is conserved. We find an entire class of possible solutions, which differ by the choice of integration constants, and present the results for a specific example. In general, we find that the twist of the magnetic field locally changes when the geometry deviates from a cylinder or torus. This new approach also allows us to generate completely new types of in situ magnetic field profiles which strongly deviate from those generated by cylindrical or toroidal models.

A. J. Weiss↗

Assessing Effects of Climate Change on Legacy Waste at the Enewetak Atoll

The Republic of the Marshall Islands (RMI) is in the central Pacific Ocean ~4,500 km west of Hawaii. The Enewetak Atoll, located in the northwest part of the RMI, was the site for 43 nuclear weapon tests between 1948 and 1958. Fallout and deposition from the tests contaminated the island surfaces, lagoon waters and sediment, and nearby ocean waters at the atoll. In the 1970s, a cleanup effort collected radioactive waste and placed it in the Cactus Crater on Runit Island (also called the Runit Dome). In December 2021, Congress directed the U.S. Department of Energy to study the impacts of climate change on the Runit Dome nuclear waste disposal site. Pacific Northwest National Laboratory (PNNL) assembled a multidisciplinary team of climate scientists, ocean modelers, environmental scientists, and health physicists to assess the likely effects of remaining radionuclides at the Enewetak Atoll. PNNL’s approach focused on effects of tropical cyclones that were postulated to mobilize and transport contaminated lagoon sediments and result in human and biota exposure. PNNL’s study estimated (1) the radionuclide source term, (2) the effects of climate change on severe storms, (3) mobilization and transport of radionuclides, and (4) radiation dose to humans and biota. Radionuclides in the lagoon and/or ocean waters of the Enewetak Atoll were characterized by the U.S. Atomic Energy Commission (AEC) in 1972, Woods Hole Oceanographic Institution in 2015, and Lawrence Livermore National Laboratory in 2018. The RMI Nationwide Radiological Study was conducted in the early 1990s for radionuclides remaining in island soils. The 1972 AEC survey remains the most comprehensive source of radionuclide data on lagoon sediments. Climate change modeling at a regional scale in the central Pacific Ocean is limited. PNNL climate scientists simulated severe historical storms postulated to occur both in a recent climate (2015) and in the future (2090) using the Advanced Research Weather Research and Forecasting (WRF-ARW) model, employing a pseudo-global-warming technique. A postulated complete, future failure of the Runit Dome was also considered. PNNL developed a high-resolution regional ocean hydrodynamics model covering the entire RMI extended economic zone using the Finite Volume Coastal Ocean Model (FVCOM). The FVCOM model was run using global reanalysis data for current climate and WRF-ARW simulation for the future climate. PNNL also developed a radionuclide fate and transport model using the FVCOM Integrated Compartment Model (FVCOM-ICM) to simulate the current and future mobilization and transport of radionuclides sorbed to lagoon sediments and the exchange of radionuclides between the water and sediment. FVCOM-ICM-predicted radionuclide concentrations were then used to estimate radiation dose to humans and biota at all islands of the Enewetak Atoll. Under current climate conditions, annual radiation exposures for the southern islands including Enewetak (Fred) and Medren (Elmer) were below the current U.S. standards. Radiation doses were somewhat elevated starting at Runit Island northward and westward to Enjebi Island (Janet). The islands in the northwest quadrant, particularly Bokoluo (Alice) and Bokombako (Belle), remain relatively contaminated. The islands in the southwestern quadrant have low contamination. The highest contribution to radiation doses comes from consumption of locally grown foods. Two radionuclides, 90Sr and 137Cs, contributed the greatest fraction for most terrestrial foods. In current climate conditions, the storms temporarily increased radionuclide concentrations in the lagoon waters, increasing the radiation dose slightly. In future conditions, doses are expected to be smaller, primarily because of the radioactive decay of the shorter-lived radioisotopes of 90Sr and 137Cs. This could make all islands in the far northwest of the atoll – except Bokombako (Belle) and perhaps Bokoluo (Alice) – suitable for residency. For the f

Prasad, Rajiv↗