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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 487 records · Page 27

"We Burn to Learn" About Fuel-Air Mixing Within Aircraft Powerplants

I am working with my branch s advanced diagnostics team to investigate fuel-air mixing in jet-fueled gas turbine combustors and jet-fuel reformers. Our data acquisition begins with bench-top experiments which will help with calibration of equipment for facility testing. While conducting the bench-top experiments I learned to align laser and optical equipment to collect data, to use the data acquisition software, and to process the data into graphs and images. which jet he1 is to be reformed into hydrogen. Testing will commence shortly, after which we will obtain and analyze data and meet a critical milestone for the end of September. I am also designing the layout for a Schlieren system that will be used during that time frame. A Schlieren instrument records changes in the refractive index distribution of transparent media like air flows. The refractive index distribution can then be related to density, temperature, or pressure distributions within the flow. I am working on a scheme to quantify this information and add to the knowledge of the fuel-air mixing process.

Robinson, Heidi N.↗

Comparative Analysis of Thermal Runaway Heat Output as a Function of Trigger Mechanism and Cell Format

High demand for energy storage systems across many fields drives the need for safe and reliable Li-ion batteries. In order to assess the risk of using such batteries in various applications, many types of abuse tests have been developed to push battery cells to their limits and learn how they fail. In this work, internal short circuit (ISC) tests, nail penetration tests, and thermal tests were used to trigger thermal runaway in D-cell, 18650, and 21700 Li-ion cells. High-speed radiography was used to gain insight to the propagation of thermal runaway throughout the cell, while calorimetric and thermal data were recorded in real time. Post-test disassembly of the calorimeter allowed for any mass ejected from the cell to be analyzed and the distribution of mass through the calorimeter to be determined. The impact of cell geometry and trigger mechanism on post-test mass distribution, thermal runaway propagation and internal cell temperature are discussed.

Lithium-ion battery; thermal runaway; calorimetry;↗

Particle Acceleration at the Sun and in the Heliosphere

Energetic particles are accelerated in rich profusion at sites throughout the heliosphere. They come from solar flares in the low corona, from shock waves driven outward by coronal mass ejections (CMEs), from planetary magnetospheres and bow shocks. They come from corotating interaction regions (CIRs) produced by high-speed streams in the solar wind, and from the heliospheric termination shock at the outer edge of the heliospheric cavity. We sample all these populations near Earth, but can distinguish them readily by their element and isotope abundances, ionization states, energy spectra, angular distributions and time behavior. Remote spacecraft have probed the spatial distributions of the particles and examined new sources in situ. Most acceleration sources can be "seen" only by direct observation of the particles; few photons are produced at these sites. Wave-particle interactions are an essential feature in acceleration sources and, for shock acceleration, new evidence of energetic-proton-generated waves has come from abundance variations and from local cross-field scattering. Element abundances often tell us the physics the source plasma itself, prior to acceleration. By comparing different populations, we learn more about the sources, and about the physics of acceleration and transport, than we can possibly learn from one source alone.

Reames, Donald V.↗

Global Precipitation Measurement: Summary of the First GPM Partners Planning Workshop - Report 1

This report provides a synopsis of the proceedings of the First Global Precipitation Measurement (GPM) Partners Planning Workshop held at the University of Maryland, College Park, from May 16 to 18, 2001. GPM consists of a multi-member global satellite constellation (i.e., an international set of satellite missions) and the accompanying scientific research program, with the main goal of providing frequent, accurate, and globally distributed precipitation measurements essential in understanding several fundamental issues associated with the global water and energy cycle (GWEC). The exchange of scientific and technical information at this and subsequent GPM workshops between representatives from around the world represents a key step in the formulation phase of GPM mission development. The U.S. National Aeronautics and Space Agency (NASA), the National Space Development Agency of Japan (NASDA), and other interested agencies from nations around the world seek to observe, understand, and model the Earth system to learn how it is changing and what consequences these changes have on life, particularly as they pertain to hydrological processes and the availability of fresh water resources. GWEN processes are central to a broader understanding of the Earth system.

Shepherd, J. Marshall↗

International Space Station Major Constituent Analyzer On-Orbit Performance

The Major Constituent Analyzer (MCA) is an integral part of the International Space Station (ISS) Environmental Control and Life Support System (ECLSS). The MCA is a mass spectrometer-based instrument designed to provide critical monitoring of six major atmospheric constituents; nitrogen, oxygen, hydrogen, carbon dioxide, methane, and water vapor. These gases are sampled continuously and automatically in all United States On-Orbit Segment (USOS) modules via the Sample Distribution System (SDS). The MCA is the primary tool for management of atmosphere constituents and is therefore critical for ensuring a habitable ISS environment during both nominal ISS operations and campout EVA preparation in the Airlock. The MCA has been in operation in the US Destiny Laboratory Module for over 10 years, and a second MCA has been delivered to the ISS for Node 3 operation. This paper discusses the performance of the MCA over the two past year, with particular attention to lessons learned regarding the operational life of critical components. Recent data have helped drive design upgrades for a new set of orbit-replaceable units (ORUs) currently in production. Several ORU upgrades are expected to increase expected lifetimes and reliability.

Gardner, Ben D.↗

Lunar and Meteorite Sample Disk for Educators

NASA Johnson Space Center (JSC) has the unique responsibility to curate NASA's extraterrestrial samples from past and future missions. Curation includes documentation, preservation, preparation and distribution of samples for research, education and public outreach. Between 1969 and 1972 six Apollo missions brought back 382 kilograms of lunar rocks, core and regolith samples, from the lunar surface. JSC also curates meteorites collected from a US cooperative effort among NASA, the National Science Foundation (NSF) and the Smithsonian Institution that funds expeditions to Antarctica. The meteorites that are collected include rocks from Moon, Mars, and many asteroids including Vesta. The sample disks for educational use include these different samples. Active relevant learning has always been important to teachers and the Lunar and Meteorite Sample Disk Program provides this active style of learning for students and the general public. The Lunar and Meteorite Sample Disks permit students to conduct investigations comparable to actual scientists. The Lunar Sample Disk contains 6 samples; Basalt, Breccia, Highland Regolith, Anorthosite, Mare Regolith and Orange Soil. The Meteorite Sample Disk contains 6 samples; Chondrite L3, Chondrite H5, Carbonaceous Chondrite, Basaltic Achondrite, Iron and Stony-Iron. Teachers are given different activities that adhere to their standards with the disks. During a Sample Disk Certification Workshop, teachers participate in the activities as students gain insight into the history, formation and geologic processes of the moon, asteroids and meteorites.

Foxworth, Suzanne↗

NASA Tech Briefs, January 2012

Contents of this issue are: (1) Energy-Based Tetrahedron Sensor for High-Temperature, High-Pressure Environments (2) Handheld Universal Diagnostic Sensor (3) Large-Area Vacuum Ultraviolet Sensors (4) Fiber Bragg Grating Sensor System for Monitoring Smart Composite Aerospace Structures (5) Health-Enabled Smart Sensor Fusion Technology (6) Extended-Range Passive RFID and Sensor Tags (7) Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks (8) Self-Healing, Inflatable, Rigidizable Shelter (9) Improvements in Cold-Plate Fabrication (10) Technique for Radiometer and Antenna Array Calibration - TRAAC (11) Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment (12) Programmable Digital Controller (13) Use of CCSDS Packets Over SpaceWire to Control Hardware (14) Key Decision Record Creation and Approval Module (15) Enhanced Graphics for Extended Scale Range (16) Debris Examination Using Ballistic and Radar Integrated Software (17) Data Distribution System (DDS) and Solar Dynamic Observatory Ground Station (SDOGS) (18) Integration Manager (19) Eclipse-Free-Time Assessment Tool for IRIS (20) Automated and Manual Rocket Crater Measurement Software (21) MATLAB Stability and Control Toolbox Trim and Static Stability Module (22) Patched Conic Trajectory Code (23) Ring Image Analyzer (24) SureTrak Probability of Impact Display (25) Implementation of a Non-Metallic Barrier in an Electric Motor (26) Multi-Mission Radioisotope Thermoelectric Generator Heat Exchangers for the Mars Science Laboratory Rover (27) Uniform Dust Distributor for Testing Radiative Emittance of Dust-Coated Surfaces (28) MicroProbe Small Unmanned Aerial System (29) Highly Stable and Active Catalyst for Sabatier Reactions (30) Better Proton-Conducting Polymers for Fuel-Cell Membranes (31) CCD Camera Lens Interface for Real-Time Theodolite Alignment (32) Peregrine 100-km Sounding Rocket Project (33) SOFIA Closed- and Open-Door Aerodynamic Analyses (34) Sonic Thermometer for High-Altitude Balloons (35) Near-Infrared Photon-Counting Camera for High-Sensitivity Observations (36) Integrated Optics Achromatic Nuller for Stellar Interferometry (37) High-Speed Digital Interferometry (38) Ultra-Miniature Lidar Scanner for Launch Range Data Collection (39) Shape and Color Features for Object Recognition Search (40) Explanation Capabilities for Behavior-Based Robot Control (41) A DNA-Inspired Encryption Methodology for Secure, Mobile Ad Hoc Networks (42) Quality Control Method for a Micro-Nano-Channel Microfabricated Device (43) Corner-Cube Retroreflector Instrument for Advanced Lunar Laser Ranging (44) Electrospray Collection of Lunar Dust (45) Fabrication of a Kilopixel Array of Superconducting Microcalorimeters with Microstripline Wiring Spacecraft Attitude Tracking and Maneuver Using Combined Magnetic Actuators (46) Coherent Detector for Near-Angle Scattering and Polarization Characterization of Telescope Mirror Coatings

Source record↗

An Automated Approach to Labelling Datasets in Earth Science Publications

NASA Data Active Archive Centers, orDAACs, ingest, store, and distribute dataacquired from satellites, ground systems as well asreanalysis models. Many authors use this datain their research. However, most of the datasets usedin Earth Science Publications are not citedcorrectly or not cited at all. Thus, there is no directlink between the datasets used and thescientific publications which reference them. Thisleads to issues with reproducibility of theresults, attribution of the research results, anddiscovery of new datasets. This project began byexploring various methods of automatically labellingGoddard Earth Sciences Data andInformation Services Center (GES DISC) datasets usingSupervised Machine Learning and EarthData Search Common Metadata Repository (CMR) queries.The ultimate goal was to create alibrary of citations that utilized automated citationlabeling to directly link the researchpublications to the data they use. Supervised MachineLearning approaches struggled due to thelimited amount of labelled training data to learnfrom. Increasing the volume of training data isdifficult as it requires subject matter experts todevote time to manually reviewing journalarticles and determining the datasets used. The CMRqueries were inconsistent because theunderlying metadata is continuously being updated.Thus, it is hard to generalize theeffectiveness of the CMR results as they are dependenton the internal state of CMR. Theseapproaches helped inform the decision to transitionthe project into using a Knowledge Graph.Another key aspect of this project focused on theautomated extraction of features (platform,instrument, variables, etc) and explicit citationsfrom within Earth Science Publications. Theseautomated extractions were used to classify researchpapers based on their platform/instrumentcouples. This information was input into the CitationManagement System for GES DISC. Theseplatform/instrument couples also provide an additionalfacet that can be searched on the GESDISC website.

Edward Jahoda↗

Uniform Dust Deposition System for Dust Tolerance Studies

Future missions to the Moon will require mechanisms and materials to effectively and reliably operate in the presences of lunar regolith. One of the challenges of developing such technologies is terrestrial testing with lunar dust simulants. Dust has a stochastic nature of depositing and it can be difficult to accurately apply it to surfaces of interest. Deposition density, particles size distribution, and percent coverage are all factors that affect the quality of dust mitigation testing. Therefore, to enable such testing the dust mitigation and seals teams at NASA Glenn Research Center (GRC) have developed a system that can uniformly and repeatably deposit lunar simulants on a range of surfaces. Testing of the Dust Deposition System (DDS) and an associatedsimulant preparation methodology have quantified the levels of uniformity and precision for this system. Furthermore, the deposition system has been paired with automated micrograph capturing and machine learning image analysis to correlate the images of dust on a surface to deposition density (in g/cm2). This correlation alleviates the need for tested samples to be accurately weighed with milligram precision and may be a useful tool for in-situ contamination evaluation on the Moon. This paper covers the design and validation testing for the DDS.

Stephen Gerdts↗

Intelligent systems engineering methodology

An added challenge for the designers of large scale systems such as Space Station Freedom is the appropriate incorporation of intelligent system technology (artificial intelligence, expert systems, knowledge-based systems, etc.) into their requirements and design. This presentation will describe a view of systems engineering which successfully addresses several aspects of this complex problem: design of large scale systems, design with requirements that are so complex they only completely unfold during the development of a baseline system and even then continue to evolve throughout the system's life cycle, design that involves the incorporation of new technologies, and design and development that takes place with many players in a distributed manner yet can be easily integrated to meet a single view of the requirements. The first generation of this methodology was developed and evolved jointly by ISX and the Lockheed Aeronautical Systems Company over the past five years on the Defense Advanced Research Projects Agency/Air Force Pilot's Associate Program, one of the largest, most complex, and most successful intelligent systems constructed to date. As the methodology has evolved it has also been applied successfully to a number of other projects. Some of the lessons learned from this experience may be applicable to Freedom.

Fouse, Scott↗

Uniform Dust Deposition System for Dust Tolerance Studies

Future missions to the Moon will require mechanisms and materials to effectively and reliably operate in the presences of lunar regolith. One of the challenges of developing such technologies is terrestrial testing with lunar dust simulants. Dust has a stochastic nature of depositing and it can be difficult to accurately apply it to surfaces of interest. Deposition density, particles size distribution, and percent coverage are all factors that affect the quality of dust mitigation testing. Therefore, to enable such testing the dust mitigation and seals teams at NASA Glenn Research Center (GRC) have developed a system that can uniformly and repeatably deposit lunar simulants on a range of surfaces. Testing of the Dust Deposition System (DDS) and an associated simulant preparation methodology have quantified the levels of uniformity and precision for this system. Furthermore, the deposition system has been paired with automated micrograph capturing and machine learning image analysis to correlate the images of dust on a surface to deposition density (in g/cm2). This correlation alleviates the need for tested samples to be accurately weighed with milligram precision and may be a useful tool for in-situ contamination evaluation on the Moon. This paper covers the design and validation testing for the DDS.

Dust↗

Novel Observing Strategies (NOS) and Earth System Digital Twins (ESDT) for Disaster Resilience

"Earth systems have now been observed continuously for more than 50 years, not only from space but also from airplanes, balloons and in-situ sensors. With the addition of commercial remote sensing providers, many more Internet-of-Things sensors and new NASA and international observatories being planned, these incredible amounts of data will soon be augmented by even larger amounts of diverse data and therefore will become more and more difficult to access, integrate, understand and utilize. At the same time, because of climate change and its impacts, in order to predict, manage, and mitigate the effects of extreme science events and disasters, the information produced by all of this data needs to be optimized, organized and analyzed in such a way that it can be utilized by traditional as well as many new non-traditional users. This calls for the development of observing systems that are agile, coordinated and responsive to events of interest, and for information systems to be dynamic, interactive and fast. With these objectives in mind, the Advanced Information Systems Technology (AIST) Program has been developing technologies that will allow for the development of Novel Observing Strategies (NOS) in a distributed, coordinated fashion (i.e., similar to an “Internet-of-Earth-Things”), as well as for the development of novel information systems or Earth System Digital Twins (ESDT) that will build a digital replica of the past and current states of the Earth systems, will derive forecasts of future states under nominal assumptions and will also offer the capability to investigate many hypothetical evolution scenarios under varying impact assumptions. Both NOS and ESDT will be facilitated by the unprecedented advances of Artificial Intelligence technologies, especially Machine Learning (ML), for extracting relevant information from these large amounts of data, for fusing and assimilating diverse data together and for running complex models faster. Together NOS and ESDT will help build the capabilities needed to anticipate, predict and mitigate the effects of future disasters."

Earth Science Remote Sensing; Information Systems↗

North Atlantic Aerosol Single Scattering Albedos: TARFOX and ACE-2 Results and Their Relation to Radiative Effects Derived from Satellite Optical Depths

Bergstrom and Russell estimated direct solar radiative flux changes caused by atmospheric aerosols over the mid-latitude North Atlantic Ocean under cloud-free and cloudy conditions. They excluded African dust aerosols, primarily by restricting calculations to latitudes 25-60 N. As inputs they used midvisible aerosol optical depth (AOD) maps derived from AVHRR satellite measurements and aerosol intensive properties determined primarily in the 1996 IGAC Troposheric Aerosol Radiative Forcing Observational Experiment (TARFOX). Those aerosol intensive properties, which included optical depth wavelength dependence and spectra of single scattering albedo (SSA) and scattering asymmetry parameter, were also checked against initial properties from the 1997 North Atlantic Aerosol Characterization Experiment (ACE 2). Bergstrom and Russell investigated the sensitivity of their derived flux changes to assumed input parameters, including midvisible AOD, SSA, and scattering asymmetry parameter. Although the sensitivity of net flux change at the tropopause to SSA was moderate over the ocean (e.g., a SSA uncertainty of 0.07 produced a flux-change uncertainty of 21%), the sensitivity over common land surfaces can be much larger. Also, flux changes within and below the aerosol layer, which affect atmospheric stability, heating rates, and cloud formation and persistence, are quite sensitive to aerosol SSA. Therefore, this paper focuses on the question: "What have we learned from TARFOX and ACE 2 regarding aerosol single scattering albedo?" Three techniques were used in TARFOX to determine midvisible SSA. One of these derived SSA as a best-fit parameter in comparing radiative flux changes measured by airborne pyranometer to those computed from aerosol properties. Another technique combined airborne measurements of aerosol scattering and absorption by nephelometer and absorption photometer. A third technique obtained SSA from best-fit complex refractive indices derived by comparing vertical profiles of lidar backscatter, sunphotometer extinction, and relative size distribution. In ACE 2 midvisible SSA was determined both as a best-fit parameter in comparing measured and calculated flux changes at the surface and by combining nephelometer and absorption photometer measurements. The nephelometer/absorption-photometer results were obtained on the ACE 2 ship (10 m asl), at the Sagres, Portugal site at 50 m asl, and also on the Pelican aircraft. This paper presents and compares the TARFOX and ACE 2 SSA results from the above techniques for different situations (e.g., marine vs continental flows, "clean" vs polluted conditions). It also discusses the strengths and limitations of the techniques, including whether they describe the aerosol in its ambient state or as perturbed by sampling processes; whether they describe the aerosol at the surface, as a function of altitude, or integrated over a column; the ease of acquiring representative data sets; results obtained in tests of consistency with radiative flux changes, and the likelihood of various artifacts and errors.

Russell, P. B.↗

The Search for Young Planetary Systems And the Evolution of Young Stars

The Space Interferometer Mission (SIM) will provide a census of planetary systems by con- ducting a broad survey of 2,000 stars that will be sensitive to the presence of planets with masses as small as approx. 15 Earth masses (1 Uranus mass) and a deep survey of approx. 250 of the nearest, stars with a mass limit of approx.3 Earth masses. The broad survey will include stars spanning a wide range of ages, spectral types, metallicity, and other important parameters. Within this larger context, the Young Stars and Planets Key Project will study approx. 200 stars with ages from 1 Myr to 100 Myr to understand the formation and dynamical evolution of gas giant planets. The SIM Young Stars and Planets Project will investigate both the frequency of giant planet formation and the early dynamical history of planetary systems. We will gain insight into how common the basic architecture of our solar system is compared with recently discovered systems with close-in giant planets by examining 200 of the nearest (less than 150 pc) and youngest (1-100 Myr) solar-type stars for planets. The sensitivity of the survey for stars located 140 pc away is shown in the planet mass-separation plane. We expect to find anywhere from 10 (assuming that only the presently known fraction of stars. 5-7%, has planets) to 200 (all young stars have planets) planetary systems. W-e have set our sensitivity threshold to ensure the detection of Jupiter-mass planets in the critical orbital range of 1 to 5 AU. These observations, when combined with the results of planetary searches of mature stars, will allow us to test theories of planetary formation and early solar system evolution. By searching for planets around pre-main sequence stars carefully selected to span an age range from 1 to 100 Myr, we will learn a t what epoch and with what frequency giant planets are found at the water-ice snowline where they are expected to form. This will provide insight into the physical mechanisms by which planets form and migrate from their place of birth, and about their survival rate. With these data in hand, we will provide data, for the first time, on such important questions as: What processes affect the formation and dynamical evolution of planets? When and where do planets form? What is initial mass distribution of planetary systems around young stars? How might planets be destroyed? What is the origin of the eccentricity of planetary orbits? What is the origin of the apparent dearth of companion objects between planets and brown dwarfs seen in mature stars? The observational strategy is a compromise between the desire to extend the planetary mass function as low as possible and the essential need to build up sufficient statistics on planetary occurrence. About half of the sample will be used to address the "where" and "when" of planet formation. We will study classical T Tauri stars (cTTs) which have massive accretion disks and post- accretion, weak-lined T Tauri stars (wTTs). Preliminary estimates suggest the sample will consist of approx. 30% cTTs and approx. 70% wTTs, driven in part by the difficulty of making accurate astrometric measurements toward objects with strong variability or prominent disks.

Beichman, Charles A.↗

Towards a Marine Stratus Climatology on Drizzle Occurrence from CALIPSO

Marine stratus are a predominant feature of our planet with the annual mean coverage exceeding 20%. They strongly reflect sunlight, yet exert only a modest effect on outgoing infrared radiation, providing a significant net cooling to the Earth’s radiative balance. Their formation is coupled to boundary layer circulations that are driven, in part, by cloud top radiative cooling and evaporative cooling from precipitation in downdrafts. Understanding how these cloud systems evolve as the climate changes is a key question that requires additional information on their lifecycle and microphysical properties to accurately represent their behavior in global circulation models. From a large-scale perspective, insight into the microphysical properties of marine stratus at cloud top can be realized through estimates of the effective radius (Re) of the droplet size distributions derived from MODIS observations. Estimates on the occurrence of rain/drizzle are available from CloudSat. Together these observations indicate that precipitation frequently occurs in clouds with higher cloud top Re. This relationship is consistent with the well documented shift in cloud top droplet size distributions towards fewer, yet larger droplets prior the onset of precipitation. Here we report on a new and complementary set observations from the CALIPSO mission. The approach derives an extinction-to-backscatter ratio (Sc, also known as the cloud lidar ratio) using an established relationship that depends on observations of the lidar attenuated backscatter and volume depolarization ratio within the cloud. Because Sc is strongly and inversely related to Re, a change in the derived Sc from higher to lower values corresponds to a change in the droplet size distribution as seen by MODIS. This change in the lidar signals at cloud top clearly identifies clouds that are capable of precipitation. The presentation provides a brief overview of the approach for deriving Sc and compares CALIOP-derived Sc with observations from other techniques. CALIOP classifications of drizzling clouds, based on the retrieved values Sc, are compared to independent, collocated assessments of drizzle occurrence reported in the standard CloudSat data products. Regional and seasonal comparisons highlight the strengths and weaknesses of the two sensors. A machine learning approach that combines information from both CALIOP and CloudSat showcases possible improvements in the global identification of scenes likely to contain rain-bearing clouds.

CALIPSO↗

Designing Agent Utilities for Coordinated, Scalable and Robust Multi-Agent Systems

Coordinating the behavior of a large number of agents to achieve a system level goal poses unique design challenges. In particular, problems of scaling (number of agents in the thousands to tens of thousands), observability (agents have limited sensing capabilities), and robustness (the agents are unreliable) make it impossible to simply apply methods developed for small multi-agent systems composed of reliable agents. To address these problems, we present an approach based on deriving agent goals that are aligned with the overall system goal, and can be computed using information readily available to the agents. Then, each agent uses a simple reinforcement learning algorithm to pursue its own goals. Because of the way in which those goals are derived, there is no need to use difficult to scale external mechanisms to force collaboration or coordination among the agents, or to ensure that agents actively attempt to appropriate the tasks of agents that suffered failures. To present these results in a concrete setting, we focus on the problem of finding the sub-set of a set of imperfect devices that results in the best aggregate device. This is a large distributed agent coordination problem where each agent (e.g., device) needs to determine whether to be part of the aggregate device. Our results show that the approach proposed in this work provides improvements of over an order of magnitude over both traditional search methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents failed midway through the simulation) the system's performance degrades gracefully and still outperforms a failure-free and centralized search algorithm. The results also show that the gains increase as the size of the system (e.g., number of agents) increases. This latter result is particularly encouraging and suggests that this method is ideally suited for domains where the number of agents is currently in the thousands and will reach tens or hundreds of thousands in the near future.

Tumer, Kagan↗

Understanding Heating in Active Region Cores through Machine Learning. I. Numerical Modeling and Predicted Observables

To adequately constrain the frequency of energy deposition in active region cores in the solar corona, systematic comparisons between detailed models and observational data are needed. In this paper, we describe a pipeline for forward modeling active region emission using magnetic field extrapolations and field-aligned hydrodynamic models. We use this pipeline to predict time-dependent emission from active region NOAA 1158 for low-, intermediate-, and high-frequency nanoflares. In each pixel of our predicted multi-wavelength, time-dependent images, we compute two commonly used diagnostics: the emission measure slope and the time lag. We find that signatures of the heating frequency persist in both of these diagnostics. In particular, our results show that the distribution of emission measure slopes narrows and the mean decreases with decreasing heating frequency and that the range of emission measure slopes is consistent with past observational and modeling work. Furthermore, we find that the time lag becomes increasingly spatially coherent with decreasing heating frequency while the distribution of time lags across the whole active region becomes more broad with increasing heating frequency. In a follow-up paper, we train a random forest classifier on these predicted diagnostics and use this model to classify real observations of NOAA 1158 in terms of the underlying heating frequency.

UV radiation↗

Transient Plume Model Testing Using LADEE Spacecraft Attitude Control System Operations

We have learned it is conceivable that the Neutral Mass Spectrometer on board the Lunarr Atmosphere Dust Environment Explorer (LADEE) could measure gases from surface-reflected Attitude Control System (ACS) thruster plume. At minimum altitude, the measurement would be maximized, and gravitational influence minimized ("short" time-of-flight (TOF) situation) Could use to verify aspects of thruster plume modeling Model the transient disturbance to NMS measurements due to ACS gases reflected from lunar surface Observe evolution of various model characteristics as measured by NMS Species magnitudes, TOF measurements, angular distribution, species separation effects

Woronowicz, Michael↗