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At least 91 records · Page 5

Impulsive Reconnection in the Sun's Atmosphere

Recent high-resolution observations from the Hinode mission show dramatically that the Sun's atmosphere is filled with explosive activity ranging from chromospheric explosions that reach heights of Mm, to coronal jets that can extend to solar radii, to giant coronal mass ejections (CME) that reach the edge of the heliosphere. The driver for all this activity is believed to be 3D magnetic reconnection. From the large variation observed in the temporal behavior of solar activity, it is clear that reconnection in the corona must take on a variety of distinct forms. The explosive nature of jets and CMEs requires that the reconnection be impulsive in that it stays off until a substantial store of free energy has been accumulated, but then turns on abruptly and stays on until much of this free energy is released. The key question, therefore, is what determines whether the reconnection is impulsive or not. We present some of the latest observations and numerical models of explosive and non-explosive solar activity. We argue that, in order for the reconnection to be impulsive, it must be driven by a quasi-ideal instability. We discuss the generality of our results for understanding 31) reconnection in other contexts.

Antiochos, Spiro K.↗

Architecture for Control of the K9 Rover

Software featuring a multilevel architecture is used to control the hardware on the K9 Rover, which is a mobile robot used in research on robots for scientific exploration and autonomous operation in general. The software consists of five types of modules: Device Drivers - These modules, at the lowest level of the architecture, directly control motors, cameras, data buses, and other hardware devices. Resource Managers - Each of these modules controls several device drivers. Resource managers can be commanded by either a remote operator or the pilot or conditional-executive modules described below. Behaviors and Data Processors - These modules perform computations for such functions as planning paths, avoiding obstacles, visual tracking, and stereoscopy. These modules can be commanded only by the pilot. Pilot - The pilot receives a possibly complex command from the remote operator or the conditional executive, then decomposes the command into (1) more-specific commands to the resource managers and (2) requests for information from the behaviors and data processors. Conditional Executive - This highest-level module interprets a command plan sent by the remote operator, determines whether resources required for execution of the plan are available, monitors execution, and, if necessary, selects an alternate branch of the plan.

Bresina, John L.↗

2011 Seattle Tolling Impact Survey

The 2011 Tolling Impact Survey measured the impact of tolling on travel behavior in Seattle, Washington. The Volpe Center conducted the survey on behalf of the U.S. Department of Transportation and the Urban Partnership Agreement. The population surveyed included drivers, public transportation users, carpoolers, and vanpoolers using the SR-520 corridor in Seattle. The survey was conducted in two phases—before and after toll implementation—to evaluate related attitude changes. The survey assessed route changes, trip timing, trip purpose, and travel mode (i.e., single-occupancy vehicle, carpool, or public transportation).

1Hz data↗

2011 Atlanta Tolling Impact Survey

The 2011 Tolling Impact Survey measured the impact of tolling on travel behavior in Atlanta, Georgia. The Volpe Center conducted the survey on behalf of the U.S. Department of Transportation and the Urban Partnership Agreement. The population surveyed included drivers, public transportation users, carpoolers, and vanpoolers using the I-85 corridor in Atlanta, Georgia. The survey was conducted in two phases—before and after toll implementation—to evaluate related attitude changes. The survey assessed route changes, trip timing, trip purpose, and travel mode (i.e., single-occupancy vehicle, carpool, or public transportation).

1Hz data↗

Resilient Strategies in Commercial Aviation

When we fly and nothing scary happens, is the system’s design affording this success? Not always — sometimes humans are the cause of success. This resilient performance is often overlooked. To capture this, we explore two types of strategies: countermeasures and modifications . First, countermeasures are behaviors triggered by variables anticipated to be challenging or problematic ( pressures ). To capture this, we look at examples of how a problem was avoided. For example, a country road may have a hairpin turn where accidents occur. With this pressure identified, we look at successful drivers for insights. Modifications are changes that are created to fill a gap between work-as-imagined and work-as-done. This strategy is from the design of systems. In aviation, work-as-imagined is often explicit, so it can be compared to behaviors using data. These two resilient potentials aim to better understand how systems function, as well as how people contribute to unrecognized successes.

Human factors↗

Energy–Performance Trade-offs in Privacy-Preserving Federated Learning on SmartNIC-Enabled HPC Systems

Federated learning (FL) is increasingly deployed on accelerator-rich high-performance computing (HPC) systems, yet the system-level energy cost of privacy-aware FL remains poorly understood, particularly across heterogeneous networking and server-placement options. We present a measurement-driven study of energy–performance trade-offs for FL on GH200-class nodes across three deployment configurations: CPU-Ethernet, CPU-InfiniBand (RDMA-capable), and a DPU-hosted FL server over InfiniBand using a BlueField-3 SmartNIC/DPU. Using NVIDIA FLARE (NVFLARE), we align node-level power telemetry with per-round timing extracted from NVFLARE logs to quantify time-to-solution (TTS), energy-to-solution (ETS), energy-delay product (EDP), and synchronization behavior for three transformer models (ALBERT, DistilBERT, BERT), trained with and without differential privacy (DP). We find that interconnect choice is the dominant driver of runtime and energy: host-managed InfiniBand consistently reduces communication overhead versus Ethernet, yielding lower TTS/ETS/EDP. In contrast, in our NVFLARE deployment, placing the FL server on the DPU does not consistently match CPU-InfiniBand performance and can be slower—especially for larger models—highlighting that server placement alone is not sufficient to guarantee end-to-end gains. Finally, under our fixed-round protocol, DP increases per-round cost and runtime variance; ETS increases largely in proportion to TTS because average node power remains relatively stable across configurations.

Kotevska, Olivera [ORNL] (ORCID:0000000316772243)↗

Nanosecond dual-wavelength irradiation effects on laser-induced damage in hafnia coatings

Nanosecond dual-wavelength laser-induced damage was investigated at 1064 nm (1ω) and 355 nm (3ω) on ion-beam-sputtered hafnia single-layer coatings. Single-wavelength 1-on-1 tests were first conducted to establish reference onset fluences. Dual-wavelength tests combined a primary beam with variable fluence at one wavelength and a background, secondary wavelength beam with fixed fluences set to several percentages of the corresponding onset fluence. When 1ω was used as the background irradiation, the perceived damage resistance at 3ω decreased gradually. Here, in contrast, 3ω background irradiation at as little as 10% of the onset fluence led to an ≈ 50% abrupt reduction in the perceived 1ω damage resistance, followed by modest changes upon further increases in 3ω background fluences. Scanning electron microscopy and conversion ratios indicate that 3ω light is the primary driver of damage onset in the case of dual wavelength irradiation. A two-step precursor generation and activation model reproduces the 3ω behavior (1ω as background), but not the strong initial 1ω reduction (3ω as background), suggesting additional 3ω-induced precursors that saturate at low fluence.

Optics and optical instruments↗

Autonomous Medical Care for Exploration

The goal of Autonomous Medical Care (AMC) is to ensure a healthy, well-performing crew which is a primary need for exploration. The end result of this effort will be the requirements and design for medical systems for the CEV, lunar operations, and Martian operations as well as a ground-based crew health optimization plan. Without such systems, we increase the risk of medical events occurring during a mission and we risk being unable to deal with contingencies of illness and injury, potentially threatening mission success. AMC has two major components: 1) pre-flight crew health optimization and 2) in-flight medical care. The goal of pre-flight crew health optimization is to reduce the risk of illness occurring during a mission by primary prevention and prophylactic measures. In-flight autonomous medical care is the capability to provide medical care during a mission with little or no real-time support from Earth. Crew medical officers or other crew members provide routine medical care as well as medical care to ill or injured crew members using resources available in their location. Ground support becomes telemedical consultation on-board systems/people collect relevant data for ground support to review. The AMC system provides capabilities to incorporate new procedures and training and advice as required. The on-board resources in an autonomous system should be as intelligent and integrated as is feasible, but autonomous does not mean that no human will be involved. The medical field is changing rapidly, and so a challenge is to determine which items to pursue now, which to leverage other efforts (e.g. military), and which to wait for commercial forces to mature. Given that what is used for the CEV or the Moon will likely be updated before going to Mars, a critical piece of the system design will be an architecture that provides for easy incorporation of new technologies into the system. Another challenge is to determine the level of care to provide for each mission type. The level of care refers to the amount and type of care one will render based on perceived need and ability. This is in contrast to the standard of care which is the benchmark by which that care is provided. There are certainly some devices and procedures that have unique microgravity or partial gravity requirements such that terrestrial methods will not work. For example, performing CPR on Mars cannot be done in exactly the same way as on Earth because the reduced gravity causes too large a reduction in the forces available for effective compression of the chest. Likewise, fluid behavior in microgravity may require a specialized water filtration and mixing system for the creation of intravenous fluids. This paper will outline the drivers for the design of the medical care systems, prioritization and planning techniques, key system components, and long term goals.

Johnson-Throop, Kathy A.↗

SSIM: NASA Mars rover robotics flight software simulation

The focus of SSim on MSL was the robotic flight software, including rover mobility and navigation, robotic arm manipulation, and sample acquisition, processing, and delivery. It can execute behaviors in simulation a thousand times faster than they execute in real time on the flight compute element. SSim is used by rover drivers to develop and validate command sequences throughout the planning cycle. SSim has been used to plan all of the Curiosity robotic operations since landing and is expected to continue to be used for the remaining life of the rover.

Leger, Chris↗

Probabilistic Risk Assessment for Decision Making During Spacecraft Operations

Decisions made during the operational phase of a space mission often have significant and immediate consequences. Without the explicit consideration of the risks involved and their representation in a solid model, it is very likely that these risks are not considered systematically in trade studies. Wrong decisions during the operational phase of a space mission can lead to immediate system failure whereas correct decisions can help recover the system even from faulty conditions. A problem of special interest is the determination of the system fault protection strategies upon the occurrence of faults within the system. Decisions regarding the fault protection strategy also heavily rely on a correct understanding of the state of the system and an integrated risk model that represents the various possible scenarios and their respective likelihoods. Probabilistic Risk Assessment (PRA) modeling is applicable to the full lifecycle of a space mission project, from concept development to preliminary design, detailed design, development and operations. The benefits and utilities of the model, however, depend on the phase of the mission for which it is used. This is because of the difference in the key strategic decisions that support each mission phase. The focus of this paper is on describing the particular methods used for PRA modeling during the operational phase of a spacecraft by gleaning insight from recently conducted case studies on two operational Mars orbiters. During operations, the key decisions relate to the commands sent to the spacecraft for any kind of diagnostics, anomaly resolution, trajectory changes, or planning. Often, faults and failures occur in the parts of the spacecraft but are contained or mitigated before they can cause serious damage. The failure behavior of the system during operations provides valuable data for updating and adjusting the related PRA models that are built primarily based on historical failure data. The PRA models, in turn, provide insight into the effect of various faults or failures on the risk and failure drivers of the system and the likelihood of possible end case scenarios, thereby facilitating the decision making process during operations. This paper describes the process of adjusting PRA models based on observed spacecraft data, on one hand, and utilizing the models for insight into the future system behavior on the other hand. While PRA models are typically used as a decision aid during the design phase of a space mission, we advocate adjusting them based on the observed behavior of the spacecraft and utilizing them for decision support during the operations phase.

dynamic fault trees↗

Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups

Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group-level processes such as subgroup formation and fission–fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals. We tracked 574 individuals from six species within the genus Canis in 15 countries on four continents with GPS telemetry to estimate the time that pairs of individuals within social groups spent in close proximity and test hypotheses regarding drivers of cohesion. Pairs of social canids (Canis spp.) varied widely in the proportion of time they spent together (5%–100%) during seasonal monitoring periods relative to both intrinsic characteristics and environmental conditions. The majority of our data came from three species of wolves (gray wolves, eastern wolves, and red wolves) and coyotes. For these species, cohesion within social groups was greatest between breeding pairs and varied seasonally as the nature of cooperative activities changed relative to annual life history patterns. Across species, wolves were more cohesive than coyotes. For wolves, pairs were less cohesive in larger groups, and when suitable, small prey was present reflecting the constraints of food resources and intragroup competition on social associations. Pair cohesion in wolves declined with increased anthropogenic modification of the landscape and greater climatic variability, underscoring challenges for conserving social top predators in a changing world. We show that pairwise cohesion in social groups varies strongly both within and across Canis species, as individuals respond to changing ecological context defined by resources, competition, and anthropogenic disturbance. Our work highlights that cohesion is a highly plastic component of animal sociality that holds significant promise for elucidating ecological and evolutionary mechanisms underlying cooperative behavior.

59 BASIC BIOLOGICAL SCIENCES↗

Development and Testing of a High Level Axial Array Duct Sound Source for the NASA Flow Impedance Test Facility

In this report both a frequency domain method for creating high level harmonic excitation and a time domain inverse method for creating large pulses in a duct are developed. To create controllable, high level sound an axial array of six JBL-2485 compression drivers was used. The pressure downstream is considered as input voltages to the sources filtered by the natural dynamics of the sources and the duct. It is shown that this dynamic behavior can be compensated for by filtering the inputs such that both time delays and phase changes are taken into account. The methods developed maximize the sound output while (i) keeping within the power constraints of the sources and (ii) maintaining a suitable level of reproduction accuracy. Harmonic excitation pressure levels of over 155dB were created experimentally over a wide frequency range (1000-4000Hz). For pulse excitation there is a tradeoff between accuracy of reproduction and sound level achieved. However, the accurate reproduction of a pulse with a maximum pressure level over 6500Pa was achieved experimentally. It was also shown that the throat connecting the driver to the duct makes it difficult to inject sound just below the cut-on of each acoustic mode (pre cut-on loading effect).

Johnson, Marty E.↗

A Vehicle-to-Grid planning framework incorporating electric vehicle user equilibrium and distribution network flexibility enhancement

The rapid surge in electric vehicle (EV) adoption, coupled with advancements in charging technologies, emphasizes the critical necessity for expanding EV recharging infrastructure. Simultaneously, the Distribution Network (DN) encounters escalating challenges in meeting charging demand during peak traffic periods. Consequently, there is a mounting demand for the deployment of innovative Vehicle-to-Grid (V2G) technologies to augment the DN’s flexibility in power dispatch and alleviate travel costs for EV users. Hence, this paper proposes an EV-user-equilibrium-(UE)-constrained V2G planning framework that enhances flexibility in the DN. The framework aims to ascertain the optimal placement and capacity of EV charging stations (EVCSs) and V2G charging piles within the Transportation Network (TN). It takes into account the equilibrium condition stemming from competitive EV charging and routing behaviors alongside the optimal expansion of DN energy resources to accommodate the electricity supplied by the V2G piles. This study commences by analyzing EV drivers’ travel decisions, considering the influence of charging and V2G pile locations and sizes. Subsequently, we tackle the Traffic Assignment Problem with User Equilibrium (TAP-UE) model to characterize the steady-state traffic flow distribution of EVs. Following this, we formulate the optimization model for the Coordinated Power and Transportation Network (CPTN), which encompasses the optimal expansion of DN facilities and traffic flow regulation under UE conditions. To mitigate the computational complexity associated with the V2G planning model, we introduce a series of linearization methods to obtain a manageable Mixed-Integer Linear Programming (MILP) solution. Finally, to validate the efficacy of our proposed planning framework, we apply it to two test systems, including a real-world case study. Through these case studies, we explore the necessity and potential benefits of V2G technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Oil price states and drivers: An analysis of the second-month spot-futures price differential

Oil remains a dominant component of global energy use, and its price, characterized by frequent changes and an ever-present potential for large swings, continues to be a focus of industry participants, policymakers and analysts attention. Here, this study examines the behavior of future spot oil prices using a continuous-time hidden Markov model (HMM) and daily price data spanning years 2007 to 2024. We identify six states in the second-month WTI spot-futures price differential and assess the roles of eleven futures price, quantity, financial market, and geopolitical/volatility variables in each state. The model yields several insights into the workings of the oil market and the relative roles of these drivers. We find support for several theoretical and empirical findings in the oil market literature, including the role of inventory, volatility/risk, and market responses to contango/backwardation in futures markets. A novel finding is that “normal contango” conditions represent a significant portion of next-day states in our in-sample data. Under the most volatile normal contango state, many of the oil market drivers differ markedly in coefficient signs and magnitudes from those in other states. The resulting model also performed well out-of-sample and would, in addition to understanding the impact of market drivers, be useful for short-term forecasting. Overall, the findings highlight the highly non-linear, regime-dependent interactions of the oil price and its drivers, emphasizing the importance of detailed information to market stakeholders.

Oladosu, Gbadebo A. [Oak Ridge National Laboratory↗

Measuring Unique Contextual Factors: Group Living Skills

BACKGROUND The Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite is a set of standardized measures used to assess behavioral health and performance risks related to future exploration-class space missions. During the HFBP-EM suite development, the importance of assessing unique contextual factors to understand the drivers of team dynamics was identified. Group living skills are a unique workplace skill which applies to those coworkers who live and work together. As mission lengths become longer, the line between work and non-work life may blur. Extreme living conditions such as spaceflight can result in increased stress over time, negatively impact mood and well-being, decrease team cohesion and increase conflict, deteriorate task performance, and potentially reduce mission success [1]. With no breaks in their isolated and confined environment possible, living with a messy, inconsiderate crewmember can add to the stress. Alternatively, crews with good group living skills may support one another, mitigating the negative effects of the extreme environment. There was no direct measure of group living skills. This work sought to fill this measurement gap and collect data related to group living in isolated, confined, extreme (ICE) environments. METHODS Group living skills as an astronaut competency area were developed with the input of experts familiar with ICE environments. Distinct aspects of this competency were reviewed and discussed by a NASA-invited group of spaceflight experts in 2015 to identify individual and team behavioral health and performance measures for operational environments. This work resulted in a 5-item measure focused on group living experiences with each crewmember (or the crew as a whole). A 6th item asks whether an individual would go on another mission with a particular crewmember or crew as a measure of future-oriented group living, or team viability. The measure was deployed in 24 teams living and working together in isolated and confined environments (e.g., International Space Station, space mission simulation analogs). RESULTS & DISCUSSION In this presentation, we will summarize results which indicate the Group Living Skills (GLS) Survey is a reliable, valid, and operationally feasible measure. Reliability was evaluated in several ways. Two-way multilevel mixed models revealed strong repeated measures reliability (ICC2 = .902, Omega between = .954). Reliability of change within teams was strong (Rc = .81). Factor analysis showed a consistent two-factor structure when individuals rated either the whole crew, all individuals, just peers, or a focal roommate. The latter used a sociometric approach to rating the GLS of the roommates. The two factors were tidiness and being considerate of others. We assessed the criterion-related validity of GLS, by examining GLS operationalized as the team-level aggregated GLS Survey scores as a predictor of team viability, team cohesion, and team performance. We used generalized mixed models to account for the repeated measures and longitudinal data. The marginal R2 change was used to determine the extent to which GLS were related to the team outcomes while controlling for mission day and campaign. Results suggested GLS was strongly related to team viability (marginal R2 change = .40), team cohesion (marginal R2 change = 0.28), social cohesion (marginal R2 change = 0.25), and moderately related to task cohesion (marginal R2 change = 0.18). GLS scores had a small relationship with team performance (marginal R2 change = .08). Results support GLS as a measure that can be used to capture group living skills of crews who live and work together in ICE. Because the items were written to be broadly applicable, less extreme environments with teams living and working together for some length of time also benefit from this measure (e.g., college roommates, camps). See Landon et al. (2024) for full results [2]. SUMMARY We report reliability and validity evidence for a new measure that assesses the Group Living Skills for teams that live and work in operational environments such as spaceflight.

J C W Miller↗

Detect the Unobservable: Abnormality Detection in mixed Autonomy for Lane Change Maneuver with Following Vehicles’ Trajectories Only

Highly Automated Vehicles (HAVs) and Advanced Driver-Assistance Systems (ADAS) are transforming modern transportation with enhanced mobility, safety, and efficiency. Despite their advantages, cybersecurity vulnerabilities in these systems can lead to abnormal behavior, posing significant risks to surrounding human-driven vehicles (HDVs) in mixed traffic environments. Here, this article addresses the challenge of detecting abnormal lateral movements of HAVs/ADAS vehicles using only trajectory profiles of following HDVs. Specifically, we propose a novel modeling approach that captures both normal and abnormal lateral behaviors through vehicle kinematics, integrated decision-making processes, vehicle control using symbolic regression for lane change vehicles. Additionally, we introduce an abnormality detection framework that relies on observable HDV data, even in occlusion scenarios. The framework evaluates the sensitivity of various car-following models to detect abnormal behaviors, providing insights into the interaction between HAVs/ADAS and HDVs in mixed autonomy systems.

Connected and Automated vehicles↗

Climatic drivers of continental-scale bird migration in spring

Avian migration studies conventionally divide North America into three or four primary flyways.This strategy has been adopted for convenience or determined by the time-averaged movement patterns, so it may not adequately reflect the real temporal variability of bird migration phenology. Using a unique radar-based data set (NEXRAD) covering the contiguous U.S. (CONUS), and an objective regionalization approach, we have identified two regions with distinct interannual variability of spring migration. This two-region approach helped us to distinguish the climatic drivers of year-to-year variability specific to the western and eastern CONUS. For example, we identified an east-west dipole pattern in migratory behavior linked to atmospheric Rossby waves that appeared to be triggered by oceanic forcing in the tropical Pacific. Our results offer a new geographic framework that would facilitate exploring the climatic cues affecting the interannual variability of migration phenology at the continental scale.

Amin Dezfuli↗

Quasiperiodic behavior in beam-driven strong Langmuir turbulence

The evolution of unmagnetized beam-driven strong Langmuir turbulence is studied in two dimensions by numerically integrating the Zakharov equations for systems pumped by monochromatic and broadband negative-damping drivers with nonzero central wavenumber. Long-time statistically steady states are reached for which the dependence of the evolution on the driver wavenumber, growth rate, and bandwidth is examined in detail. For monochromatic drivers, a quasiperiodic cycle is found to develop if the driver wavenumber is sufficiently large. The characteristic frequency of the quasiperiodic cycle and the average system energy are both approximately proportional to the growth rate. Broadening of the driver in wavenumber tends to degrade the system-wide coherence of the cycle, but its main features appear to survive on the scale of the coherence length of the driver.

Robinson, P. A.↗