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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 19 records

Probabilistic Forecasting of Ground Magnetic Perturbation Spikes at Mid-Latitude Stations

The prediction of large fluctuations in the ground magnetic field (dB/dt) is essential for preventing damage from Geomagnetically Induced Currents. Directly forecasting these fluctuations has proven difficult, but accurately determining the risk of extreme events can allow for the worst of the damage to be prevented. Here we trained Convolutional Neural Network models for eight mid-latitude magnetometers to predict the probability that dB/dt will exceed the 99th percentile threshold 30–60 min in the future. Two model frameworks were compared, a model trained using solar wind data from the Advanced Composition Explorer (ACE) satellite, and another model trained on both ACE and SuperMAG ground magnetometer data. The models were compared to examine if the addition of current ground magnetometer data significantly improved the forecasts of dB/dt in the future prediction window. A bootstrapping method was employed using a random split of the training and validation data to provide a measure of uncertainty in model predictions. The models were evaluated on the ground truth data during eight geomagnetic storms and a suite of evaluation metrics are presented. The models were also compared to a persistence model to ensure that the model using both datasets did not over-rely on dB/dt values in making its predictions. Overall, we find that the models using both the solar wind and ground magnetometer data had better metric scores than the solar wind only and persistence models, and was able to capture more spatially localized variations in the dB/dt threshold crossings.

Michael Coughlan↗

3D Normal Human Neural Progenitor Tissue-Like Assemblies: A Model of Persistent VZV Infection

Varicella-zoster virus (VZV) is a neurotropic human alphaherpesvirus that causes varicella upon primary infection, establishes latency in multiple ganglionic neurons, and can reactivate to cause zoster. Live attenuated VZV vaccines are available; however, they can also establish latent infections and reactivate. Studies of VZV latency have been limited to the analyses of human ganglia removed at autopsy, as the virus is strictly a human pathogen. Recently, terminally differentiated human neurons have received much attention as a means to study the interaction between VZV and human neurons; however, the short life-span of these cells in culture has limited their application. Herein, we describe the construction of a model of normal human neural progenitor cells (NHNP) in tissue-like assemblies (TLAs), which can be successfully maintained for at least 180 days in three-dimensional (3D) culture, and exhibit an expression profile similar to that of human trigeminal ganglia. Infection of NHNP TLAs with cell-free VZV resulted in a persistent infection that was maintained for three months, during which the virus genome remained stable. Immediate-early, early and late VZV genes were transcribed, and low-levels of infectious VZV were recurrently detected in the culture supernatant. Our data suggest that NHNP TLAs are an effective system to investigate long-term interactions of VZV with complex assemblies of human neuronal cells.

Goodwin, Thomas J.↗

Three-Dimensional Normal Human Neural Progenitor Tissue-Like Assemblies: A Model for Persistent Varicell-Zoster Virus Infection and Platform to Study Viral Infectivity and Oxidative Stress and Damage

The environment of space results in a multitude of challenges to the human physiology that present barriers to extended habitation and exploration. Over 40 years of investigation to define countermeasures to address space flight adaptation has left gaps in our knowledge regarding mitigation strategies partly due to the lack of investigative tools, monitoring strategies, and real time diagnostics to understand the central causative agent(s) responsible for physiologic adaptation and maintaining homeostasis. Spaceflight-adaptation syndrome is the combination of space environmental conditions and the synergistic reaction of the human physiology. Our work addresses the role of oxidative stress and damage (OSaD) as a negative and contributing Risk Factor (RF) in the following areas of combined spaceflight related dysregulation: i) radiation induced cellular damage [1], [2] ii) immune impacts and the inflammatory response [3], [4] and iii) varicella zoster virus (VZV) reactivation [5]. Varicella-zoster (VZV)/Chicken Pox virus is a neurotropic human alphaherpesvirus resulting in varicella upon primary infection, suppressed by the immune system becomes latent in ganglionic neurons, and reactivates under stress events to re-express in zoster and possibly shingles. Our laboratory has developed a complex threedimensional (3D) normal human neural tissue model that emulates several characteristics of the human trigeminal ganglia (TG) and allows the study of combinatorial experimentation which addresses, simultaneously, OSaD associated with Spaceflight adaptation and habitation [6].

Goodwin, T. J.↗

Three-Dimensional Normal Human Neutral Progenitor Tissue-Like Assemblies: A Model for Persistent Varicella-Zoster Virus Infection and Platform to Study Oxidate Stress and Damage in Multiple Hit Scenarios

The environment of space results in a multitude of challenges to the human physiology that present barriers to extended habitation and exploration. Over 40 years of investigation to define countermeasures to address space flight adaptation has left gaps in our knowledge regarding mitigation strategies partly due to the lack of investigative tools, monitoring strategies, and real time diagnostics to understand the central causative agent(s) responsible for physiologic adaptation and maintaining homeostasis. Spaceflight-adaptation syndrome is the combination of space environmental conditions and the synergistic reaction of the human physiology. Our work addresses the role of oxidative stress and damage (OSaD) as a negative and contributing Risk Factor (RF) in the following areas of combined spaceflight related dysregulation: i) radiation induced cellular damage [1], [2] ii) immune impacts and the inflammatory response [3], [4] and iii) varicella zoster virus (VZV) reactivation [5]. Varicella-zoster (VZV)/Chicken Pox virus is a neurotropic human alphaherpes virus resulting in varicella upon primary infection, suppressed by the immune system becomes latent in ganglionic neurons, and reactivates under stress events to re-express in zoster and possibly shingles. Our laboratory has developed a complex three-dimensional (3D) normal human neural tissue model that emulates several characteristics of the human trigeminal ganglia (TG) and allows the study of combinatorial experimentation which addresses, simultaneously, OSaD associated with Spaceflight adaptation and habitation [6]. By combining the RFs of microgravity, radiation, and viral infection we will demonstrate that living in the space environment leads to significant physiological consequences for the peripheral and subsequently the central nervous system (PNS, CNS) associated with OSaD generation and consequentially endangers long-duration and exploration-class missions.

Goodwin, Thomas J.↗

Irreversible wave-mean flow interactions in a mechanistic model of the stratosphere

A wave-1 minor warming is simulated in a mechanistic, global, primitive equation model. The modification of the zonal flow by the rearrangement of potential vorticity on a middle stratopheric isentrope is compared in a fully nonlinear model and in a model with only one wave and the zonal flow (a quasi-linear model). The permanent rearrangement of potential vorticity during the wave episode is more intense and more localized meridionally in the fully nonlinear model, which is able to capture the process of planetary wave breaking in some detail. Additional experiments reveal that the differences between the quasi-linear and nonlinear models persist for a broad range of wave amplitudes, and that the quasi-linear model can qualitatively reproduce the modification of the zonal flow by the wave when the diffusive dissipation of the wave is enhanced. These results are discussed in the context of the theory of barotropic Rossby waves in shear flows, and in comparison with recent numerical simulations of the middle atmosphere.

Robinson, Walter A.↗

ATTRACTOR: Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability

Autonomous systems (AS) are crucial to realizing the vision of new, complex transportation modes, such as advanced air mobility (AAM) and urban air mobility (UAM). A chief barrier to induction of AS into aviation is insufficient understanding of AS reliability in time-critical and safety-critical environments—an obstacle to certification. ATTRACTOR is aimed at building a basis for certification of classes of autonomous cyber-physical-human systems (CPHS) via establishing metrics and models of trustworthiness and trust in multi-agent team interactions, analyzable trajectories, explainability of computational algorithms (explainable artificial intelligence, or XAI), and persistent modeling and simulation, in the context of missions planning and operation. By “building a basis for certification,” we mean acquiring an understanding of when a system is trustworthy and developing computable means to estimate trustworthiness and trust in order to eventually inform functional requirements that contribute to certification. The outcomes are applicable not just to aviation but to all domains that rely on autonomous systems.

Autonomy↗

Serious Gaming for Building a Basis of Certification via Trust and Trustworthiness of Autonomous Systems

Autonomous systems governed by a variety of adaptive and nondeterministic algorithms are being planned for inclusion into safety-critical environments, such as unmanned aircraft and space systems in both civilian and military applications. However, until autonomous systems are proven and perceived to be capable and resilient in the face of unanticipated conditions, humans will be reluctant or unable to delegate authority, remaining in control aided by machine-based information and decision support. Proving capability, or trustworthiness, is a necessary component of certification. Perceived capability is a component of trust. Trustworthiness is an attribute of a cyber-physical system that requires context-driven metrics to prove and certify. Trust is an attribute of the agents participating in the system and is gained over time and multiple interactions through trustworthy behavior and transparency. Historically, artificial intelligence and machine learning systems provide answers without explanation - without a rationale or insight into the machine “thinking”. In order to function as trusted teammates, machines must be able to explain their decisions and actions. This transparency is a product of both content and communication. NASA’s Autonomy Teaming & TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) project seeks to build a basis for certification of autonomous systems via establishing metrics for trustworthiness and trust in multi-agent team interactions, using AI (Artificial Intelligence) explainability and persistent modeling and simulation, in the context of mission planning and execution, with analyzable trajectories. Inspired by Massively Multiplayer Online Role Playing Games (MMORPG) and Serious Gaming, the proposed ATTRACTOR modeling and simulation environment is similar to online gaming environments in which player (aka agent) participants interact with each other, affect their environment, and expect the simulation to persist and change regardless of any individual agent’s active participation. This persistent simulation environment will accommodate individual agents, groups of self-organizing agents, and large-scale infrastructure behavior. The effects of the emerging adaptation and coevolution can be observed and measured to building a basis of measurable trustworthiness and trust, toward certification of safety-critical autonomous systems.

Allen, B. Danette↗

CFD validation experiments at McDonnell Aircraft Company

Information is given in viewgraph form on computational fluid dynamics (CFD) validation experiments at McDonnell Aircraft Company. Topics covered include a high speed research model, a supersonic persistence fighter model, a generic fighter wing model, surface grids, force and moment predictions, surface pressure predictions, forebody models with 65 degree clipped delta wings, and the low aspect ratio wing/body experiment.

Verhoff, August↗

Uncertainty in Land-Use Adaptation Persists Despite Crop Model Projections Showing Lower Impacts Under High Warming

Climate change is expected to impact crop yields and alter resource availability. However, the understanding of the potential of agricultural land-use adaptation and its costs under climate warming is limited. Here, we use a global land system model to assess land-use-based adaptation and its cost under a set of crop model projections, including CO2 fertilization, based on climate model outputs. In our simulations of a low-emissions scenario, the land system responds through slight changes in cropland area in 2100, with costs close to zero. For a high emissions scenario and impacts uncertainty, the response tends toward cropland area changes and investments in technology, with average adaptation costs between −1.5 and +19 US$05 per ton of dry matter per year. Land-use adaptation can reduce adverse climate effects and use favorable changes, like local gains in crop yields. However, variance among high-emissions impact projections creates challenges for effective adaptation planning.

Agriculture↗

Evaluation of Machine Learning and Deep Learning Algorithms for Fire Prediction in Southeast Asia

Vegetation fires are prevalent in South/Southeast Asian countries, making fire prediction crucial due to their potential environmental, economic, and social impacts. Accurate predictions of fires facilitate timely interventions, helping to mitigate uncontrolled fires that can lead to biodiversity loss and air quality issues. In this study, we utilize VIIRS satellite-derived fire data alongside six machine learning and deep learning models—Simple Persistence, Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), CNN-LSTM, and ConvLSTM—to determine the most effective fire prediction model, using Root Mean Square Error (RMSE) as the metric. Our results indicate that the CNN model is the most reliable in regions with spatial dependencies, such as Brunei, Indonesia, Malaysia, the Philippines, Timor-Leste, and Thailand. Conversely, the ConvLSTM model excels in countries with complex spatiotemporal dynamics like Laos, Myanmar, and Vietnam. The CNN-LSTM hybrid model also performed well in Cambodia, suggesting a need for a balanced approach in areas requiring both spatial and temporal feature extraction. Furthermore, simpler models like Persistence and MLP showed limitations in capturing dynamic patterns and temporal dependencies. Our findings highlight the importance of evaluating models before implementing any decision support systems (DSS) in fire management. By tailoring models to specific regional fire data, we can enhance prediction accuracy and responsiveness, ultimately improving fire risk management in Southeast Asia and beyond.

Deep learning↗

Modulation of Terrestrial Convection by Tropospheric Humidity, and Implications for Other Planets

For decades, deep cumulus convection was viewed as consisting partly of undilute plumes that do not interact with their surrounding environment in order to explain their observed tendency to reach or penetrate the tropical tropopause. This behavior was built into all cumulus parameterizations used in terrestrial global climate and numerical weather prediction models, and it still persists in some models today. In the past decade, though, some embarrassing failures of global models have come to light, notably their tendency to rain over land near noon rather than in late afternoon or evening as observed, and the absence in the models of the Madden-Julian Oscillation (MJO), the major source of intraseasonal (30-90 day) precipitation variability in the Indian Ocean, West Pacific, and surrounding continental regions. In the past decade it has become clear that an important missing component of parameterizations is strong turbulent entrainment of drier environmental air into cumulus updrafts, which reduces the buoyancy of the updrafts and thus limits their vertical development. Tropospheric humidity thus serves as a throttle on convective penetration to high altitudes and delays the convective response to large-scale destabilizing influences in the environment.

tropical regions↗

Whole planet cooling and the radiogenic heat source contents of the earth and moon

Thermal evolution models based on subsolidus whole mantle convection which indicate that the surface heat flows of the earth and the moon do not necessarily provide good measures of the total amounts of radioactives in these bodies have been constructed. These models assume an initially hot state, but with a wide variety of choices for the parameters characterizing the rheology and convective vigor. All models are constrained to be consistent with present-day surface heat fluxes, and many of the terrestrial models are consistent with the mantle viscosities indicated by postglacial rebound. In the lunar models, heat generation is typically only 70-80% of the surface heat flow, even with allowance for the strong near-surface enhancement of radioactives. Despite the simplicity of these models, the persistence of a significant difference between heat generation and heat output indicates that this difference is real and should be incorporated in geochemical modeling of planets.

Schubert, G.↗

Persistence and predictability in a perfect model

A realistic two-level GCM is used to examine the relationship between predictability and persistence. Predictability is measured by the average divergence of ensembles of solutions starting from perturbed initial conditions, and persistence is defined in terms of the autocorrelation function based on a single long-term model integration. The average skill of the dynamical forecasts is compared with the skill of simple persistence-based statistical forecasts. For initial errors comparable in magnitude to present-day analysis errors, the statistical forecast loses all skill after about one week, reflecting the lifetime of the lowest frequency fluctuations in the model. Large ensemble mean dynamical forecasts would be expected to remain skillful for about 3 wk. The disparity between the skill of the statistical and dynamical forecasts is greater for the higher frequency modes, which have little memory beyond 1 d, yet remain predictable for about 2 wk. The results are analyzed in terms of two characteristic time scales.

Schubert, Siegfried D.↗

Ensemble formulation of surface fluxes and improvement in evapotranspiration and cloud parameterizations in a GCM

The influence of some modifications to the parameters of the current general circulation model (GCM) is investigated. The aim of the modifications was to eliminate strong occasional bursts of oscillations in planetary boundary layer (PBL) fluxes. Smoothly varying bulk aerodynamic friction and heat transport coefficients were found by ensemble averaging of the PBL fluxes in the current GCM. A comparison was performed of the simulations of the modified model and the unmodified model. The comparison showed that the surface fluxes and cloudiness in the modified model simulations were much more accurate. The planetary albedo in the model was also realistic. Weaknesses persisted in the models positioning of the Inter-tropical convergence zone (ICTZ) and in the temperature estimates for polar regions. A second simulation of the model following reparametrization of the cloud data showed improved results and these are described in detail.

Sud, Y. C.↗

Large-scale ocean-atmosphere interactions in a simplified coupled model of the midlatitude wintertime circulation

Midlatitude ocean-atmosphere interactions are studied in simulations from a simplified coupled model that includes synoptic-scale atmospheric variability, ocean current advection of SST, and air-sea heat exchange. Although theoretical dynamical ('identical twin') predictions using this model have shown that the SST anomalies in this model indeed influence the atmosphere, it is found here that standard cross correlation and empirical orthogonal function analyses of monthly mean model output yield the standard result, familiar from observational studies, that the atmosphere forces the ocean with little or no feedback. Therefore, these analyses are inconclusive and leave open the question of whether anomalous SST is influencing the atmosphere. In contrast, it is found that compositing strong warm events of model SST is a useful indicator of ocean forcing the atmosphere. Additional evidence is presented for oceanic influence on the atmosphere, namely, that ocean current advection appears to enhance the persistence of model SST anomalies through a feedback effect that is absent when only heat flux is allowed to influence SST anomaly evolution.

Miller, Arthur J.↗

Photographic Evidence of Streamwise Arrays of Vortices in Boundary-Layer Flow

Photographs are presented of various models coated with fluorescent oil to show evidence of surface vortices at a Mach number of 3.03. Vortex formation was evidently present on models with forward-facing steps, rearward-facing steps, wires, discrete surface particles, or unswept flat surfaces with sharp leading edges. Some photographs are also presented for the models coated with a sublimation material which clearly indicates the location of boundary-layer transition; however, it does not show the vortices as clearly as the fluorescent oil. The study was made on the models at an angle of attack of 0 deg at unit Reynolds numbers of 7.7 and 10.7 million per foot. The spacing of the vortices as indicated by the flow studies on the unswept model was smaller at the higher Reynolds number in accordance with Gortler's theory. The flow studies also indicated that stable surface vortices produced by either steps or surface roughness persisted over model areas known to have turbulent boundary layers.

Hopkins, Edward J.↗

Low and middle altitude cusp particle signatures for general magnetopause reconnection rate variations. 1: Theory

We present predictions of the signatures of magnetosheath particle precipitation (in the regions classified as open low-latitude boundary layer, cusp, mantle and polar cap) for periods when the interplanetary magnetic field has a southward component. These are made using the 'pulsating cusp' model of the effects of time-varying magnetic reconnection at the dayside magnetopause. Predictions are made for both low-altitude satellites in the topside ionosphere and for midaltitude spacecraft in the magnetosphere. Low-altitude cusp signatures, which show a continuous ion dispersion signature, reveal 'quasi-steady reconnection' (one limit of the pulsating cusp model), which persists for a period of at least 10 min. We estimate that 'quasi-steady' in this context corresponds to fluctuations in the reconnection rate of a factor of 2 or less. The other limit of the pulsating cusp model explains the instantaneous jumps in the precipitating ion spectrum that have been observed at low altitudes. Such jumps are produced by isolated pulses of reconnection: that is, they are separated by intervals when the reconnection rate is zero. These also generate convecting patches on the magnetopause in which the field lines thread the boundary via a rotational discontinuity separated by more extensive regions of tangential discontinuity. Predictions of the corresponding ion precipitation signatures seen by midaltitude spacecraft are presented. We resolve the apparent contradiction between estimates of the width of the injection region from midaltitude data and the concept of continuous entry of solar wind plasma along open field lines. In addition, we reevaluate the use of pitch angle-energy dispersion to estimate the injection distance.

Lockwood, M.↗