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There is an increasing need for space missions to be able to collaboratively (and competitively) develop plans both within and across missions. In addition, interacting spacecraft that interleave onboard planning and execution must reach consensus on their commitments to each other prior to execution.
an increasing need for space missions to be able to collaboratively (and competitively) develop plans both within and across missions. In addition, interacting spacecraft that interleave onboard planning and execution must reach consensus on their commitments to each other prior to execution. In domains where missions have varying degrees of interaction and different constraints on communication and computation, the missions will require different coordination protocols in order to efficiently reach consensus with in their imposed deadlines. We describe a Shared Activity Coordination (SHAC) framework that provides a decentralized algorithm for negotiating the scheduling of shared activities over the lifetimes of multiple agents and a foundation for customizing protocols for negotiating planner interactions. We investigate variations of a few simple protocols based on argumentation and distributed constraints satisfaction techniques and evaluate their abilities to reach consistent solutions according to computation, time, and communication costs in an abstract domain where spacecraft propose joint measurements.
Roughness influences the flux of wind driven sand transport. In this paper, we report on sediment transport measurements for four different surface roughness configurations composed of the same size (solid) roughness elements in the atmospheric inertial sublayer (ISL). Results of these tests indicate that sediment transport rates through patches of roughness in the atmospheric inertial sublayer are to a large extent controlled and scale proportionally with the roughness density (lambda = n b h/S, where n is number of elements of breadth b and height h in area S) of the surface. However, element size apparently increases the magnitude of the reduction beyond that attributable to lambda. A sediment transport model that incorporates the effect of shear stress partitioning appears to predict reasonably well the effect of roughness on sand transport in the cases where the roughness elements are less than or equal to 0.10 m in height. However, when the dimensions of the roughness itself are equivalent to or are greater than the range of saltation lengths (vertical and horizontal), additional interactions of the elements with the saltation cloud appear to reduce the transport efficiency.
The acoustic assessment task for both the Subsonic Fixed Wing and the Supersonic projects under NASA s Fundamental Aeronautics Program was designed to assess the current state-of-the-art in noise prediction capability and to establish baselines for gauging future progress. The documentation of our current capabilities included quantifying the differences between predictions of noise from computer codes and measurements of noise from experimental tests. Quantifying the accuracy of both the computed and experimental results further enhanced the credibility of the assessment. This presentation gives sample results from codes representative of NASA s capabilities in aircraft noise prediction both for systems and components. These include semi-empirical, statistical, analytical, and numerical codes. System level results are shown for both aircraft and engines. Component level results are shown for a landing gear prototype, for fan broadband noise, for jet noise from a subsonic round nozzle, and for propulsion airframe aeroacoustic interactions. Additional results are shown for modeling of the acoustic behavior of duct acoustic lining and the attenuation of sound in lined ducts with flow.
Stratospheric wave events and major sudden stratospheric warming (SSW) events are well captured in high-resolution global forecasts out to 10 days. Tropospheric influences of SSW include statistically significant shifts in the storm tracks and associated surface temperature and precipitation pattern changes. Since these events can in turn influence the troposphere on time scales of 30-60 days the ability to predict these events and the subsequent long-term response on time scales beyond 10 days is of interest. Here we examine the prediction of stratospheric wave events and their evolution using the NASA GMAO (Global Modeling and Assimilation Office) Sub-Seasonal to Seasonal (S2S) system. This is a recently released subseasonal to seasonal forecast system, GEOS-S2S version 2.1. Compared to GMAO's previous system, the new version runs at higher atmospheric resolution (approximately 1/2 degree globally), contains a substantially improved model of the cryosphere, includes additional interactive aerosol model components, and the ocean data assimilation system has been replaced with a Local Ensemble Transform Kalman Filter. Results are based on a comprehensive series of hindcasts starting from the year 2000. They show that while the S2S system is not as accurate at 10 days in forecasting major SSW events as the NASA GMAO Forward Processing system, it can usefully predict stratospheric anomalies out to 20 days and the subsequent stratospheric/tropospheric evolution beyond 30 days.
Defining a feasible vehicle design and mission architecture capable of reliably delivering apayload of 20 metric tons (mt) or more is a great challenge for landing humans on Mars. TheMid Lift-to-Drag Rigid Vehicle (MRV), a rigid decelerator studied in NASA’s Entry, Descent,and Landing Architecture Study (EDLAS), has shown to be a viable vehicle candidate forfuture human Mars missions. As the vehicle concept matures, models of increasing fidelity areadded to the six-degree-of-freedom (6DoF) EDL simulation. This paper presents 6DoFsimulation results using model updates for vehicle mass properties, fineness ratio, andaerodynamic-propulsive interactions. Additionally, an assessment of the Fractional-Polynomial Powered Descent Guidance (FP2DG) performance is presented, and the vehicleperformance is compared with the Tunable Apollo Powered Descent Guidance (TAPDG).Finally, Monte Carlo results of the vehicle design trades are presented.
Humanity is standing on the cusp of its next giant leap – an international, sustainable, and commercial return to the moon. Unlike the Apollo missions, the expectation that a permanent human presence will be established is well founded. Initially, crewed missions to the lunar surface are expected to last between 6 and 30 days and occur approximately once per year, however the robust suite of landers and orbiting assets proposed by both commercial and government entities provide an opportunity to conduct science research on the moon and in cis-lunar space, 24x7 for many years. In the 50 years since the conclusion of Apollo, NASA’s crewed space science missions have been evolving. This can be seen clearly from Skylab and the Space Shuttle’s Spacelab to the International Space Station (ISS). Presently aboard the ISS, international crews spend nearly half their time working on experiments while many payloads collect science non-stop with either very limited, or no crew interaction. Additionally, a fleet of orbiting experiments complement and validate those investigations performed on the ISS. As the number, variety, and complexity of these investigation increase, it becomes ever more necessary to integrate across the many entities involved to prevent duplication of effort, ensure complementary results, reduce cost, and create a sustainable environment to conduct groundbreaking scientific research in space. In this paper, we examine how the various elements of the Artemis program including NASA’s Lunar Gateway, Commercial Lunar Payload Services (CLPS) endeavor, the Human Landing Systems (HLS), surface habitats, rovers and many more will be operated to ensure interoperability, maximize science return, and enable success for government, commercial and private partners.
Humanity is standing on the cusp of its next giant leap – an international, sustainable, and commercial return to the moon. Unlike the Apollo missions, the expectation that a permanent human presence will be established is well founded. Initially, crewed missions to the lunar surface are expected to last between 6 and 30 days and occur approximately once per year, however the robust suite of landers and orbiting assets proposed by both commercial and government entities provide an opportunity to conduct science research on the moon and in cis-lunar space, 24x7 for many years. In the 50 years since the conclusion of Apollo, NASA’s crewed space science missions have been evolving. This can be seen clearly from Skylab and the Space Shuttle’s Spacelab to the International Space Station (ISS). Presently aboard the ISS, international crews spend nearly half their time working on experiments while many payloads collect science non-stop with either very limited, or no crew interaction. Additionally, a fleet of orbiting experiments complement and validate those investigations performed on the ISS. As the number, variety, and complexity of these investigation increase, it becomes ever more necessary to integrate across the many entities involved to prevent duplication of effort, ensure complementary results, reduce cost, and create a sustainable environment to conduct groundbreaking scientific research in space. In this paper, we examine how the various elements of the Artemis program including NASA’s Lunar Gateway, Commercial Lunar Payload Services (CLPS) endeavor, the Human Landing Systems (HLS), surface habitats, rovers and many more will be operated to ensure interoperability, maximize science return, and enable success for government, commercial and private partners.
The Quasi-Biennial Oscillation (QBO) impacts the large-scale circulation by altering lower stratospheric meridional temperature gradients which alter the propagation of upward propagating planetary waves. Proposed teleconnections of the QBO include impacts on the stratospheric polar vortices, extratropical surface winter climate, and the Madden-Julian Oscillation. However, long-term projections of the QBO remain highly uncertain. While recent multi-model investigations (Richter et al. 2019, Butchart et al. 2020) show that the amplitude of the QBO weakens robustly among models, changes in QBO period and stability remain highly uncertain. Here we examine the QBO response to increased greenhouse gases using the NASA Goddard Institute for Space Studies Middle Atmosphere Model E2.2 (Rind et al., 2020; Orbe et al. 2020). Compared to lower vertical resolution versions of ModelE, E2.2 also has a higher model top (0.002 hPa) and employs additional interactive non-orographic gravity wave drag sources from convection and shear, which produce a sufficiently realistic QBO, thus rendering it suitable for use in climate change studies. Overall, we find that both the QBO period and amplitude decrease in response to increased CO , the former related to increased lower stratospheric momentum fluxes (associated with convection) and the latter associated partly with a stronger residual mean circulation. Experiments integrated using fully interactive chemistry also reveal that ozone feedbacks significantly impact the magnitude of the QBO amplitude response. Finally, integrations using fixed (pre-industrial) sea surface temperatures (SST) show that the QBO amplitude responds differently to rapid adjustments versus SST feedbacks, as compared to the QBO period.
This invention relates to the field of energy storage devices, and especially electrochemical energy storage devices including electrolytes comprising an ionic liquid, one or more solvents, and one or more salts of a Group 2 element. Effects on electrochemical performance of the electrolyte of each of the components of the electrolyte were systematically determined. In addition, interactions between the electrolytes and separator films were dissected to optimize electrochemical performance of coin cell batteries.
Sensitivity analysis in terrestrial ecosystem modeling is important for understanding controlling processes, guiding model development, and targeting new observations to reduce parameter and prediction uncertainty. Complex and computationally expensive terrestrial ecosystem models (TEM) limit the number of ensemble simulations, requiring sophisticated and efficient methods to analyze sensitivities of multiple model responses to different types of parameter uncertainties. In this study, we propose a distance-based global sensitivity analysis (DGSA) method. DGSA first classifies model response samples into a small set of discrete classes and then calculates the distance between parameter frequency distributions in different classes to measure the parameter sensitivity. The principle is that, if the parameter distribution is the same in each class, then the model response is insensitive to the parameter, while a large difference in the distributions indicates the parameter is influential to the response. Built on this idea, DGSA can be applied to analyze sensitivity of a single and a group of responses to different kinds of parameter uncertainties including continuous, discrete and even stochastic. Besides the main-effect sensitivity from a single parameter, DGSA can also quantify the sensitivity from parameter interactions. Additionally, DGSA is computationally efficient which can use a small number of model evaluations to obtain an accurate and statistically significant result. We applied DGSA to two TEMs, one having eight parameters and three kinds of model responses, and the other having 47 parameters and a long-period response. We demonstrated that DGSA can be used for sensitivity problems with multiple responses and high-dimensional parameters efficiently.
In today’s digital world, the spread of fake news and the rise of AI-generated text have become major threats to content authenticity and public trust. This thesis addresses both challenges through two complementary research directions: detecting fake news using multimodal features, and identifying AI-generated text using semantic and structural reasoning. The first part of the work focuses on fake news detection by introducing a novel model that combines text and image features through a unique rotational attention mechanism. Unlike traditional attention methods, this approach rotates the roles of query, key, and value across modalities to capture deeper interactions. Additionally, the model incorporates external domain information by linking news posts to top-ranked websites from Google search results, which helps assess the credibility of content based on its broader web context. This results in a more reliable and accurate fake news detection system that outperforms existing state-of-the-art methods. The second part presents SGG-ATD, a new framework for detecting AI-generated text. It uses masked language modeling to measure sentence coherence, followed by constructing a graph where keywords—both original and predicted—are connected based on semantic and contextual similarity. A Graph Convolutional Network (GCN) is then used to learn structural relationships within the text for final classification. Experimental results demonstrate that SGG-ATD achieves high F1-scores and consistently outperforms strong baselines. This method contributes to robust AI text detection, supporting accountability and resilience against AI-driven misinformation.
The interaction of laser radiation with foams of various porosities and low densities has been the subject of several numerical and experimental studies. In all cases, the modeling of low-Z under-dense foams as uniform gases of equivalent average density using standard radiation-hydrodynamics codes has resulted in heat-front velocities that are considerably faster than those observed experimentally. It has been theoretically conjectured that this difference may be attributed to the breakdown of the foam’s morphology, leading to a dynamics of filament expansion where the ion and electron energy partitions are significantly different from those calculated using the uniform gas model. We found that 3D computer simulations employing a disconnected representation of the foam’s microstructure which allowed for the dynamics of foam element heating, expansion, and stagnation largely supported the theoretical picture. Simulations using this model for laser experiments on under-dense 2 mg cc -1 SiO 2 aerogel foams reproduced the experimental data fairly well. We used the validated model in simulations of low-density structured foam-like materials (produced via additive manufacturing) with a variety of morphologies. We found that the log-pile configurations were consistent with the analytical propagation model of Gus’kov et al. Further validation of the model was obtained by simulating experiments performed at the Jupiter Laser Facility using the log-pile and octet-truss foam morphologies. Simulations of the foam-laser interaction using a wave propagation code showed that the microstructure was able to enhance stimulated Brillouin scattering (SBS) by concentrating the light energy into density holes. In turn, this promotes laser filamentation, reducing SBS and bringing the predicted values closer to the experimental data.
In situ monitoring is required to improve the understanding and increase the reliability of additive manufacturing methods such as laser powder bed fusion (LPBF). Current diagnostic methods for LPBF capture optical images, X-ray radiographs, or measure the emission of thermal or acoustic signals from the component. Herein, a methodology based on the thermal emission of electrons - thermionic emission - from the metal surface during LPBF is proposed which can resolve laser-material interaction dynamics. The high sensitivity of thermionic emission to surface temperature and surface morphology is revealed to enable precise determination of the transition between conduction and keyhole mode melting regimes. Increases in thermionic emission are correlated to laser scanning conditions that give rise to pore formation and regions where surface defects are pronounced. The information presented here is a critical step in furthering our understanding and validation of laser-based metal additive manufacturing.
The Surface Modeling and Grid Generation for Iced Airfoils (SmaggIce) software toolkit has been extended to allow interactive grid generation for multi-element iced airfoils. The essential phases of an icing effects study include geometry preparation, block creation and grid generation. SmaggIce Version 2.0 now includes these main capabilities for both single and multi-element airfoils, plus an improved flow solver interface and a variety of additional tools to enhance the efficiency and accuracy of icing effects studies. An overview of these features is given, especially the new multi-element blocking strategy using the multiple wakes method. Examples are given which illustrate the capabilities of SmaggIce for conducting an icing effects study for both single and multi-element airfoils.
Epitaxial growth has been widely used for high-quality growth of crystalline materials. However, epitaxial growth techniques usually require lattice match and similar thermal expansion coefficient between growth material and substrate, which blocks this growth technique from wide applicability. Recently, van der Waals (vdW) epitaxy has been demonstrated that allows to relax the limitation of epitaxial growth. vdW epitaxy on layered or two-dimensional (2D) materials is mediated by weak vdW interactions. In addition to these interactions, a substrate below 2D materials also plays a role to intervene in the epitaxial growth process, leaving room to realize a novel epitaxial growth process: remote epitaxy. Potential fluctuation—the difference between potential energy maxima and minima along the surface of the substrate—is influenced by this remote interaction; the fluctuation is predominant over the vdW force, due to the atomic thickness of 2D materials. The remote interactions can be controlled by modulation of polarities of 2D materials and epitaxy materials. Polar-material-based heterostructure, such as GaAs, InP, GaP and GaN with their substrate sandwiching 2D materials, enables the semiconductor film to be exfoliated from the underlying substrates through the 2D materials. This process is expected to open a novel avenue for the field of non-silicon electronics and photonics, where the ability to re-use graphene-coated substrates allows savings on the high cost of non-silicon substrates.
The Exploration Medical Capability (ExMC) Element Systems Engineering (SE) goals include defining the technical system needed to support medical capabilities for a Mars exploration mission. A draft medical system architecture was developed based on stakeholder needs, system goals, and system behaviors, as captured in an ExMC concept of operations document and a system model. This talk will discuss a high-level view of the medical system, as part of a larger crew health and performance system, both of which will support crew during Deep Space Transport missions. Other mission components, such as the flight system, ground system, caregiver, and patient, will be discussed as aspects of the context because the medical system will have important interactions with each. Additionally, important interactions with other aspects of the crew health and performance system are anticipated, such as health & wellness, mission task performance support, and environmental protection. This talk will highlight areas in which we are working with other disciplines to understand these interactions.
Processing additive plays an important role in the standard operation procedures for fabricating top performing polymer solar cells (PSCs) through efficient interactions with key photovoltaic materials. However, improving interaction study of acceptor materials to high performance halogenated aromatic additives such as diiodobenzene (DIB) is a widely neglected route for molecular engineering toward more efficient device performances. Here, in this work, two novel Y-type acceptor molecules of BTP-TT and BTP-TTS with different aromatic side chains on the outer positions are designed and synthesized. The resulting aromatic side chains significantly enhanced the interactions between the acceptor molecules and DIB through an arene/halogenated arene interaction, which improved the crystallinity of the acceptor molecules and induced a polymorph with better photovoltaic performances. Thus, high power conversion efficiencies (PCEs) of 18.04% and 19.22% are achieved in binary and ternary blend devices using BTP-TTS as acceptor and DIB as additive. Aromatic side chain engineering for improving additive interactions is proved to be an effective strategy for achieving much higher performance photovoltaic materials and devices.