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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Advancing Autonomy in Distributed Space Systems: Insights From on-Orbit Testing with the Starling 1.0 Mission

Autonomous decision-making is crucial for enhancing mission effectiveness in Distributed Space Systems (DSS), particularly in multi-spacecraft operations where communication constraints and mission complexity pose challenges. The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in DSS through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. The DSA experiment onboard the Starling 1.0 Mission showcases collaborative resource allocation for multi-point science data collection with four small spacecraft. Autonomy in decision-making is highlighted as a crucial factor for multi-spacecraft missions, enabling spacecraft to operate independently, reducing reliance on ground control. This capability is particularly significant for future deep-space missions, where communication delays and limited data transmission capacity make traditional command and control approaches impractical. This demonstration focuses on a GPS Channel Selection Experiment, leveraging emergent capabilities like "shared sampling" and "simultaneous sampling" to optimize channel selection across the spacecraft swarm. The experiment aims to capture ionospheric phenomena such as the Equatorial Ionization Anomaly and Polar Patches. The DSA system's autonomous reconfiguration ability is showcased, emphasizing its adaptability to natural phenomena without significant integration efforts. The GPS Channel Selection Experiment utilizes a dual-band GPS receiver to estimate plasma density in the ionosphere. Explorative and exploitative channel selections are employed based on the nature of observed phenomena. The performance of DSA algorithms is evaluated in terms of optimal channel allocations and responsiveness to changes in observed features. The DSA Flight Software utilizes the Core Flight System (cFS) framework, ensuring compatibility with the Starling 1.0 flight mission software. DSA showcases results from RTI’s Connext DDS Micro communication middleware, enabling message routing over the Ad-Hoc Network of Starling 1.0. This paper provides a comprehensive overview of the DSA experiment's initial results, emphasizing the advancements in autonomy for Distributed Space Systems and the successful collaboration with the Starling 1.0 mission.

Caleb Ashmore Adams↗
NASA NTRSDate not supplied

Innovations in Distributed Spacecraft Autonomy

The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in distributed space systems through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. This talk describes recent successes of the DSA experiment onboard the Starling 1.0 mission.

Caleb Adams↗
DOE OSTI2012

Promoting the Market for Plug-in Hybrid and Battery Electric Vehicles: Role of Recharge Availability

Much recent attention has been drawn to providing adequate recharge availability as a means to promote the battery electric vehicle (BEV) and plug-in hybrid electric vehicle (PHEV) market. The possible role of improved recharge availability in developing the BEV-PHEV market and the priorities that different charging options should receive from the government require better understanding. This study reviews the charging issue and conceptualizes it into three interactions between the charge network and the travel network. With travel data from 3,755 drivers in the National Household Travel Survey, this paper estimates the distribution among U.S. consumers of (a) PHEV fuel-saving benefits by different recharge availability improvements, (b) range anxiety by different BEV ranges, and (c) willingness to pay for workplace and public charging in addition to home recharging. With the Oak Ridge National Laboratory MA3T model, the impact of three recharge improvements is quantified by the resulting increase in BEV-PHEV sales. Compared with workplace and public recharging improvements, home recharging improvement appears to have a greater impact on BEV-PHEV sales. The impact of improved recharging availability is shown to be amplified by a faster reduction in battery cost.

25 ENERGY STORAGE↗
DOE OSTI2014

ISMB Conference Funding to Support Attendance of Early Researchers and Students

ISMB Conference Funding for Students and Young Scientists Historical Description The Intelligent Systems for Molecular Biology (ISMB) conference has provided a general forum for disseminating the latest developments in bioinformatics on an annual basis for the past 22 years. ISMB is a multidisciplinary conference that brings together scientists from computer science, molecular biology, mathematics and statistics. The goal of the ISMB meeting is to bring together biologists and computational scientists in a focus on actual biological problems, i.e., not simply theoretical calculations. The combined focus on “intelligent systems” and actual biological data makes ISMB a unique and highly important meeting. 21 years of experience in holding the conference has resulted in a consistently well-organized, well attended, and highly respected annual conference. "Intelligent systems" include any software which goes beyond straightforward, closed-form algorithms or standard database technologies, and encompasses those that view data in a symbolic fashion, learn from examples, consolidate multiple levels of abstraction, or synthesize results to be cognitively tractable to a human, including the development and application of advanced computational methods for biological problems. Relevant computational techniques include, but are not limited to: machine learning, pattern recognition, knowledge representation, databases, combinatorics, stochastic modeling, string and graph algorithms, linguistic methods, robotics, constraint satisfaction, and parallel computation. Biological areas of interest include molecular structure, genomics, molecular sequence analysis, evolution and phylogenetics, molecular interactions, metabolic pathways, regulatory networks, developmental control, and molecular biology generally. Emphasis is placed on the validation of methods using real data sets, on practical applications in the biological sciences, and on development of novel computational techniques. The ISMB conferences are distinguished from many other conferences in computational biology or artificial intelligence by an insistence that the researchers work with real molecular biology data, not theoretical or toy examples; and from many other biological conferences by providing a forum for technical advances as they occur, which otherwise may be shunned until a firm experimental result is published. The resulting intellectual richness and cross-disciplinary diversity provides an important opportunity for both students and senior researchers. ISMB has become the premier conference series in this field with refereed, published proceedings, establishing an infrastructure to promote the growing body of research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Public Health Analysis Transport Optimization Model v. 1.0

PHANTOM models logistic functions of national public health systems. The system enables public health officials to visualize and coordinate options for public health surveillance, diagnosis, response and administration in an integrated analytical environment. Users may simulate and analyze system performance applying scenarios that represent current conditions or future contingencies what-if analyses of potential systemic improvements. Public health networks are visualized as interactive maps, with graphical displays of relevant system performance metrics as calculated by the simulation modeling components.

Beyeler, Walt↗
DOE OSTI2023

AI-Driven Smart Community Control for Accelerating PV Adoption and Enhancing Grid Resilience

The U.S. Department of Energy (DOE) has launched a Connected Communities program that supports projects that expand DOE's network of grid-interactive, efficient building communities nationwide. As an early pilot of Connected Communities, the National Renewable Energy Laboratory (NREL) and its partners have developed and demonstrated a community-scale, hierarchical control solution to address the potential grid issues arising from high penetration of solar photovoltaics (PV) as well as to improve grid reliability and resilience in this residential community. A field pilot study has been performed at an affordable housing development called the Basalt Vista Community, which was built for school teachers and other professionals in the local workforce and represents an autonomous energy grid with all-electric, energy-efficient homes. With no natural gas line in the community, this is the first all-electric net-zero community in rural Colorado. In the field pilot study, NREL has validated the performance of the hierarchical control solution, which consists of NREL's foresee home energy management systems (HEMS) and community aggregators, in increasing demand flexibility and self-consuming PV, reducing potential over-voltages, and supporting critical loads during emergency events. In this presentation, we will present the methodology, simulation and field pilot results, and lessons learned from the project.

all-electric community↗
DOE OSTI2018

A Framework for Imperfectly Observed Networks

Model a network as an edge-weighted graph, where the (unknown) weight w{sub e} of edge e indicates the frequency of observed interactions, and over time t we observe a Poisson (tw{sub e}) number of interactions across edges e. How should we estimate some given statistic of the underlying network? This leads to wide-ranging and challenging problems, on which this article makes only partial progress.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A Dynamic Pore Network Model for Imbibition Simulation Considering Corner Film Flow

Wetting films can develop in the corners of angular pores under strong wetting conditions. Modeling the dynamics of corner film remains elusive using direct numerical simulations because of the significant scale difference between main meniscus and corner film flow. In this paper, the modified interacting capillary bundle model (ICB), developed in our previous work to describe accurately corner film dynamics in a single square tube, is incorporated into a single-pressure dynamic pore network model (DPNM) to simulate imbibition in strongly wetting porous media with corner film flow. The traditional pore network is decomposed into several layers of interacting subpore networks where the 0th layer of subpore network simulates the main meniscus flow and higher layers the corner film flow. The fluid flow between different layers is captured by interlayer throats. In addition, the snap-off mechanism caused by the thickening of wetting corner film is considered. The accuracy of the developed model is validated for four cases: spontaneous imbibition in a single square tube, wetting fluid redistribution through corner films under a capillary pressure difference, snap off in a narrow throat connecting two large pores, and imbibition dynamics in a real microfluidic porous geometry. The validated model is then used to simulate both spontaneous and controlled imbibition in a pore network with random pore size distribution. Finally, the interaction between corner film and main meniscus flow in porous media is analyzed from a pore-scale perspective.

58 GEOSCIENCES↗
DOE OSTI2014

Electrical conductivity and luminescence properties of two silver(I) coordination polymers with heterocyclic nitrogen ligands

The synthesis and X-ray structural characterization of two novel silver(I) coordination polymers, [Ag(NO{sub 3})(quin)]{sub n} (1) and [Ag{sub 8}(HL){sub 2}(H{sub 2}O){sub 4}(mpyz)]·3H{sub 2}O (2) are reported, where quin=5,6,7,8-tetrahydroquinoxaline, H{sub 6}L=cyclohexane-1,2,3,4,5,6-hexacarboxylic acid and mpyz=2-methyl pyrazine. The single crystal diffraction analyses showed that complex 1 is a 2D layered structure, while 2 presents a 3D polymeric architecture. In complex 2 the network is stabilized by argentophilic interactions and hydrogen bonding. Electrical conductivity of order 3×10{sup −4} Scm{sup −1} (1) and 1.6×10{sup −4} Scm{sup −1} (2) is measured on thin film specimen at room temperature. The photoluminescence and thermal properties of the complexes have also been studied. - Graphical abstract: Two new 1D and 3D coordination polymers of Ag(I) have been synthesized and characterized by X-ray analysis. The electrical, luminescence and thermal properties have been studied. - Highlights: • 1 is 2D layered while 2 present a 3D polymeric architecture. • The network in 2 is stabilized by argentophilic interactions and hydrogen bonding. • Electrical conductivity measurement is quite interesting. • Argentophilic interaction and intra-ligand π{sup ⁎}–π CT explains emission behavior of 2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Impact of Dispersion Solvent on Ionomer Thin Films and Membranes

Perfluorosulfonic acid (PFSA) ionomers are an important class of materials that many electrochemical devices rely on as their ion-conducting electrolyte. Often, PFSA films are prepared through solution-processing techniques. Previous research has demonstrated that the solvent environment affects PFSA dispersion conformation, but it is not clear to what extent (if at all) these conformational effects persist for thin films and membranes upon casting, nor how dispersion solvent impacts film formation during the drying process. Here in this paper, we explore these questions by systematically examining the effect of Thin Film all length scales affected by dispersion solvent water and n-propanol mixtures on PFSA thin-film formation and structure, membrane structure, and resulting properties. Using a combination of in situ, time-resolved grazing incidence X-ray scattering and tender wide-angle X-ray scattering, it is shown that films prepared from high-water-concentration dispersions exhibit stronger interactions and arrangement upon drying, and possess larger network domain sizes than those prepared from low-water-concentration dispersions. These stronger interactions likely manifest in greater network connectivity, as evidenced by enhanced conductivity for membranes and decreased water uptake for thin films. Significantly, these solvent-induced differences persist even after thermal annealing. It is clear that the dispersion solvent choice is a critical parameter controlling PFSA nano- and mesoscale structure and presents an important dial with which to direct PFSA macroscale properties.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Simulating ensembles of nonlinear continuous time dynamical systems via active ultra wideband wireless network

The paper deals with a new multi-element processor platform assigned for modelling the behaviour of interacting dynamical systems, i.e., active wireless network. Experimentally, this ensemble is implemented in an active network, the active nodes of which include direct chaotic transceivers and special actuator boards containing microcontrollers for modelling the dynamical systems and an information display unit (colored LEDs). The modelling technique and experimental results are described and analyzed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2008

Ground-based Network and Supersite Measurements for Studying Aerosol Properties and Aerosol-Cloud Interactions

From radiometric principles, it is expected that the retrieved properties of extensive aerosols and clouds from reflected/emitted measurements by satellite (and/or aircraft) should be consistent with those retrieved from transmitted/emitted radiance observed at the surface. Although space-borne remote sensing observations contain large spatial domain, they are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite datasets. The development and deployment of AERONET (AErosol RObotic NETwork) sunphotometer network and SMART-COMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere) mobile supersite are aimed for the optimal utilization of collocated ground-based observations as constraints to yield higher fidelity satellite retrievals and to determine any sampling bias due to target conditions. To characterize the regional natural and anthropogenic aerosols, AERONET is an internationally federated network of unique sunphotometry that contains more than 250 permanent sites worldwide. Since 1993, there are more than 480 million aerosol optical depth observations and about 15 sites have continuous records longer than 10 years for annual/seasonal trend analyses. To quantify the energetics of the surface-atmosphere system and the atmospheric processes, SMART-COMMIT instrument into three categories: flux radiometer, radiance sensor and in-situ probe. Through participation in many satellite remote-sensing/retrieval and validation projects over eight years, SMART-COMMIT have gradually refine( and been proven vital for field deployment. In this paper, we will demonstrate the capability of AERONET SMART-COMMIT in current Asian Monsoon Year-2008 campaigns that are designed and being executed to study the compelling variability in temporal scale of both anthropogenic and natural aerosols (e.g., airborne dust, smoke, mega-city pollutant). Feedback mechanisms between aerosol radiative effects and monsoon dynamics have been recently proposed, however there is a lack of consensus on whether aerosol forcing would be more likely to enhance or reduce the strength of the monsoon circulation. We envision robust approaches which well-collocated ground-based measurements and space-borne observations will greatly advance our understanding of absorbing aerosols (e.g., "Global Dimming" vs. "Elevated Heat-Pump" effects) on aerosol cloud water cycle interactions.

Tsay, Si-Chee↗
DOE OSTI2014

Hybrid methods for cybersecurity analysis :

Early 2010 saw a signi cant change in adversarial techniques aimed at network intrusion: a shift from malware delivered via email attachments toward the use of hidden, embedded hyperlinks to initiate sequences of downloads and interactions with web sites and network servers containing malicious software. Enterprise security groups were well poised and experienced in defending the former attacks, but the new types of attacks were larger in number, more challenging to detect, dynamic in nature, and required the development of new technologies and analytic capabilities. The Hybrid LDRD project was aimed at delivering new capabilities in large-scale data modeling and analysis to enterprise security operators and analysts and understanding the challenges of detection and prevention of emerging cybersecurity threats. Leveraging previous LDRD research e orts and capabilities in large-scale relational data analysis, large-scale discrete data analysis and visualization, and streaming data analysis, new modeling and analysis capabilities were quickly brought to bear on the problems in email phishing and spear phishing attacks in the Sandia enterprise security operational groups at the onset of the Hybrid project. As part of this project, a software development and deployment framework was created within the security analyst work ow tool sets to facilitate the delivery and testing of new capabilities as they became available, and machine learning algorithms were developed to address the challenge of dynamic threats. Furthermore, researchers from the Hybrid project were embedded in the security analyst groups for almost a full year, engaged in daily operational activities and routines, creating an atmosphere of trust and collaboration between the researchers and security personnel. The Hybrid project has altered the way that research ideas can be incorporated into the production environments of Sandias enterprise security groups, reducing time to deployment from months and years to hours and days for the application of new modeling and analysis capabilities to emerging threats. The development and deployment framework has been generalized into the Hybrid Framework and incor- porated into several LDRD, WFO, and DOE/CSL projects and proposals. And most importantly, the Hybrid project has provided Sandia security analysts with new, scalable, extensible analytic capabilities that have resulted in alerts not detectable using their previous work ow tool sets.

Dunlavy, Daniel M.↗
DOE OSTI2022

Dynamics of particle network in composite battery cathodes

We report that improving composite battery electrodes requires a delicate control of active materials and electrode formulation. The electrochemically active particles fulfill their role as energy exchange reservoirs through interacting with the surrounding conductive network. We formulate a network evolution model to interpret the regulation and equilibration between electrochemical activity and mechanical damage of these particles. Through statistical analysis of thousands of particles using x-ray phase contrast holotomography in a LiNi 0.8 Mn 0.1 Co 0.1 O 2 -based cathode, we found that the local network heterogeneity results in asynchronous activities in the early cycles, and subsequently the particle assemblies move toward a synchronous behavior. Our study pinpoints the chemomechanical behavior of individual particles and enables better designs of the conductive network to optimize the utility of all the particles during operation.

25 ENERGY STORAGE↗
DOE OSTI2023

Mean Field Theory of Self‐Organizing Memristive Connectomes

Abstract Biological neuronal networks are characterized by nonlinear interactions and complex connectivity. Given the growing impetus to build neuromorphic computers, understanding physical devices that exhibit structures and functionalities similar to biological neural networks is an important step toward this goal. Self‐organizing circuits of nanodevices are at the forefront of the research in neuromorphic computing, as their behavior mimics synaptic plasticity features of biological neuronal circuits. However, an effective theory to describe their behavior is lacking. This study provides for the first time an effective mean field theory for the emergent voltage‐induced polymorphism of circuits of a nanowire connectome, showing that the behavior of these circuits can be explained by a low‐dimensional dynamical equation. The equation can be derived from the microscopic dynamics of a single memristive junction in analytical form. The effective model is tested on experiments of nanowire networks and show that it fits both the potentiation and depression of these synapse‐mimicking circuits. It is shown that this theory applies beyond the case of nanowire networks by formulating a general mean‐field theory of conductance transitions in self‐organizing memristive connectomes.

Caravelli, Francesco↗
DOE OSTI2015

GBNV encoded movement protein (NSm) remodels ER network via C-terminal coiled coil domain

Plant viruses exploit the host machinery for targeting the viral genome–movement protein complex to plasmodesmata (PD). The mechanism by which the non-structural protein m (NSm) of Groundnut bud necrosis virus (GBNV) is targeted to PD was investigated using Agrobacterium mediated transient expression of NSm and its fusion proteins in Nicotiana benthamiana. GFP:NSm formed punctuate structures that colocalized with mCherry:plasmodesmata localized protein 1a (PDLP 1a) confirming that GBNV NSm localizes to PD. Unlike in other movement proteins, the C-terminal coiled coil domain of GBNV NSm was shown to be involved in the localization of NSm to PD, as deletion of this domain resulted in the cytoplasmic localization of NSm. Treatment with Brefeldin A demonstrated the role of ER in targeting GFP NSm to PD. Furthermore, mCherry:NSm co-localized with ER–GFP (endoplasmic reticulum targeting peptide (HDEL peptide fused with GFP). Co-expression of NSm with ER–GFP showed that the ER-network was transformed into vesicles indicating that NSm interacts with ER and remodels it. Mutations in the conserved hydrophobic region of NSm (residues 130–138) did not abolish the formation of vesicles. Additionally, the conserved prolines at positions 140 and 142 were found to be essential for targeting the vesicles to the cell membrane. Further, systematic deletion of amino acid residues from N- and C-terminus demonstrated that N-terminal 203 amino acids are dispensable for the vesicle formation. On the other hand, the C-terminal coiled coil domain when expressed alone could also form vesicles. These results suggest that GBNV NSm remodels the ER network by forming vesicles via its interaction through the C-terminal coiled coil domain. Interestingly, NSm interacts with NP in vitro and coexpression of these two proteins in planta resulted in the relocalization of NP to PD and this relocalization was abolished when the N-terminal unfolded region of NSm was deleted. Thus, the NSm interacts with NP via its N-terminal unfolded region and the NSm–NP complex could in turn interact with the ER membrane via the C-terminal coiled coil domain of NSm to form vesicles that are targeted to PD and there by assist the cell to cell movement of the viral genome complex. - Highlights: • GBNV NSm localizes to plasmodesmata via the C-terminal coiled coil domain. • GBNV NSm interacts with endoplasmic reticulum network and remodels it to vesicles. • The C-terminal coiled domain alone is responsible for vesicle formation. • The N-terminal unfolded region of NSm is involved in the re-localization of NP to PD.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2023

Blade-Wake Interaction Noise for Small Hovering Rotors, Part I: Characterization Study

This work illustrates the use of artificial neural network modeling to study and characterize broadband blade-wake interaction noise from hovering small unmanned aerial systems rotors subject to varying airfoil geometries, rotor geometries, and operating conditions. Design of experiments was used to create input feature spaces, and a high-fidelity strategy was implemented at the discrete data points defined by the input feature spaces to design airfoils and rotor blades, predict the unsteady rotor aerodynamics and aeroacoustics, and isolate the blade-wake interaction noise from the acoustic broadband noise. A metric for the blade-wake interaction noise was developed, and the ANOPP2 Artificial Neural Network Tool was used to identify an optimal prediction model for the nonlinear relationship between the input features and the metric for blade-wake interaction noise. This optimal artificial neural network was then validated over training/test data and exhibited prediction accuracy over 91% for data previously unseen by the model. A sensitivity analysis was conducted, which showed that input features that directly modify the thrust coefficient had a dominant effect over blade-wake interaction noise. The optimal prediction model along with aerodynamic simulations were used to further study the effect of varying input features on blade-wake interaction noise, and three types of blade-wake interaction noise were identified

Christopher S. Thurman↗
DOE OSTI2017

Chemically interconnected light-weight 3D-carbon nanotube solid network

Owing to the weak physical interactions such as van der Waals and π-π interactions, which hold nanotubes together in carbon nanotube (CNT) bulk structures, the tubes can easily slide on each other. In creating covalent interconnection between individual carbon nanotube (CNT) structures we saw remarkable improvements in the properties of their three-dimensional (3D) bulk structures. The creation of such nanoengineered 3D solid structures with improved properties and low-density remains one of the fundamental challenges in real-world applications. We also report the scalable synthesis of low-density 3D macroscopic structure made of covalently interconnected nanotubes using free-radical polymerization method after functionalized CNTs with allylamine monomers. The resulted interconnected highly porous solid structure exhibits higher mechanical properties, larger surface area and greater porosity than non-crosslinked nanotube structures. To gain further insights into the deformation mechanisms of nanotubes, fully atomistic reactive molecular dynamics simulations are used. Here we demonstrate one such utility in CO 2 uptake, whose interconnected solid structure performed better than non-interconnected structures.

36 MATERIALS SCIENCE↗