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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Flexible Wing Base Micro Aerial Vehicles: Micro Air Vehicles (MAVs) for Surveillance and Remote Sensor Delivery

Micro Air Vehicles (MAVs) will be developed for tracking individuals, locating terrorist threats, and delivering remote sensors, for surveillance and chemical/biological agent detection. The tasks are: (1) Develop robust MAV platform capable of carrying sensor payload. (2) Develop fully autonomous capabilities for delivery of sensors to remote and distant locations. The current capabilities and accomplishments are: (1) Operational electric (inaudible) 6-inch MAVs with novel flexible wing, providing superior aerodynamic efficiency and control. (2) Vision-based flight stability and control (from on-board cameras).

Ifju, Peter↗
DOE OSTI2022

A Study on Efficient Reinforcement Learning Through Knowledge Transfer

Although Reinforcement Learning (RL) algorithms have made impressive progress in learning complex tasks over the past years, there are still prevailing short-comings and challenges. Specifically, the sample-inefficiency and limited adaptation across tasks often make classic RL techniques impractical for real-world applications despite the gained representational power when combining deep neural networks with RL, known as Deep Reinforcement Learning (DRL). Recently, a number of approaches to address those issues have emerged. Many of those solutions are based on smart DRL architectures that enhance single task algorithms with the capability to share knowledge between agents and across tasks by introducing Transfer Learning (TL) capabilities. Here this survey addresses strategies of knowledge transfer from simple parameter sharing to privacy preserving federated learning and aims at providing a general overview of the field of TL in the DRL domain, establishes a classification framework, and briefly describes representative works in the area.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Critical Insights into Solvent Choice for High-Voltage Organosulfur Electrolytes

Organosulfur electrolytes are promising candidates for enabling high-voltage cathodes due to their superior oxidative stability compared to conventional carbonate-based systems. However, their viscous nature and inability to passivate the anode necessitate the use of passivating agents and diluents to achieve meaningful charge/discharge rates. In this study, we investigate the use of cyclic fluorinated carbonates (CFCs) to form passivating interphases on electrode surfaces, aiming to optimize electrolyte performance in high-voltage systems. Electrolyte formulations containing 1.2 M LiPF 6 in a CFC:sulfone:1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropylether (TTE) mixture (2/5/3 V/V/V) were assessed in full-cell configurations with a LiNi 0.8 Mn 0.1 Co 0.1 O 2 (FCG-NMC) cathode and a 4.5 V upper cutoff potential. The results reveal that 3-3-3-trifluoropropylene carbonate (TFPC) combined with ethyl methyl sulfone (EMS) optimizes electrolyte performance, resulting in lower resistance buildup and reduced capacity loss compared to commercial electrolytes. We also explore the failure mechanisms of several carbonate/sulfone mixtures and identify key considerations for electrolyte compatibility in high-voltage systems. TFPC enhances cycling stability and lowers overall cell resistance, while fluoroethylene carbonate (FEC) formulations, despite higher ionic conductivity, fail to form adequate passivation layers, leading to rapid capacity loss. Additionally, EMS provides superior physical properties that avoid common failure modes seen with other sulfone solvents like methyl isopropyl sulfone and tetramethylene sulfone. Furthermore, this study underscores the importance of carefully selecting passivating carbonates and sulfone solvents to improve electrolyte performance and expand the viability of high-voltage electrolyte systems.

LiNi0.8Mn0.1Co0.1O2 cathode↗
DOE OSTI2020

Regeneration of critical-sized defects, in a goat model, using a dextrin-based hydrogel associated with granular synthetic bone substitute

Abstract The development of injectable bone substitutes (IBS) have obtained great importance in the bone regeneration field, as a strategy to reach hardly accessible defects using minimally invasive techniques and able to fit to irregular topographies. In this scenario, the association of injectable hydrogels and bone graft granules is emerging as a well-established trend. Particularly, in situ forming hydrogels have arisen as a new IBS generation. An in situ forming and injectable dextrin-based hydrogel (HG) was developed, aiming to act as a carrier of granular bone substitutes and bioactive agents. In this work, the HG was associated to a granular bone substitute (Bonelike®) and implanted in goat critical-sized calvarial defects (14 mm) for 3, 6 and 12 weeks. The results showed that HG improved the handling properties of the Bonelike® granules and did not affect its osteoconductive features, neither impairing the bone regeneration process. Human multipotent mesenchymal stromal cells from the umbilical cord, extracellular matrix hydrolysates and the pro-angiogenic peptide LLKKK18 were also combined with the IBS. These bioactive agents did not enhance the new bone formation significantly under the conditions tested, according to micro-computed tomography and histological analysis.

Pereira, Isabel↗
DOE OSTI2023

Trust in News as Moderated by Known Truth Assessments and Source

Disinformation has become a problem in various spaces, from social media to organizations. Given the lack of evidence and transparency surrounding organizational disinformation, we aim to understand issue of information exposure effect and source trust from the lens of traditional information consumption online. Using an online experiment and multi-level mixed-effects modeling, we find that the exposure effect exists even over only two exposures to a headline, as long as participants are not shown fact-checking. Fact-checking can be effective in reducing the impact of the exposure effect. Additionally, we find that participants trusted sources significantly more before seeing the headlines. The possible presence of disinformation reduces trust in sources, even when considered highly neutral and reputable. These findings can inform simulations of agent interactions with misinformation as well as future experimental designs focused on evaluations of belief and trust based on recognizability of a source.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1982

Nonequilibrium material effects on the behavior of polymeric composite matrices and their related composites

The effects of physical aging on the material properties of some linear and network macromolecular glasses are discussed. The free volume concept is used to describe this behavior. The effect of physical aging on properties of some uniaxial graphite/fiber epoxy resin composites is investigated using stress relaxation in both tensile and flexural modes. The matrix polymers used were resins both of which are based on a 4,4-methylenedianiline derivative of epichlorohydrin with diamino diphenyl sulfone (DDS) as the curing agent. The matrix resin, as used in the practical application in composites, not fully cured and the glass transition of the network was dependent on the curing schedule. The physical aging of the bulk crosslinked epoxy was found to depend on the annealing temperature, and the T sub g of the resin. The physical aging of the composite, monitored by the stress relaxation method, was found to be dependent on the testing direction.

Wilkes, G. L.↗
NASA NTRS2017

Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

Meng, Ran↗
NASA NTRS2019

Impacts of In-Space Assembly as Applied to Human Exploration Architectures

Human missions to Mars present several major challenges that must be overcome, including delivering multiple large mass and volume elements, keeping the crew safe and productive, meeting cost constraints, and ensuring a sustainable campaign. Traditional methods for executing human Mars missions minimize or eliminate in-space assembly (iSA), which provides a narrow range of options for addressing these challenges and limits the types of missions that can be performed. This paper discusses recent work to evaluate how the inclusion of in-space assembly in space mission architectural concepts could provide novel solutions to address these challenges by increasing operational flexibility, robustness, risk reduction, crew health and safety, and sustainability. Several assembly focus areas identified through previous work were developed and evaluated to identify high-potential iSA applications that can have meaningful impacts on the challenges facing Mars missions. Architecture trade options were developed and assessed through sensitivity analyses, resulting in identification of six iSA-based architecture solutions that could be incorporated into Mars mission architectures with moderate levels of assembly. Assembly agent and infrastructure concepts were also developed that would be necessary to enable or facilitate the iSA operations. Several observations developed through the study are presented to inform future human mission architecture and campaign developments.

Jefferies, Sharon A.↗
NASA NTRS2022

Modal Logic Without Possible Worlds: A New Semantics for Modal Logic in Simplicial Complexes

In this paper, we set out to give a novel semantics for modal logic in simplicial complexes. The motivation for this semantics will be first the replacement of possible worlds with the idea of an ``agent perspective''. After exploring some of the philosophical implications of such a move, we give a semantics based around this idea. Following this, we explore some of the more interesting consequences of such a system, in particular the soundness of an unusual axiom we call NU^*. After giving soundness and completeness, we conclude by exploring ways to weaken this axiom in our semantics.

Philip Sink↗
DOE OSTI2025

A Dynamic Pricing Method to Manage the Impact of EV Charging on the Grid Using RL

This work addresses the challenge of managing electrical vehicle (EV) charging loads on distribution feeders with the increase in deployment of fast charging stations. To mitigate the adverse impacts on feeder health, a novel dynamic grid-informed pricing approach is proposed. This approach leverages reinforcement learning (RL) to determine hourly charging prices based on real-time grid conditions. A synthetic environment was developed to train the reinforcement learning agent. A model of an IEEE 34-bus distribution feeder with EV charging stations has been developed in OpenDSS utilizing Caldera for realistic EV charging profiles. Test cases demonstrate that the dynamic pricing strategy achieves higher energy delivery to the EV end user at a lower cost compared to constant pricing methods, while lowering voltage deviations and congestion. This approach offers more granular price adjustments, responding dynamically to feeder conditions and potentially improving grid stability and efficiency. The communication architecture to implement this dynamic pricing method is described. This research contributes to the development of smart grid-informed charging solutions that can reduce the cost of charging to the end user while also helping the grid.

EV charging, dynamic pricing, grid-informed chargi↗
DOE OSTI2025

A dynamic pricing method to manage the impact of EV charging on the grid using RL

This work addresses the challenge of managing electrical vehicle (EV) charging loads on distribution feeders with the increase in deployment of fast charging stations. To mitigate the adverse impacts on feeder health, a novel dynamic grid-informed pricing approach is proposed. This approach leverages reinforcement learning (RL) to determine hourly charging prices based on real-time grid conditions. A synthetic environment was developed to train the reinforcement learning agent. A model of an IEEE 34-bus distribution feeder with EV charging stations has been developed in OpenDSS utilizing Caldera for realistic EV charging profiles. Test cases demonstrate that the dynamic pricing strategy achieves higher energy delivery to the EV end user at a lower cost compared to constant pricing methods, while lowering voltage deviations and congestion. This approach offers more granular price adjustments, responding dynamically to feeder conditions and potentially improving grid stability and efficiency. The communication architecture to implement this dynamic pricing method is described. This research contributes to the development of smart grid-informed charging solutions that can reduce the cost of charging to the end user while also helping the grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A Q-Learning-Based Approach for Distributed Beam Scheduling in mmWave Networks

We consider the problem of distributed downlink beam scheduling and power allocation for millimeter-Wave (mmWave) cellular networks where multiple base stations (BSs) belonging to different service operators share the same unlicensed spectrum with no centralized control or explicit coordination among them. Our goal is to design efficient distributed beam scheduling and power allocation schemes such that the network-level payoff, defined as the weighted sum of the total throughput and a power penalization term, can be maximized. To this end, we propose a distributed scheduling approach to power allocation and adaptation for efficient interference management over the shared spectrum by modeling each BS as an independent Q-learning agent. As a baseline, we compare the proposed approach to the state-of-the-art non-cooperative game-based approach which was previously developed for the same problem. We conduct extensive experiments under various scenarios to verify the effect of multiple factors on the performance of both approaches. Experiment results show that the proposed approach adapts well to different interference conditions by learning from experience and thus can achieve higher payoff than the game-based approach. The proposed approach can also be integrated into our previously developed Lyapunov stochastic optimization framework for the purpose of network utility maximization with optimality guarantee. As a result, the weights in the payoff function can be automatically and optimally determined by the virtual queue values from the sub-problems derived from the Lyapunov optimization framework.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2017

Flight Deck Surface Trajectory-Based Operations (STBO): A Four-Dimensional Trajectory (4DT) Simulation

Within human factors there is burgeoning interest in the Human-Autonomy Teaming (HAT) concept as away to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous automation as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as plays (Shively et al., 2017). It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations (Nourbakhsh et al., 2005), healthcare and medicine (Tsui Yanco, 2007), autonomous vehicles (Parasuraman, Barnes, Cosenzo, Mulgund, 2007), photography (Lachter, Brandt, Sadler, Shively, in press), and aviation (Shively et al., in press). The current paper presents one such effort to apply HAT. It details the design of a R-HAT Agent developed as part of a NASA Research Agreement awarded to Human-Autonomy Teaming Solutions Inc. (HATS Inc), and developed in collaboration with the Human-Autonomy Teaming Laboratory at NASA Ames Research Center. The role of this Agent is to mediate interaction between the automation and the human operator of an advanced ground dispatch station, with this mediation based upon previously mentioned core tenets for HAT and the many lessons learned from the HAT research literature. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO; Lachter, Brandt, Battiste, Matessa, Johnson, in press). Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by the Agent, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, the Agent determines what tasks need to be done and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. The R-HAT Agent has been designed to both support end users and research in RCO and HAT. Additionally, the Agent and its underlying architecture were developed with generalizability in mind as a modular piece of software applicable outside of RCO aviation in domains such as those mentioned above. This paper will also discuss future further development and testing of the R-HAT Agent.

Bakowski, Deborah L.↗
NASA NTRS2009

Swarm autonomic agents with self-destruct capability

Systems, methods and apparatus are provided through which in some embodiments an autonomic entity manages a system by generating one or more stay alive signals based on the functioning status and operating state of the system. In some embodiments, an evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy. The evolvable neural interface receives and generates heartbeat monitor signals and pulse monitor signals that are used to generate a stay alive signal that is used to manage the operations of the synthetic neural system. In another embodiment an asynchronous Alice signal (Autonomic license) requiring valid credentials of an anonymous autonomous agent is initiated. An unsatisfactory Alice exchange may lead to self-destruction of the anonymous autonomous agent for self-protection.

Hinchey, Michael G.↗
NASA NTRS2011

Swarm autonomic agents with self-destruct capability

Systems, methods and apparatus are provided through which in some embodiments an autonomic entity manages a system by generating one or more stay alive signals based on the functioning status and operating state of the system. In some embodiments, an evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy. The evolvable neural interface receives and generates heartbeat monitor signals and pulse monitor signals that are used to generate a stay alive signal that is used to manage the operations of the synthetic neural system. In another embodiment an asynchronous Alice signal (Autonomic license) requiring valid credentials of an anonymous autonomous agent is initiated. An unsatisfactory Alice exchange may lead to self-destruction of the anonymous autonomous agent for self-protection.

Hinchey, Michael G.↗
DOE OSTI2025

Pricing Strategy of Electric Vehicle Aggregators Based on Locational Marginal Price to Minimize Photovoltaic (PV) Curtailment

The global climate crisis demands urgent action to mitigate global warming. Using renewable energy sources, such as solar and wind power, for electricity generation is crucial. This shift from centralized to distributed power systems, however, brings challenges, including voltage fluctuations and renewable energy curtailment. The rapid growth of the electric vehicle (EV) industry adds complexity, increasing overall electricity demand and straining the power supply during peak charging times. This paper proposes a scheduling strategy for EV aggregators to reduce renewable energy curtailment and stabilize grid operation by strategically scheduling EV charging. Using Multi -Agent Transport Simulation (MATSim), a traffic simulation tool, EV driving data in Denver, Colorado, USA, were modeled. The EV aggregator adjusts charging fees based on locational marginal prices, encouraging EVs to charge at different stations according to pricing. Simulations on an IEEE 33-bus system with distributed energy resources and EV charging stations validate the proposed algorithm, demonstrating its effectiveness in reducing curtailment by 12.55% and stabilizing grid operation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Understanding of three different polyvinylpyrrolidone (PVP) based battery binders blends on graphene surfaces from first principles via DFT simulations

Binders play a crucial role in binding electrodes, current collectors, and conductive agents during battery manufacturing. The selection of the binders and their blends considerably affect various properties such as mechanical durability, adhesion performance, ionic/electronic conductivities, and solid electrolyte interface stability for lithium-ion batteries. In this work, polyvinylidene di-fluoride (PVDF), polyacrylic acid (PAA), polyvinylpyrrolidone (PVP), and lithiated polyacrylic acid (Li-PAA) were selected as the model binders, and their blends were studied on graphene surfaces. Further, among them, PVDF is hardly soluble in water unlike the other binders, so in practice, the blend of PVP:PVDF is not thought to be a proper combination. However, the PVP:PVDF binder has also been included because the purpose of this work is to calculate several electronic properties such as binding energies, intermolecular interaction energies, bond critical points, electron density, and the Laplacian of electron density at critical bonding regions of all these blends at the molecular level via density functional theory (DFT) simulations in order to evaluate and compare how is the interaction strength and bonding type of three different lithium-ion batteries (LIBs) binder blends on graphene surfaces. Most stable binder pairs and their binding mechanisms on graphene surfaces were studied. The delocalization of lithium in Li-PAA was studied with the presence of water.

25 ENERGY STORAGE↗