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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Providing Effective Access to Shared Resources: A COIN Approach

Managers of systems of shared resources typically have many separate goals. Examples are efficient utilization of the resources among its users and ensuring no user's satisfaction in the system falls below a preset minimal level. Since such goals will usually conflict with one another, either implicitly or explicitly the manager must determine the relative importance of the goals, encapsulating that into an overall utility function rating the possible behaviors of the entire system. Here we demonstrate a distributed, robust, and adaptive way to optimize that overall function. Our approach is to interpose adaptive agents between each user and the system, where each such agent is working to maximize its own private utility function. In turn, each such agent's function should be both relatively easy for the agent to learn to optimize, and 'aligned' with the overall utility function of the system manager - an overall function that is based on but in general different from the satisfaction functions of the individual users. To ensure this we enhance the COllective INtelligence (COIN) framework to incorporate user satisfaction functions in the overall utility function of the system manager and accordingly in the associated private utility functions assigned to the users agents. We present experimental evaluations of different COIN-based private utility functions and demonstrate that those COIN-based functions outperform some natural alternatives.

Airiau, Stephane↗
NASA NTRS2004

Providing Effective Access to Shared Resources: A COIN Approach

Managers of systems of shared resources typically have many separate goals. Examples are efficient utilization of the resources among its users and ensuring no user s satisfaction in the system falls below a preset minimal level. Since such goals will usually conflict with one another, either implicitly or explicitly the manager must determine the relative importance of the goals, encapsulating that into an overall utility function rating the possible behaviors of the entire system. Here we demonstrate a distributed, robust, and adaptive way to optimize that overall function. Our approach is to interpose adaptive agents between each user and the system, where each such agent is working to maximize its own private utility function. In turn, each such agent's function should be both relatively easy for the agent to learn to optimize, and "aligned" with the overall utility function of the system manager - an overall function that is based on but in general different from the satisfaction functions of the individual users. To ensure this we enhance the Collective INtelligence (COIN) framework to incorporate user satisfaction functions in the overall utility function of the system manager and accordingly in the associated private utility functions assigned to the users agents. We present experimental evaluations of different COIN-based private utility functions and demonstrate that those COIN-based functions outperform some natural alternatives.

Airiau, Stephane↗
DOE OSTI2022

Development of a Lateral Flow Strip-Based Recombinase-Aided Amplification for Active Chlamydia psittaci Infection

Chlamydia psittaci is the causative agent of psittacosis, a worldwide zoonotic disease. A rapid, specific, and sensitive diagnostic assay would be benefit for C. psittaci infection control. In this study, an assay combining recombinase-aided amplification and a lateral flow strip (RAA-LF) for the detection of active C. psittaci infection was developed. The RAA-LF assay targeted the CPSIT_RS02830 gene of C. psittaci and could be accomplished in 15 min at a single temperature (39°C). The analytical sensitivity of the assay was as low as 1 × 10 0 copies/μl and no cross-reaction with some other intracellular pathogens was observed. Moreover, all feces samples from mice infected with C. psittaci at day-1 post-infection were positive in the RAA-LF assay. In conclusion, the RAA-LF assay provides a convenient, rapid, specific and sensitive method for detection of active C. psittaci infection and it is also suitable for C. psittaci detection in field.

Jiao, Jun↗
DOE OSTI2020

Mechanisms of Degradation of Toxic Nerve Agents: Quantum-chemical Insight into Interactions of Sarin and Soman with Molybdenum Dioxide

With the urgent need to provide an efficient and reliable protection for people from fatal chemical and biological weapons, our fundamental understanding of how toxins interact with filters is far from complete. The situation is further complicated by natural difficulties of performing experimental measurements with lethal toxins. Unlike experiments, computational modeling offers an attractive and safe yet reliable way of studying behavior of toxic agents on a variety of substrates at a great level of detail. Here, we report DFT-based quantum-chemical calculations of adsorption and decomposition of DMMP, sarin and soman on MoO 2 (011) surface. Our calculations show that MoO 2 strongly adsorbs toxic nerve agents and quickly decomposes them. Decomposition of DMMP on the MoO 2 (011) surface proceeds via the PO-CH 3 bond breaking and a formation of a surface methoxy group. The calculated activation barrier for this reaction is 131.5 kJ mol -1 . Unlike DMMP, decomposition of sarin and soman proceeds via the dealkylation reaction yielding propene and 3,3-dimethyl-1-butene, respectively. Decomposition of sarin requires a remarkably low energy (53.7 kJ mol- 1 ), whereas the similar reaction in soman requires 50 kJ mol -1 more energy. We also make specific predictions to guide Ambient-Pressure X-ray Photoelectron Spectroscopy (APXPS) experiments on sarin interaction with MoO 2 samples. We conclude that MoO 2 serves as an efficient substrate able of degrading toxins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Synthesis of PHI-type zeolite harmotome using barium as an inorganic structure-directing agent inspired from natural mineral compositions

Zeolites are nanoporous aluminosilicates widely used as commercial adsorbents, heterogeneous catalysts, and ion-exchange materials due to their unique porosity, acidity, and thermal stability. The vast majority of synthetically-realized zeolite structures are prepared under hydrothermal conditions in alkaline media, and often in the presence of an organic structure-directing agent that facilitates the crystallization of diverse porous networks. Due to economic and environmental disadvantages of organic-based syntheses, it is often desirable to produce zeolites in organic-free media using alkali metal ions as the most commonly employed inorganic structure-directing agents (ISDAs). Here, in this study, we were inspired by the elemental compositions of natural zeolite minerals to examine the use of an alkaline earth metal ion as the ISDA to prepare zeolites with the PHI framework type. Two natural minerals exhibiting this crystal structure are phillipsite and harmotome. Both structures contain sodium and potassium as extra-framework cations, but only harmotome contains barium cations. Here we examined how the combination of alkali and alkaline earth ISDAs promote the formation of PHI-type zeolites. Our findings reveal that each isostructure is prepared under different synthesis conditions where simply adding barium to a growth mixture does not always lead to harmotome formation. Harmotome is formed in more dilute and alkaline growth media; however, time-resolved analyses of zeolite crystallization reveal that harmotome can be synthesized at low temperatures (ca. 65 °C) with rates that are 5-times faster than syntheses of phillipsite. This seemingly indicates that barium reduces the energetic barrier for PHI-type zeolite nucleation in ways that are not fully understood. Moreover, harmotome crystals exhibit an average particle size of ca. 60 nm, which is nearly 40-fold smaller than phillipsite crystals prepared under similar conditions. Collectively, these findings identify routes to control crystallization of PHI-type zeolites and may provide a broader strategy for using the composition of natural zeolite minerals to optimize the preparation of synthetic analogues.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Applying Biomimetic Algorithms for Extra-Terrestrial Habitat Generation

The objective is to simulate and optimize distributed cooperation among a network of robots tasked with cooperative excavation on an extra-terrestrial surface. Additionally to examine the concept of directed Emergence among a group of limited artificially intelligent agents. Emergence is the concept of achieving complex results from very simple rules or interactions. For example, in a termite mound each individual termite does not carry a blueprint of how to make their home in a global sense, but their interactions based strictly on local desires create a complex superstructure. Leveraging this Emergence concept applied to a simulation of cooperative agents (robots) will allow an examination of the success of non-directed group strategy achieving specific results. Specifically the simulation will be a testbed to evaluate population based robotic exploration and cooperative strategies while leveraging the evolutionary teamwork approach in the face of uncertainty about the environment and partial loss of sensors. Checking against a cost function and 'social' constraints will optimize cooperation when excavating a simulated tunnel. Agents will act locally with non-local results. The rules by which the simulated robots interact will be optimized to the simplest possible for the desired result, leveraging Emergence. Sensor malfunction and line of sight issues will be incorporated into the simulation. This approach falls under Swarm Robotics, a subset of robot control concerned with finding ways to control large groups of robots. Swarm Robotics often contains biologically inspired approaches, research comes from social insect observation but also data from among groups of herding, schooling, and flocking animals. Biomimetic algorithms applied to manned space exploration is the method under consideration for further study.

Birge, Brian↗
NASA NTRSDate not supplied

Zero-Trust Architecture for Autonomous Edge Computing

We are at the apex of an aviation revolution where autonomy will play a central role in enabling complex, multi-agent systems to communicate, interact, and collaborate on a myriad of applications spanning autonomous swarms to wild-fire management. Autonomy is not an absolute but rather a spectrum ranging from a system requiring significant human intervention to one requiring little to none [1]. For example, the extreme, in the case of an autonomous aircraft, is one that operates independently in the airspace interacting with all other elements (air traffic controllers, other pilots) as if it were a human pilot. Critical to this vision is an architecture that enables autonomous agents to interact with minimal latency. Edge computing is an emerging architecture where compute and storage is pushed to the ‘edge’ of the network in order to minimize the round-trip time from agent to resource thereby mitigating the latency associated with cloud-only based approaches. Additionally, services can generate massive amounts of data (e.g., video feeds), which may require analysis in near real-time. Moving this data to the cloud for further processing may not be feasible due to latency, bandwidth, and cost. Privacy, security, and reliability can also be improved by edge computing architectures. However, this geo-distributed and dynamic* architecture complicates the establishment of unambiguous network security boundaries and can lead to vulnerabilities including man in the middle attacks, replay attacks, physical security breaches of edge nodes, signal interception, etc. This motivates the need for zero-trust architectures [2–4] which de-emphasize the notion of static network perimeters and, as the name implies, do not instill any innate trust in any particular agent. It is required that all agents must be authorized and approved in every transaction. In this paper, we present a zero-trust architecture suitable for edge-computing applications that demand significant low-latency, security, privacy, and reliability.

zero trust↗
DOE OSTI2020

Enhanced detection of volatile organic compounds (VOCs) by caffeine modified carbon nanotube junctions

Detection of vapor phase analytes and gas molecules is primarily essential for numerous applications including medical diagnostic, environmental monitoring, chemical threat detection, food quality control, and chemical warfare agents. Here, we developed Caffeine functionalized carbon nanotubes (CNTs) random network based vapor quantum resistive sensors (vQRSs) for volatile organic compounds (VOCs) detection. The localized transmission electron microscopy (TEM) image and energy dispersive X-ray spectroscopy (EDS) confirm migration of caffeine to CNT–CNT junction (CNTj). We have recorded more than one order of magnitude higher sensitivity and unique selectivity towards selective VOCs (e.g., acetone, toluene, ethanol, methanol, etc.) with short response time (few seconds) for caffeine modified CNT junction (Caf-CNTj) vQRSs. Molecular dynamics (MD) calculations suggest that the sensitivity of the sensor is diffusion limited, with an advective contribution for ethanol. Furthermore, the designed Caf-CNTj sensors can potentially be important candidate to be a part of electronic nose used for various application such as breath analysis and food quality monitoring.

36 MATERIALS SCIENCE↗
DOE OSTI2024

HSQC spectra of lignin isolated from poplar roots

Here we present a curated dataset of two-dimensional heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra of lignin isolated from roots of a greenhouse grown natural population of an energy crop poplar (Populus trichocarpa). Dormant cuttings of field-grown poplar were grown in 6-liter pots in a peat-based media containing bark, perlite, vermiculite, dolomite lime and a wetting agent in an environmentally controlled greenhouse. Temperatures were between 21 and 23 °C, with supplemental lighting to support a 16-h day length using 1000-watt high-pressure sodium lights in greenhouse. Once established, all plants were cut-back, allowed to regrow and harvested at the same time following an eight-month long growth period. Plants were harvested and the belowground roots were washed off soils, blotted, dried in an oven at 70 °C for 3 days, and Wiley milled (mesh size 20). The roots were Soxhlet-extracted with toluene/ethanol for 24 h to remove extractives. The extracted roots were ball-milled in a Retsch PM100 planetary ball mill using a porcelain jar with ceramic balls at 600 rpm for 2 h (in 5 min on and 5 min off cycles to avoid excessive sample heating). The ball-milled materials were then subjected to enzymatic hydrolysis for 48 h followed by centrifugation and washing with deionized water. The solid residue was extracted twice with 96% (v/v) 1,4-dioxane/water mixture at room temperature overnight. The extracts were combined, rotary evaporated, and freeze-dried to recover lignin. The dry lignin samples were dissolved in deuterated dimethyl sulfoxide (d6) and transferred into a 5 mm tube. 13C–1H HSQC experiments were performed in a Bruker Avance III HD 500 MHz NMR spectrometer operating at a frequency of 125.12 MHz for the 13C nucleus using a standard Bruker pulse sequence on a Prodigy platform cryoprobe. The NMR spectra were acquired under the following acquisition conditions: 220 ppm spectral width in F1 (13C) dimension with 256 data points and 12 ppm spectral width in F2 (1H) dimension with 1024 data points, a 90° pulse, a one bond C–H coupling constant of 145 Hz, a 1.0 s pulse delay, and 64 scans. Spectra were processed using the Bruker TopSpin software. Additional meta data is embedded in the raw spectra figures.

HSQC, lignin, poplar, roots, CBI↗
DOE OSTI2022

Silver Nanoparticles Functionalized Nanosilica Grown over Graphene Oxide for Enhancing Antibacterial Effect

The continuous growth of multidrug-resistant bacteria due to the overuse of antibiotics and antibacterial agents poses a threat to human health. Silver nanoparticles, silica-based materials, and graphene-based materials have become potential antibacterial candidates. In this study, we developed an effective method of enhancing the antibacterial property of graphene oxide (GO) by growing nanosilica (NS) of approximately 50 nm on the graphene oxide (GO) surface. The structures and compositions of the materials were characterized through powdered X-ray diffraction (P-XRD), transmission electron microscopy (TEM), scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM-EDS), ultraviolet–visible spectroscopy (UV–VIS), dynamic light scattering (DLS), Raman spectroscopy (RM), Fourier-transform infrared spectroscopy (FTIR), Brunauer–Emmet–Teller (BET) surface area, and pore size determination. The silver nanoparticles (AgNPs) with an average diameter of 26 nm were functionalized on the nanosilica (NS) surface. The composite contained approximately 3% of silver nanoparticles. The silver nanoparticles on nanosilica supported over graphene oxide (GO/NS/AgNPs) exhibited a 7-log reduction of Escherichia coli and a 5.2-log reduction of Bacillus subtilis within one hour of exposure. Both GO/NS and GO/NS/AgNPs exhibited substantial antimicrobial effects against E. coli and B. subtilis.

36 MATERIALS SCIENCE↗
NASA NTRS1988

Airborne and spaceborne lasers for terrestrial geophysical sensing; Proceedings of the Meeting, Los Angeles, CA, Jan. 14, 15, 1988

The present conference on airborne and spaceborne remote sensing laser applications discusses topics in atmospheric and geophysical sciences-related sensors, lidar and DIAL component and subsystem technologies, and coherent laser experiments and semiconductor laser technologies. Attention is given to airborne lidar measurement of aerosols, a ground-based injection-locked pulsed TEA laser for wind measurements, chemical/biological agent standoff detection methods, lidars for wind shear erosion, laser tuning to selected gas absorption lines in the atmosphere, the NASA lidar-in-space technology experiment, and the Laser Atmospheric Wind Sounder.

Allario, Frank↗
NASA NTRS1991

Future applications of artificial intelligence to Mission Control Centers

Future applications of artificial intelligence to Mission Control Centers are presented in the form of the viewgraphs. The following subject areas are covered: basic objectives of the NASA-wide AI program; inhouse research program; constraint-based scheduling; learning and performance improvement for scheduling; GEMPLAN multi-agent planner; planning, scheduling, and control; Bayesian learning; efficient learning algorithms; ICARUS (an integrated architecture for learning); design knowledge acquisition and retention; computer-integrated documentation; and some speculation on future applications.

Friedland, Peter↗
NASA NTRS1991

Processing for maximizing the level of crystallinity in linear aromatic polyimides

The process of the present invention includes first treating a polyamide acid (such as LARC-TPI polyamide acid) in an amide-containing solvent (such as N-methyl pyrrolidone) with an aprotic organic base (such as triethylamine), followed by dehydrating with an organic dehydrating agent (such as acetic anhydride). The level of crystallinity in the linear aromatic polyimide so produced is maximized without any degradation in the molecular weight thereof.

St.clair, Terry L.↗
NASA NTRS1994

A data analysis assistant

This paper discusses the use of a domain-independent planner, COLLAGE, as a software assistant to Earth scientists working with remotely-sensed and ground based data sets. The planner can be viewed as an advisory agent that helps scientists select appropriate data and creates a suitable plan for data-processing that meets stated scientific requirements.

Lansky, Amy L.↗
NASA NTRS2007

Intelligent Motion and Interaction Within Virtual Environments

What makes virtual actors and objects in virtual environments seem real? How can the illusion of their reality be supported? What sorts of training or user-interface applications benefit from realistic user-environment interactions? These are some of the central questions that designers of virtual environments face. To be sure simulation realism is not necessarily the major, or even a required goal, of a virtual environment intended to communicate specific information. But for some applications in entertainment, marketing, or aspects of vehicle simulation training, realism is essential. The following chapters will examine how a sense of truly interacting with dynamic, intelligent agents may arise in users of virtual environments. These chapters are based on presentations at the London conference on Intelligent Motion and Interaction within a Virtual Environments which was held at University College, London, U.K., 15-17 September 2003.

Ellis, Stephen R.↗
DOE OSTI2022

A Hybrid Reinforcement Learning-MPC Approach for Distribution System Critical Load Restoration

This paper proposes a hybrid control approach for distribution system critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while MPC models grid operations incorporating RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. We formulate the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The RL algorithm is trained offline using a historical forecast of renewable generation and load demand. The method is tested using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery. Case studies demonstrated that the proposed method outperforms other policies with static operating reserves.

distribution system↗
DOE OSTI2024

Planar slicing for nonextrusion AM processes

Extrusion-based AM processes, including material extrusion and directed energy deposition, construct objects by continuously depositing a relatively small amount of molten feedstock to a specific location. Nonextrusion AM processes, on the other hand, tend to form each layer by linearly or areally projecting either energy onto a vat of photocurable liquid or a binding agent into a bed of loose powder. Such systems vary significantly from extrusion-based AM processes but do share similarities. The general approach to path planning is the same, but nonextrusion processes typically favor the use of bitmap representations, instead of polygons, for pathing computation and do not use a g-code file to command the printer. In this chapter, a high-level discussion of these differences will be covered.

Macdonald, Eric↗