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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Evolutionary Agent-Based Simulation of the Introduction of New Technologies in Air Traffic Management

Accurate simulation of the effects of integrating new technologies into a complex system is critical to the modernization of our antiquated air traffic system, where there exist many layers of interacting procedures, controls, and automation all designed to cooperate with human operators. Additions of even simple new technologies may result in unexpected emergent behavior due to complex human/ machine interactions. One approach is to create high-fidelity human models coming from the field of human factors that can simulate a rich set of behaviors. However, such models are difficult to produce, especially to show unexpected emergent behavior coming from many human operators interacting simultaneously within a complex system. Instead of engineering complex human models, we directly model the emergent behavior by evolving goal directed agents, representing human users. Using evolution we can predict how the agent representing the human user reacts given his/her goals. In this paradigm, each autonomous agent in a system pursues individual goals, and the behavior of the system emerges from the interactions, foreseen or unforeseen, between the agents/actors. We show that this method reflects the integration of new technologies in a historical case, and apply the same methodology for a possible future technology.

Simulation↗
NASA NTRS2014

Agent Based Modeling of Air Carrier Behavior for Evaluation of Technology Equipage and Adoption

As part of ongoing research, the National Aeronautics and Space Administration (NASA) and LMI developed a research framework to assist policymakers in identifying impacts on the U.S. air transportation system (ATS) of potential policies and technology related to the implementation of the Next Generation Air Transportation System (NextGen). This framework, called the Air Transportation System Evolutionary Simulation (ATS-EVOS), integrates multiple models into a single process flow to best simulate responses by U.S. commercial airlines and other ATS stakeholders to NextGen-related policies, and in turn, how those responses impact the ATS. Development of this framework required NASA and LMI to create an agent-based model of airline and passenger behavior. This Airline Evolutionary Simulation (AIRLINE-EVOS) models airline decisions about tactical airfare and schedule adjustments, and strategic decisions related to fleet assignments, market prices, and equipage. AIRLINE-EVOS models its own heterogeneous population of passenger agents that interact with airlines; this interaction allows the model to simulate the cycle of action-reaction as airlines compete with each other and engage passengers. We validated a baseline configuration of AIRLINE-EVOS against Airline Origin and Destination Survey (DB1B) data and subject matter expert opinion, and we verified the ATS-EVOS framework and agent behavior logic through scenario-based experiments. These experiments demonstrated AIRLINE-EVOS's capabilities in responding to an input price shock in fuel prices, and to equipage challenges in a series of analyses based on potential incentive policies for best equipped best served, optimal-wind routing, and traffic management initiative exemption concepts..

Horio, Brant M.↗
NASA NTRS2015

Collaborating with Autonomous Agents

With the anticipated increase of small unmanned aircraft systems (sUAS) entering into the National Airspace System, it is highly likely that vehicle operators will be teaming with fleets of small autonomous vehicles. The small vehicles may consist of sUAS, which are 55 pounds or less that typically will y at altitudes 400 feet and below, and small ground vehicles typically operating in buildings or defined small campuses. Typically, the vehicle operators are not concerned with manual control of the vehicle; instead they are concerned with the overall mission. In order for this vision of high-level mission operators working with fleets of vehicles to come to fruition, many human factors related challenges must be investigated and solved. First, the interface between the human operator and the autonomous agent must be at a level that the operator needs and the agents can understand. This paper details the natural language human factors e orts that NASA Langley's Autonomy Incubator is focusing on. In particular these e orts focus on allowing the operator to interact with the system using speech and gestures rather than a mouse and keyboard. With this ability of the system to understand both speech and gestures, operators not familiar with the vehicle dynamics will be able to easily plan, initiate, and change missions using a language familiar to them rather than having to learn and converse in the vehicle's language. This will foster better teaming between the operator and the autonomous agent which will help lower workload, increase situation awareness, and improve performance of the system as a whole.

Trujillo, Anna C.↗
NASA NTRS2017

Formal Assurance for Cognitive Architecture Based Autonomous Agent

Autonomous systems are designed and deployed in different modeling paradigms. These environments focus on specific concepts in designing the system. We focus our effort in the use of cognitive architectures to design autonomous agents to collaborate with humans to accomplish tasks in a mission. Our research focuses on introducing formal assurance methods to verify the behavior of agents designed in Soar, by translating the agent to the formal verification environment Uppaal.

Bhattacharyya, Siddhartha↗
NASA NTRS2018

Multistage Delivery of Active Agents

Multistage delivery vehicles are disclosed which include a first stage particle and a second stage particle. The first stage particle is a micro or nanoparticle that contains the second stage particle. The second stage particle includes an active agent, such as a therapeutic agent or an imaging agent. The multistage delivery vehicle allows sequential overcoming or bypassing of biological barriers. The multistage delivery vehicle is administered as a part of a composition that includes a plurality of the vehicles. Methods of making the multistage delivery vehicles are also provided.

Ferrari, Mauro↗
NASA NTRS2018

The Mid-IR Spectral Effects of Darkening Agents and Porosity on the Silicate Surface Features of Airless Bodies

We systematically measured the mid-IR spectra of different mixtures of three silicates (antigorite, lizardite, and pure silica) with varying effective porosities and amounts of darkening agent (iron oxide and carbon). These spectra have broad implications for interpretation of current and future mission data for airless bodies, as well as for testing the capabilities of new instruments. Serpentines, such as antigorite and lizardite, are common to airless surfaces, and their mid-IR spectra in the presence of darkening agents and different surface porosities would be typical for those measured by spacecraft. Silica has only been measured in the plumes of Enceladus and presents exciting possibilities for other Saturn-system surfaces due to long range transport of E-ring material. Results show that the addition of the IR-transparent salt, KBr, to simulate surface porosity affected silicate spectra in ways that were not predictable from linear mixing models. The strengthening of silicate bands with increasing pore space, even when only trace amounts of KBr were added, indicates that spectral features of porous surfaces are more detectable in the mid-IR. Combining iron oxide with the pure silicates seemed to flatten most of the silicate features, but strengthened the reststrahlen band of the silica. Incorporating carbon with the silicates weakened all silicate features, but the silica bands were more resistant to being diminished, indicating silica may be more detectable in the mid-IR than the serpentines. We show how incorporating darkening agents and porosity provides a more complete explanation of the mid-IR spectral features previously reported on worlds such as Iapetus.

Young, Cindy L.↗
NASA NTRS2020

Multi-Agent Motion Planning using Deep Learning for Space Applications

State-of-the-art motion planners cannot scale to a large number of systems. Motion planning for multiple agents is an NP (non-deterministic polynomial-time) hard problem, so the computation time increases exponentially with each addition of agents. This computational demand is a major stumbling block to the motion planner's application to future NASA missions involving the swarm of space vehicles. We applied a deep neural network to transform computationally demanding mathematical motion planning problems into deep learning-based numerical problems. We showed optimal motion trajectories can be accurately replicated using deep learning-based numerical models in several 2D and 3D systems with multiple agents. The deep learning-based numerical model demonstrates superior computational efficiency with plans generated 1000 times faster than the mathematical model counterpart.

Madani, Ramtin↗
NASA NTRSDate not supplied

Intelligent Change Detection System: Autonomous Intelligent Machine Agent Model Development

NASA’s significant role in facilitating the harmonious integration of unmanned aircraft systems (UAS), with other aerial vehicles operating in the National Airspace System (NAS), has revealed a need for more advanced technological tools than are being utilized currently. This technology would lend itself to significantly assisting Direct-Action Aviation Personnel (DAAP) with the ingress and egress of UAS operations within the NAS. Providing research findings that would reduce technical barriers, associated with UAS-NAS integration, has been a persistent effort by both NASA and the FAA. One such research effort, pursued by NASA’s Transformative Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) project, is the development of an autonomous intelligent machine (AIM) agent that would aid DAAP functioning as implemented in remote ground control stations (RGCS). This evolution of the “human-machine” symbiosis, within the aviation environment, is necessary for many reasons. For example, there are projections of large increases to the 864,000 registered UAS and 45,000 aviation operations taking place in the NAS each day. With a data output range from 1 to 20 terabytes per flight or each aerial vehicle, which is projected to have proportional rate increase to that of registered UASs. It is evident, that due to the projected increase of UASs and their generated data, the human-agent’s data managing capabilities will be quickly overwhelmed by the enormous amounts of data emanating in the NAS. The research efforts presented in this paper puts forward results from the development, assessment, and verification of a previously conceptualized AIM-Agent that combats actionable-data (information) errors resulting from the visual perception phenomenon known as “change blindness” (CB). CB has been identified as one of the main culprits of information erroring encountered within the ground control station operator (GCSO) community.

Change Blindness↗
DOE OSTI2014

Methods, microfluidic devices, and systems for detection of an active enzymatic agent

Embodiments of the present invention provide methods, microfluidic devices, and systems for the detection of an active target agent in a fluid sample. A substrate molecule is used that contains a sequence which may cleave in the presence of an active target agent. A SNAP25 sequence is described, for example, that may be cleaved in the presence of Botulinum Neurotoxin. The substrate molecule includes a reporter moiety. The substrate molecule is exposed to the sample, and resulting reaction products separated using electrophoretic separation. The elution time of the reporter moiety may be utilized to identify the presence or absence of the active target agent.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Methods and kits for predicting a response to an erythropoietic agent

Methods for predicting a response to an erythropoietic agent in a subject include providing a biological sample from the subject, and determining an amount in the sample of at least one peptide selected from the group consisting of SEQ ID NOS: 1-17. If there is a measurable difference in the amount of the at least one peptide in the sample, when compared to a control level of the same peptide, the subject is then predicted to have a good response or a poor response to the erythropoietic agent. Kits for predicting a response to an erythropoietic agent are further provided and include one or more antibodies, or fragments thereof, that specifically recognize a peptide of SEQ ID NOS: 1-17.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Method for removing strongly adsorbed surfactants and capping agents from metal to facilitate their catalytic applications

A method of synthesizing activated electrocatalyst, preferably having a morphology of a nanostructure, is disclosed. The method includes safely and efficiently removing surfactants and capping agents from the surface of the metal structures. With regard to metal nanoparticles, the method includes synthesis of nanoparticle(s) in polar or non-polar solution with surfactants or capping agents and subsequent activation by CO-adsorption-induced surfactant/capping agent desorption and electrochemical oxidation. The method produces activated macroparticle or nanoparticle electrocatalysts without damaging the surface of the electrocatalyst that includes breaking, increasing particle thickness or increasing the number of low coordination sites.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Metal organic frameworks for the catalytic detoxification of chemical warfare nerve agents

A method of using a metal organic framework (MOF) comprising a metal ion and an at least bidendate organic ligand to catalytically detoxify chemical warfare nerve agents including exposing the metal-organic-framework (MOF) to the chemical warfare nerve agent and catalytically decomposing the nerve agent with the MOF.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

System and method for regeneration and recirculation of a reducing agent using highly exothermic reactions induced by mixed industrial slags

Embodiments relate to systems and methods for regenerating and recirculating a CO, H.sub.2 or combinations thereof utilized for metal oxide reduction in a reduction furnace. The reduction furnace receives the reducing agent, reduces the metal oxide, and generates an exhaust of the oxidized product. The oxidized product is transferred to a mixing vessel, where the oxidized product, a calcium oxide, and a vanadium oxide interact to regenerate the reducing agent from the oxidized product. The regenerated reducing agent is transferred back to the reduction furnace for continued metal oxide reductions.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Object discrimination based on a swarm of agents

A configuration system for identifying a target configuration of agents for acquiring data is provided. In some embodiments, the configuration system generates sample configurations, each of which has a location within the space for each agent. The configuration system selects as the target configuration a sample configuration that is suitable to acquire data. The configuration system selects the target configuration by, for at least one or more sample configurations, directing that the agents assume the sample configuration and then acquire data when in the sample configuration. The configuration system then stores, for each sample configuration, an indication of suitability for acquiring data based on the sample configuration. The configuration system selects a sample configuration that is deemed to be suitable as the target configuration.

Beer, N. Reginald↗
DOE OSTI2021

Object discrimination based on a swarm of agents

A configuration system for identifying a target configuration of agents for acquiring data is provided. In some embodiments, the configuration system generates sample configurations, each of which has a location within the space for each agent. The configuration system selects as the target configuration a sample configuration that is suitable to acquire data. The configuration system selects the target configuration by, for at least one or more sample configurations, directing that the agents assume the sample configuration and then acquire data when in the sample configuration. The configuration system then stores, for each sample configuration, an indication of suitability for acquiring data based on the sample configuration. The configuration system selects a sample configuration that is deemed to be suitable as the target configuration.

Beer, Neil Reginald↗
DOE OSTI2021

Processing of perovskite films using inks with complexing agents

A method can comprise providing an ink comprising reactants, a complexing agent, and a solvent, depositing the ink onto a substrate to form a wet film, drying the wet film to form a precursor layer, and annealing the precursor layer to form a perovskite film. The reactants can comprise a first and a second cation, a first metal, and a first and a second anion, wherein the first and second cations are different from each other, and the first and second anions are different from each other. The complexing agent can comprise a heterocyclic donor material. The perovskite film can comprise a mixed-cation mixed-halide perovskite material, and less than 5% by mass of the complexing agent. The perovskite film can also be formed using a one-step process.

Bailie, Colin David↗
DOE OSTI2021

Method and composition for targeted delivery of therapeutic agents

Functionalized single walled or multi-walled carbon nanotubes (f-CNTs) can be delivered into mammals to targeted organs, such as the kidney and the liver. These f-CNTs may be non-covalently linked or covalently linked to therapeutic agents. In particular, the application delivers carbon nanotube-therapeutic agent conjugates to a target organ, thereby preventing or reducing damages to the organ caused by other agents or procedure.

McDevitt, Michael R.↗