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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight methods is paramount for establishing an effective architecture for autonomous systems. A fundamental objective of the ATTRACTOR (Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability) project was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation environment for test and evaluation of autonomous systems. The Autonomous Entity Operations Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single- and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. Together AEON and BEAM enable sim-to-flight with minimal configuration changes. By using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the lab and in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.

Benjamin N Kelley↗
NASA NTRSDate not supplied

Synthetic Data Generation for 3D Mesh Prediction and Spatial Reasoning During Multi-Agent Robotic Missions

In-space assembly operations require accurate reasoning over the pose, location, and structural organization of both the autonomous agents and assembly materials. In a full six-degree-of-freedom space, an accurate understanding of the full three-dimensional structure of the object of interest greatly enriches information for pose estimation and collision planning. Current methods of predicting pose estimation require a priori understanding of the shape of the object. Additionally, visual information in the space environment is impacted by variations in contrast and illumination. Using synthetic data allows us to rapidly generate large datasets with in varying environments and lighting conditions.This work details the generation of synthetic data used to explore the use of a region-based convolutional neural networks to detect objects of interest and predict a voxel-based three-dimensional mesh in order to understand their full three-dimensional shape. This mesh provides useful spatial information during in-space assembly operations without requiring either the complexity of maintaining models over the progress of building an object or observations from multiple angles. The generated meshes are then compared to that of ground truth in order to measure its performance.

synthetic data↗
NASA NTRSDate not supplied

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight methods is paramount for establishing an effective architecture for autonomous systems. A fundamental objective of the ATTRACTOR (Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability) project was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation environment for test and evaluation of autonomous systems. The Autonomous Entity Operations Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single- and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. Together AEON and BEAM enable sim-to-flight with minimal configuration changes. By using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the lab and in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.

Benjamin N Kelley↗
NASA NTRSDate not supplied

Synthetic Data Generation for 3D Mesh Prediction and Spatial Reasoning During Multi-Agent Robotic Missions

In-space assembly operations require accurate reasoning over the pose, location, and structural organization of both the autonomous agents and assembly materials. In a full six-degree-of-freedom space, an accurate understanding of the full three-dimensional structure of the object of interest greatly enriches information for pose estimation and collision planning. Current methods of predicting pose estimation require a priori understanding of the shape of the object. Additionally, visual information in the space environment is impacted by variations in contrast and illumination. Using synthetic data allows us to rapidly generate large datasets with in varying environments and lighting conditions. This work details the generation of synthetic data used to explore the use of a region-based convolutional neural networks to detect objects of interest and predict a voxel-based three-dimensional mesh in order to understand their full three-dimensional shape. This mesh provides useful spatial information during in-space assembly operations without requiring either the complexity of maintaining models over the progress of building an object or observations from multiple angles. The generated meshes are then compared to that of ground truth in order to measure its performance.

James Ecker↗
NASA NTRS2017

CARACaS multi-agent maritime autonomy for unmanned surface vehicles in the Swarm II harbor patrol demonstration

This paper describes new autonomy technology that enabled a team of unmanned surface vehicles (USVs) to execute cooperative behaviors in the USV Swarm II harbor patrol demonstration and provides a description of autonomy performance in the event. The new developments extend the NASA Jet Propulsion Laboratory’s CARACaS (Control Architecture for Robotic Agent Command and Sensing) autonomy architecture, which pro- vides foundational software infrastructure, core executive functions, and several default robotic technology mod- ules. In Swarm II, CARACaS demonstrated higher levels of autonomy and more complex cooperation than previous on-water exercises, using full-sized vehicles and real-world sensing and communication. The core au- tonomous behaviors to support the harbor patrol scenario included Patrol, Track, Inspect, and Trail, providing the capability of finding all vessels entering the patrol area, keeping track of them, inspecting them to infer intent, and trailing suspect vessels. Significantly, CARACaS assumed responsibility for not only executing tasks safely and efficiently but also recognizing what tasks needed to be accomplished, given the current state of the world. Since the heterogeneous USV teams shared world model that evolved, such as due to (dis)appearance of vessels in the area or a change in health or availability of a USV, CARACaS replanned to generate and reallocate the new task list. Thus, human intervention was never required in the loop to task USVs during mission execution, though a supervisory role was supported in the autonomy system for mission monitoring and exception handling. Finally, CARACaS also ensured the USVs avoided hazards and obeyed the applicable rules of the road, using its local motion planning modules.

Sandoval, Michael↗
NASA NTRSDate not supplied

AMMPER: Agent-based Model for Microbial Populations Exposed to Radiation

Exposure of microbial populations to galactic cosmic radiation (GCR) in the deep-space radiation environment may lead to intracellular damage that compromises the ability of cells to repair and replicate. While simulation programs of deep-space radiation do exist, they focus primarily on single-cell damage, rather than population-wide effects. In this work, a new application and graphical user interface, Agent-Based Model for Microbial Populations Exposed to Radiation (AMMPER) is presented, which simulates the effects of proton-based GCR on Saccharomyces cerevisiae population growth. AMMPER consists of a 50x50x50 µm simulation space, analogous to an aqueous culture medium with non-limiting nutrient and pH buffering, in a microwell plate or microfluidic culture card. This model utilizes Relativistic Ion Tracks (RITRACKS) to create detailed track structures of the radiation traversals. AMMPER then calculates the radiation dose present at each cell, and subsequently determines the damage (chromosomal aberrations, oxidative stress, etc.) and resulting loss of cell viability from both primary and secondary radiative effects. Through implementing cell replication, repair, damage, and death, the effect of radiation exposure on the population growth can be determined. With AMMPER, long-duration effects of the deep space environment on entire populations can be determined and used to assess the feasibility of sustaining life in space.

Amrita Singh↗
NASA NTRS2022

Multi-Agent Control Approach to the Stability of Linear Deployable Systems

Collisions and undesired dynamic responses may occur during the expansion phase of deployable elements on a spacecraft. This problem is more pronounced in large and complex deployable elements where characterization of transient dynamics using testing and simulation can be challenging. This paper introduces a multi-agent control theory approach to address the problem of collisions and transient behavior in deployable lattice systems. We introduce the graph theoretic and relative error vector-based state-space structures to represent the geometry of a lattice-based deploy system. We show that under the assumption of almost-strict dissipativity, the closed-loop feedback gains of the relative error dynamics are the spring and damper constants in the structure. Moreover, we introduce the control perspective of shaping transient dynamics using eigenstructure assignment and balanced coordinate transformation.

Pablos, Juan L. de↗
NASA NTRSDate not supplied

Joint Communication Resource Allocation and Velocity Selection in Urban Air Mobility via Multi-agent Reinforcement Learning

With traffic congestion problems becoming more severe in urban areas, the National Aeronautics and Space Administration promotes the Urban Air Mobility (UAM) concept, which envisages a safe and efficient air transportation system. However, the increased communication demands in UAM can exacerbate the spectrum scarcity. Therefore, a new communication resource allocation solution is necessary. In this paper, we focus on uplink UAM communications, where multiple aerial vehicles (AV) perform cargo/passenger delivery tasks. With predefined flight paths, AVs make decisions on communication resource allocation and velocity selection to complete their missions under safety constraints. Accordingly, we formulate a joint optimization problem to minimize the weighted sum of the total travel time and communication outage time. We first model the optimization problem as a Markov game and propose a multi-agent reinforcement learning based solution. Simulation results corroborate the effectiveness of the proposed solution.

Ruixuan Han↗
DOE OSTI2011

CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Poisoning of a silica supported cobalt catalyst due to the presence of sulfur impurities in syngas during Fischer-Tropsch synthesis: Effect of chelating agent

Sulfur compounds that are generally found in syngas derived from coal and biomass are a poison to Fischer-Tropsch (FT) catalysts. The presence of sulfur impurities in the ppm range can limit the life of a FT catalyst to a few hours or a few days. In this study, FT synthesis was carried out in a fixed-bed reactor at 230 °C, 20 bar, and 13,500 Ncm3/h/gcat for 72 h using syngas with H2/CO = 2.0. Cobalt-based catalysts were subjected to poisoning by 10 and 50 ppm sulfur in the syngas. The performance of FT catalyst was compared in context of syngas conversion, product selectivities and yields, during the poisoning as well as post-poisoning stages. At both the impurity concentrations, the sulfur was noted to cause permanent loss in the activity, possibly by adsorbing irreversibly on the surface. The sulfur poison affects the hydrogenation and the chain-propagation ability of the catalysts, and shifts the product selectivity towards short-chain hydrocarbons with higher percentages of olefins. Additional diffusion limitations caused due to sulfur poisoning are thought to alter the product selectivity. The shifts in product selectivities suggest that the sulfur decreases the ability of the catalyst to form C-C bonds to produce longer-chain hydrocarbons. The selective blocking of sulfur is thought to affect the hydrogenation ability on the catalyst, resulting in more olefins in the product after sulfur poisoning. The sulfur poisoning on the cobalt catalyst is expected to cause an increase in the number of sites responsible for WGS or to influence the Boudouard reaction, resulting in a higher CO2 selectivity. Both the sites responsible for CO adsorptions as well as the sites for chain growth are poisoned during the poisoning. Additionally, the performance of a base-case cobalt catalyst is compared with that of catalysts modified by chelating agents (CAs). The superior performance of CA-modified catalysts during sulfur poisoning is attributed to the presence of smaller crystallite sizes and higher dispersions of cobalt on the support. Finally, the sulfur deactivation data is modeled by a simple kinetic expression to determine the deactivation constant, deactivation rates and half-life of the FT catalyst.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Anti-cancer agents based on 6-trifluoromethoxybenzimidazole derivatives and method of making

The present disclosure relates to novel compounds having the structural Formulas (1a,1b), stereoisomers, tautomers, racemics, prodrugs, metabolites thereof, or pharmaceutically acceptable salt and/or solvate thereof as chemotherapy agents for treating of cancer, particularly androgen-independent prostate cancer. The disclosure also relates to methods for preparing said compounds, and to pharmaceutical compositions comprising said compounds.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Anti-cancer agents based on 4-(hetero)Ary1-1,2,5-oxadiazol-3-yl Amino derivatives and a method of making

The present disclosure relates to novel compounds that can be used as anti-cancer agents in the prostate cancer therapy. ##STR00001## In particular, the invention relates N-substituted derivatives of 4-(hetero)aryl-1,2,5-oxadiazol-3-yl amines having the structural Formula (I) and (II), stereoisomers, tautomers, racemics, prodrugs, metabolites thereof, or pharmaceutically acceptable salt and/or solvate thereof. Meaning of R1 and R2 in the Formula (I) and (II) are defined in claim 1. The invention also relates to methods for preparing said compounds, and to pharmaceutical compositions comprising said compounds.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Anti-cancer agents based on N-acyl-2, 3-dihydro-1H-pyrrolo[2,3-b] quinoline derivatives and a method of making

The present disclosure relates to novel compounds that can be used as anti-cancer agents in the prostate cancer therapy. In particular, the invention relates to N-acyl derivatives of 2,3-dihydro-1H-pyrrolo[2,3-b]quinolines having the structural Formula (I), ##STR00001## stereoisomers, tautomers, racemics, prodrugs, metabolites thereof, or pharmaceutically acceptable salt and/or solvate thereof. The meaning of R1 is independently selected from H; C1-C6 Alkyl, cyclo-Alkyl or iso-Alkyl substituents; R2 is selected from C1-C6 Alkyl, cyclo-Alkyl or iso-Alkyl; substituted or non-substituted, fused or non-fused to substituted or non-substituted aromatic ring, aryl or heteroaryl groups. The invention also relates to methods for preparing said compounds, and to pharmaceutical compositions comprising said compounds.

59 BASIC BIOLOGICAL SCIENCES↗