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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Freeze-Thaw Cycling as a Chemical Weathering Agent on a Cold and Icy Mars

Liquid water was abundant on early Mars, but whether the climate was warm and wet or cold and icy with punctuated periods of melting is still poorly understood. Modern climate models for Mars tend to predict a colder, icier early climate than previously imagined. In addition, ice and glaciation have been major geologic agents throughout the later Hesperian and Amazonian eras. One process that can act in such climates is repeated freezing and thawing of water on the surface and in the subsurface, and is significant because it can occur anywhere with an active layer and could have persisted for a time after liquid water was no longer stable on Mars’ surface. As freeze-thaw is the dominant mechanical weathering process in most glacial/periglacial terrains, it was likely a significant geomorphologic driver at local to regional scales during past climates, and would potentially have been most active when day-average surface temperatures exceeded 0 °C for part of the year. Indeed, freeze-thaw involving liquid water in the Amazonian is evidenced by abundant geomorphic features including polygonal ground and solifluction lobes requiring seasonal thawing. In addition to physical modification, freezing can drive solutions towards supersaturation and force dissolved solutes out as precipitates. In Mars-like terrains, dissolved solutes are typically dominated by silica. In polar regions on Earth, freeze-thaw cycles have been shown to promote deposition of silica, and freeze-thaw experiments on synthetic solutions found stable amorphous silica that built up over multiple cycles. Freeze-thaw may therefore be an important but overlooked chemical weathering process on Mars. However, our ability to assess its impact on alteration of martian terrains is majorly limited by the current lack of understanding of the alteration phases produced (and formation rates) under controlled freeze-thaw weathering of Mars-relevant materials. To address this knowledge gap, we report results from (1) freeze-thaw weathering products found at a glacial Mars analog site at the Three Sisters, Oregon, and (2) new controlled freeze-thaw experiments on basaltic material.

Scudder, N. A.↗
NASA NTRS2020

Optimal Multi-Agent Search and Rescue Using Potential Field Theory

This paper presents an algorithm for efficient search and rescue using a multi-agent system of vehicles. The algorithm uses an artificial potential field combined with a time-varying reward function for visiting various points within the search area. The reward function is used to weight the attractiveness of these points in the potential field, and collision avoidance terms are used to repel vehicles from each other, which has the additional effect of reducing duplication of searching efforts. The algorithm generates velocity commands in real-time based on communication with the other vehicles. This framework allows vehicles to react in a dynamic environment, which is a significant advantage to simply following a-priori defined trajectories. Simulation results are presented to demonstrate the ability of the algorithm to cover the search area effectively. The algorithm is also compared to an exhaustive lawn-mower search pattern. This comparison is done via a Monte Carlo simulation with randomized target initial conditions and trajectories. The time to find the target improved by 16 and 30% in the mean and median, respectively. Additionally, this paper presents a method for analyzing the upper bound for time to find a target under the potential field guidance algorithm assuming a radially expanding search area.

John R Cooper↗
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 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↗
DOE OSTI2013

Engineered plant biomass particles coated with bioactive agents

Plant biomass particles coated with a bioactive agent such as a fertilizer or pesticide, characterized by a length dimension (L) aligned substantially parallel to a grain direction and defining a substantially uniform distance along the grain, a width dimension (W) normal to L and aligned cross grain, and a height dimension (H) normal to W and L. In particular, the L.times.H dimensions define a pair of substantially parallel side surfaces characterized by substantially intact longitudinally arrayed fibers, the W.times.H dimensions define a pair of substantially parallel end surfaces characterized by crosscut fibers and end checking between fibers, and the L.times.W dimensions define a pair of substantially parallel top and bottom surfaces.

09 BIOMASS FUELS↗
DOE OSTI2014

Engineered plant biomass particles coated with biological agents

Plant biomass particles coated with a biological agent such as a bacterium or seed, characterized by a length dimension (L) aligned substantially parallel to a grain direction and defining a substantially uniform distance along the grain, a width dimension (W) normal to L and aligned cross grain, and a height dimension (H) normal to W and L. In particular, the L.times.H dimensions define a pair of substantially parallel side surfaces characterized by substantially intact longitudinally arrayed fibers, the W.times.H dimensions define a pair of substantially parallel end surfaces characterized by crosscut fibers and end checking between fibers, and the L.times.W dimensions define a pair of substantially parallel top and bottom surfaces.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Stabilization of green bodies via sacrificial gelling agent during electrophoretic deposition

In one embodiment, a method for electrophoretic deposition of a three-dimensionally patterned green body includes suspending a first material in a gelling agent above a patterned electrode of an electrophoretic deposition (EPD) chamber, and gelling the suspension while applying a first electric field to the suspension to cause desired patterning of the first material in a resulting gelation. In another embodiment, a ceramic, metal, or cermet includes a plurality of layers, wherein each layer includes a gradient in composition, microstructure, and/or density in an x-y plane oriented parallel to a plane of deposition of the plurality of layers along a predetermined distance in a z-direction perpendicular to the plane of deposition.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Molecular predictors of therapeutic response to specific anti-cancer agents

Herein is described the use of a collection of 50 breast cancer cell lines to match responses to 77 conventional and experimental therapeutic agents with transcriptional, proteomic and genomic subtypes found in primary tumors. Almost all compounds produced strong differential responses across the cell lines produced responses that were associated with transcriptional and proteomic subtypes and produced responses that were associated with recurrent genome copy number abnormalities. These associations can now be incorporated into clinical trials that test subtype markers and clinical responses simultaneously.

59 BASIC BIOLOGICAL SCIENCES↗