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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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NASA NTRS2001

Adjustable Autonomy Testbed

The Adjustable Autonomy Testbed (AAT) is a simulation-based testbed located in the Intelligent Systems Laboratory in the Automation, Robotics and Simulation Division at NASA Johnson Space Center. The purpose of the testbed is to support evaluation and validation of prototypes of adjustable autonomous agent software for control and fault management for complex systems. The AA T project has developed prototype adjustable autonomous agent software and human interfaces for cooperative fault management. This software builds on current autonomous agent technology by altering the architecture, components and interfaces for effective teamwork between autonomous systems and human experts. Autonomous agents include a planner, flexible executive, low level control and deductive model-based fault isolation. Adjustable autonomy is intended to increase the flexibility and effectiveness of fault management with an autonomous system. The test domain for this work is control of advanced life support systems for habitats for planetary exploration. The CONFIG hybrid discrete event simulation environment provides flexible and dynamically reconfigurable models of the behavior of components and fluids in the life support systems. Both discrete event and continuous (discrete time) simulation are supported, and flows and pressures are computed globally. This provides fast dynamic simulations of interacting hardware systems in closed loops that can be reconfigured during operations scenarios, producing complex cascading effects of operations and failures. Current object-oriented model libraries support modeling of fluid systems, and models have been developed of physico-chemical and biological subsystems for processing advanced life support gases. In FY01, water recovery system models will be developed.

Malin, Jane T.↗
NASA NTRS2021

Collision Free Dynamic Stability of Formations Using Projection Based Estimators

Transient instability is a phenomenon where inter- agent collisions can occur in dynamically stable formations of autonomous agents. Therefore, the necessity to manage and mitigate transient instabilities is essential for successfully deploying formation structures. This paper develops a novel control architecture that augments the baseline formation maintenance controller to mitigate transient instabilities. At its heart, the proposed architecture consists of a projection operator based estimator disguised as a reference model that generates collision-free trajectories for the agents to follow. This paper’s main theoretical result shows that the proposed control architecture can simultaneously mitigate transient instabilities and guarantee asymptotic convergence of the formation dynamics. Also, an illustrative example demonstrates the theoretical developments presented in this paper.

Bayard, David S.↗
NASA NTRS2004

An Agent-Based Interface to Terrestrial Ecological Forecasting

This paper describes a flexible agent-based ecological forecasting system that combines multiple distributed data sources and models to provide near-real-time answers to questions about the state of the Earth system We build on novel techniques in automated constraint-based planning and natural language interfaces to automatically generate data products based on descriptions of the desired data products.

Golden, Keith↗
NASA NTRS1990

Pharmacokinetics and Pharmacodynamics in Space

The Pharmacokinetics and Pharmacodynamics Panel met on 29-30 Aug. 1988 at the Lunar and Planetary Institute in Houston, Texas to discuss pharmacokinetic and pharmacodynamic implications of space flight and make recommendations for operational and research strategies. Based on the knowledge available on the physiological changes that occur during space flight, the dependence of pharmacokinetics on physiological factors, and the therapeutic requirements for future space missions, the panel made several recommendations for research. It was suggested that using medications available with a large (wide) therapeutic window will avoid unforeseen therapeutic consequences during flight. The sequence for conducting research was outlined as follows: (1) identify ground-based simulation models (e.g., antiorthostatic bed rest) for conducting pharmacokinetic and pharmacodynamic research; (2) estimate parametric changes in these models using pharmacologic agents that have different pharmacokinetic characteristics and a narrow therapeutic index; (3) verify these findings during flight; and (4) develop and identify appropriate and effective drug delivery systems, dosage forms, and regimens. The panel recommended gaining a thorough understanding of the pharmacokinetic deviations of medications that have a narrow therapeutic index (e.g. cardiovascular drugs and sedative hypnotics) in order to ensure safe and effective treatment during flight with these agents. It was also suggested that basic information on physiological factors such as organ blood flow, protein composition and binding, tissue distribution, and metabolism by hepatic enzymes must be accumulated by conducting ground-based animal and human studies using models of weightlessness. This information will be useful to construct and identify physiologically based pharmacokinetic models that can provide valuable information on the pharmacodynamic consequences of space flight and aid in identifying appropriate therapeutic regimens.

Putcha, Lakshmi↗
NASA NTRS2004

Verifying Multi-Agent Systems via Unbounded Model Checking

We present an approach to the problem of verification of epistemic properties in multi-agent systems by means of symbolic model checking. In particular, it is shown how to extend the technique of unbounded model checking from a purely temporal setting to a temporal-epistemic one. In order to achieve this, we base our discussion on interpreted systems semantics, a popular semantics used in multi-agent systems literature. We give details of the technique and show how it can be applied to the well known train, gate and controller problem. Keywords: model checking, unbounded model checking, multi-agent systems

Kacprzak, M.↗
NASA NTRS2020

Detection and Mitigation of Transient Instabilities in Multi-Agent Systems and Swarms

We first introduce the novel concept of transient instabilities in multi-agent systems and swarms, i.e., a small disturbance leads to increasing-amplitude oscillations throughout the swarm, which results in a large number of inter-agent collisions. This instability is dominant in the transient phase of the system and it does not appear in the steady-state behavior of the system, as each agent uses Lyapunov-stable feedback control laws. We present a rigorous definition of transient instability in swarms, and discuss its key properties. We also present a sufficient condition to check if a swarm will be transient stable. We study the behaviour of different control laws under this condition. We also show how transient instability phenomenon could impact the dynamics of deployable structures. Next, we present a novel control architecture that augments the baseline formation maintenance controller to mitigate transient instabilities. At its heart, the proposed architecture consists of a projection operator based estimator disguised as a reference model that generates collision-free trajectories for the agents to follow. We present numerical simulation results to demonstrate the effectiveness of our proposed approaches.

Quadrelli, Marco B.↗
NASA NTRS2013

Unified Simulation and Analysis Framework for Deep Space Navigation Design

As the technology that enables advanced deep space autonomous navigation continues to develop and the requirements for such capability continues to grow, there is a clear need for a modular expandable simulation framework. This tool's purpose is to address multiple measurement and information sources in order to capture system capability. This is needed to analyze the capability of competing navigation systems as well as to develop system requirements, in order to determine its effect on the sizing of the integrated vehicle. The development for such a framework is built upon Model-Based Systems Engineering techniques to capture the architecture of the navigation system and possible state measurements and observations to feed into the simulation implementation structure. These models also allow a common environment for the capture of an increasingly complex operational architecture, involving multiple spacecraft, ground stations, and communication networks. In order to address these architectural developments, a framework of agent-based modules is implemented to capture the independent operations of individual spacecraft as well as the network interactions amongst spacecraft. This paper describes the development of this framework, and the modeling processes used to capture a deep space navigation system. Additionally, a sample implementation describing a concept of network-based navigation utilizing digitally transmitted data packets is described in detail. This developed package shows the capability of the modeling framework, including its modularity, analysis capabilities, and its unification back to the overall system requirements and definition.

Anzalone, Evan↗
NASA NTRS1997

Collaborating Fuzzy Reinforcement Learning Agents

Earlier, we introduced GARIC-Q, a new method for doing incremental Dynamic Programming using a society of intelligent agents which are controlled at the top level by Fuzzy Relearning and at the local level, each agent learns and operates based on ANTARCTIC, a technique for fuzzy reinforcement learning. In this paper, we show that it is possible for these agents to compete in order to affect the selected control policy but at the same time, they can collaborate while investigating the state space. In this model, the evaluator or the critic learns by observing all the agents behaviors but the control policy changes only based on the behavior of the winning agent also known as the super agent.

Berenji, Hamid R.↗
NASA NTRS1991

A CLIPS/X-window interface

The design and implementation of an interface between the C Language Integrated Production System (CLIPS) expert system development environment and the graphic user interface development tools of the X-Window system are described. The underlying basis of the CLIPS/X-Window is a client-server model in which multiple clients can attach to a single server that interprets, executes, and returns operation results, in response to client action requests. Implemented in an AIX (UNIX) operating system environment, the interface has been successfully applied in the development of graphics interfaces for production rule cooperating agents in a knowledge-based computer aided design (CAD) system. Initial findings suggest that the client-server model is particularly well suited to a distributed parallel processing operational mode in a networked workstation environment.

Pohl, Kym Jason↗
NASA NTRS1989

A logical model of cooperating rule-based systems

A model is developed to assist in the planning, specification, development, and verification of space information systems involving distributed rule-based systems. The model is based on an analysis of possible uses of rule-based systems in control centers. This analysis is summarized as a data-flow model for a hypothetical intelligent control center. From this data-flow model, the logical model of cooperating rule-based systems is extracted. This model consists of four layers of increasing capability: (1) communicating agents, (2) belief-sharing knowledge sources, (3) goal-sharing interest areas, and (4) task-sharing job roles.

Bailin, Sidney C.↗
NASA NTRS2022

Contribution of Spicules to Solar Coronal Emission

Recent high-resolution imaging and spectroscopic observations have generated renewed interest in spicules' role in explaining the hot corona. Some studies suggest that some spicules, often classified as type II, may provide significant mass and energy to the corona. Here we use numerical simulations to investigate whether such spicules can produce the observed coronal emission without any additional coronal heating agent. Model spicules consisting of a cold body and hot tip are injected into the base of a warm (0.5 MK) equilibrium loop with different tip temperatures and injection velocities. Both piston- and pressure-driven shocks are produced. We find that the hot tip cools rapidly and disappears from coronal emission lines such as Fe xii 195 and Fe xiv 274. Prolonged hot emission is produced by preexisting loop material heated by the shock and by thermal conduction from the shock. However, the shapes and Doppler shifts of synthetic line profiles show significant discrepancies with observations. Furthermore, spatially and temporally averaged intensities are extremely low, suggesting that if the observed intensities from the quiet Sun and active regions were solely due to type II spicules, one to several orders of magnitude more spicules would be required than have been reported in the literature. This conclusion applies strictly to the ejected spicular material. We make no claims about emissions connected with waves or coronal currents that may be generated during the ejection process and heat the surrounding area.

Shanwlee Sow Mondal↗
NASA NTRS2010

Programs Model the Future of Air Traffic Management

Through Small Business Innovation Research (SBIR) contracts with Ames Research Center, Intelligent Automation Inc., based in Rockville, Maryland, advanced specialized software the company had begun developing with U.S. Department of Defense funding. The agent-based infrastructure now allows NASA's Airspace Concept Evaluation System to explore ways of improving the utilization of the National Airspace System (NAS), providing flexible modeling of every part of the NAS down to individual planes, airports, control centers, and even weather. The software has been licensed to a number of aerospace and robotics customers, and has even been used to model the behavior of crowds.

Source record↗
NASA NTRS2022

Neurosymbolic Hybrid Approach to Driver Collision Warning

There are two main algorithmic approaches to autonomous driving systems: (1) An end-to-end system in which a single deep neural network learns to map sensory input directly into appropriate warning and driving responses. (2) A mediated hybrid recognition system in which a system is created by combining independent modules that detect each semantic feature. While some researchers believe that deep learning can solve any problem, others believe that a more engineered and symbolic approach is needed to cope with complex environments with less data. Deep learning alone has achieved state-of-the-art results in many areas, from complex gameplay to predicting protein structures. In particular, in image classification and recognition, deep learning models have achieved accuracies as high as humans. But sometimes it can be very difficult to debug if the deep learning model doesn't work. Deep learning models can be vulnerable and are very sensitive to changes in data distribution. Generalization can be problematic. It's usually hard to prove why it works or doesn't. Deep learning models can also be vulnerable to adversarial attacks. Here, we combine deep learning-based object recognition and tracking with an adaptive neurosymbolic network agent, called the Non-Axiomatic Reasoning System (NARS), that can adapt to its environment by building concepts based on perceptual sequences. We achieved an improved intersection-over-union (IOU) object recognition performance of 0.65 in the adaptive retraining model compared to IOU 0.31 in the COCO data pre-trained model. We improved the object detection limits using RADAR sensors in a simulated environment, and demonstrated the weaving car detection capability by combining deep learning-based object detection and tracking with a neurosymbolic model.

Wang, Pei↗
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↗
NASA NTRS2010

Modeling Social Influence via Combined Centralized and Distributed Planning Control

Real world events are driven by a mixture of both centralized and distributed control of individual agents based on their situational context and internal make up. For example, some people have partial allegiances to multiple, contradictory authorities, as well as to their own goals and principles. This can create a cognitive dissonance that can be exploited by an appropriately directed psychological influence operation (PSYOP). An Autonomous Dynamic Planning and Execution (ADP&E) approach is proposed for modeling both the unperturbed context as well as its reaction to various PSYOP interventions. As an illustrative example, the unrest surrounding the Iranian elections in the summer of 2009 is described in terms applicable to an ADP&E modeling approach. Aspects of the ADP&E modeling process are discussed to illustrate its application and advantages for this example.

Vaccaro, James↗
NASA NTRS1996

Microgravity Effects on Transendothelial Transport

The Endothelial Cell (EC) layer which lines blood vessels from the aorta to the capillaries provides the principal barrier to transport of water and solutes between blood and underlying tissue. Endothelial cells are continuously exposed to the mechanical shearing force (shear stress) and normal force (pressure) imposed by flowing blood on their surface, and they are adapted to this mechanical environment. When the cardiovascular system is exposed to microgravity, the mechanical environmental of endothelial cells is perturbed drastically and the transport properties of EC layers are altered in response. We have shown recently that step changes in shear stress have an acute effect on transport properties of EC layers in a cell culture model, and several recent studies in different vessels of live animals have confirmed the shear-dependent transport properties of the endothelium. We hypothesize that alterations in mechanical forces induced by microgravity and their resultant influence on transendothelial transport of water and solutes are, in large measure, responsible for the characteristic cephalad fluid shift observed in humans experiencing microgravity. To study the effects of altered mechanical forces on transendothelial transport and to test pharmacologic agents as counter measures to microgravity induced fluid shifts we have proposed ground-based studies using well defined cell culture models.

Tarbell, John M.↗
NASA NTRS2017

Modeling Space Radiation with Radiomimetic Agent Bleomycin

Space radiation consists of proton and helium from solar particle events (SPE) and high energy heavy ions from galactic cosmic ray (GCR). This mixture of radiation with particles at different energy levels has different effects on biological systems. Currently, majority studies of radiation effects on human were based on single-source radiation due to the limitation of available method to model effects of space radiation on living organisms. While NASA Space Radiation Laboratory is working on advanced switches to make it possible to have a mixed field radiation with particles of different energies, the radiation source will be limited. Development of an easily available experimental model for studying effects of mixed field radiation could greatly speed up our progress in our understanding the molecular mechanisms of damage and responses from exposure to space radiation, and facilitate the discovery of protection and countermeasures against space radiation, which is critical for the mission to Mars. Bleomycin, a radiomimetic agent, has been widely used to study radiation induced DNA damage and cellular responses. Previously, bleomycin was often compared to low low Linear Energy Transfer (LET) gamma radiation without defined characteristics. Our recent work demonstrated that bleomycin could induce complex clustered DNA damage in human fibroblasts that is similar to DNA damage induced by high LET radiation. These type of DNA damage is difficult to repair and can be visualized by gamma-H2Ax staining weeks after the initial insult. The survival ratio between early and late plating of human fibroblasts after bleomycin treatment is between low LET and high LET radiation. Our results suggest that bleomycin induces DNA damage and other cellular stresses resembling those resulted from mixed field radiation with both low and high LET particles. We hypothesize that bleomycin could be used to mimic space radiation in biological systems. Potential advantages and limitations of using bleomycin to treat biological specimen as an easily available model to study effects of space radiation on biological systems and to develop countermeasures for space radiation associated risks will be discussed.

Lu, Tao↗
NASA NTRS1989

A development framework for distributed artificial intelligence

The authors describe distributed artificial intelligence (DAI) applications in which multiple organizations of agents solve multiple domain problems. They then describe work in progress on a DAI system development environment, called SOCIAL, which consists of three primary language-based components. The Knowledge Object Language defines models of knowledge representation and reasoning. The metaCourier language supplies the underlying functionality for interprocess communication and control access across heterogeneous computing environments. The metaAgents language defines models for agent organization coordination, control, and resource management. Application agents and agent organizations will be constructed by combining metaAgents and metaCourier building blocks with task-specific functionality such as diagnostic or planning reasoning. This architecture hides implementation details of communications, control, and integration in distributed processing environments, enabling application developers to concentrate on the design and functionality of the intelligent agents and agent networks themselves.

Adler, Richard M.↗