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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Functional Allocation Approach for Separation Assurance for Remotely Piloted Aircraft

A functional analysis framework is employed with the objective of exploring the separation assurance function for the remotely piloted aircraft system. The architecture of the remotely piloted aircraft system—highlighting several of the component systems and the functions resident onboard the remotely piloted aircraft and in the ground control station—is described to provide the context for understanding the complexity of the said system for a detailed functional analysis. The interactions between the agents of the separation assurance function belonging to the air traffic service provider, remotely piloted aircraft system operator and remotely piloted aircraft are described. Separation assurance by air traffic control, remain well clear by the remotely piloted aircraft system and collision avoidance onboard the remotely piloted aircraft are briefly discussed. The functional analysis framework is illustrated by relating the agents to the actions of (a) acquiring the surveillance information, (b) checking for conflicts, (c) creating the solutions for resolving conflicts and (d) implementing the conflict resolution solutions. This example is offered as a template by which a more detailed functional analysis of this and other functions could be developed. The architecture of the remotely piloted aircraft system is described to aid this process.

functional analysis↗
NASA NTRS2022

Functional Allocation Approach for Separation Assurance for Remotely Piloted Aircraft

A functional analysis framework is employed with the objective of exploring the separation assurance function for the remotely piloted aircraft system. The architecture of the remotely piloted aircraft system—highlighting several of the component systems and the functions resident onboard the remotely piloted aircraft and in the ground control station—is described to provide the context for understanding the complexity of the said system for a detailed functional analysis. The interactions between the agents of the separation assurance function belonging to the air traffic service provider, remotely piloted aircraft system operator and remotely piloted aircraft are described. Separation assurance by air traffic control, remain well clear by the remotely piloted aircraft system and collision avoidance onboard the remotely piloted aircraft are briefly discussed. The functional analysis framework is illustrated by relating the agents to the actions of (a) acquiring the surveillance information, (b) checking for conflicts, (c) creating the solutions for resolving conflicts and (d) implementing the conflict resolution solutions. This example is offered as a template by which a more detailed functional analysis of this and other functions could be developed. The architecture of the remotely piloted aircraft system is described to aid this process.

Functional analysis↗
NASA NTRS2017

Synoptic Traveling Weather Systems on Mars: Effects of Radiatively-Active Water Ice Clouds

Atmospheric aerosols on Mars are critical in determining the nature of its thermal structure, its large-scale circulation, and hence the overall climate of the planet. We conduct multi-annual simulations with the latest version of the NASA Ames Mars global climate model (GCM), gcm2.3+, that includes a modernized radiative-transfer package and complex water-ice cloud microphysics package which permit radiative effects and interactions of suspended atmospheric aerosols (e.g., water ice clouds, water vapor, dust, and mutual interactions) to influence the net diabatic heating. Results indicate that radiatively active water ice clouds profoundly affect the seasonal and annual mean climate. The mean thermal structure and balanced circulation patterns are strongly modified near the surface and aloft. Warming of the subtropical atmosphere at altitude and cooling of the high latitude atmosphere at low levels takes place, which increases the mean pole-to-equator temperature contrast (i.e., "baroclinicity"). With radiatively active water ice clouds (RAC) compared to radiatively inert water ice clouds (nonRAC), significant changes in the intensity of the mean state and forced stationary Rossby modes occur, both of which affect the vigor and intensity of traveling, synoptic period weather systems. Such weather systems not only act as key agents in the transport of heat and momentum beyond the extent of the Hadley circulation, but also the transport of trace species such as water vapor, water ice-clouds, dust and others. The northern hemisphere (NH) forced Rossby waves and resultant wave train are augmented in the RAC case: the modes are more intense and the wave train is shifted equatorward. Significant changes also occur within the subtropics and tropics. The Rossby wave train sets up, combined with the traveling synoptic period weather systems (i.e., cyclones and anticyclones), the geographic extent of storm zones (or storm tracks) within the NH. A variety of circulation features will be presented which indicate contrasts between the RAC and nonRAC cases, and which highlight key effects radiatively-active clouds have on physical and dynamical processes active in the current climate of Mars.

Atmospheric aerosols↗
NASA NTRS2017

Synoptic Traveling Weather Systems on Mars: Effects of Radiatively-Active Water Ice Clouds

Atmospheric aerosols on Mars are critical in determining the nature of its thermal structure, its large-scale circulation, and hence the overall climate of the planet. We conduct multi-annual simulations with the latest version of the NASA Ames Mars global climate model (GCM), gcm2.3+, that includes a modernized radiative-transfer package and complex water-ice cloud microphysics package which permit radiative effects and interactions of suspended atmospheric aerosols (e.g., water ice clouds, water vapor, dust, and mutual interactions) to influence the net diabatic heating. Results indicate that radiatively active water ice clouds profoundly affect the seasonal and annual mean climate. The mean thermal structure and balanced circulation patterns are strongly modified near the surface and aloft. Warming of the subtropical atmosphere at altitude and cooling of the high latitude atmosphere at low levels takes place, which increases the mean pole-to-equator temperature contrast (i.e., "baroclinicity"). With radiatively active water ice clouds (RAC) compared to radiatively inert water ice clouds (nonRAC), significant changes in the intensity of the mean state and forced stationary Rossby modes occur, both of which affect the vigor and intensity of traveling, synoptic period weather systems.Such weather systems not only act as key agents in the transport of heat and momentum beyond the extent of the Hadley circulation, but also the transport of trace species such as water vapor, water ice-clouds, dust and others. The northern hemisphere (NH) forced Rossby waves and resultant wave train are augmented in the RAC case: the modes are more intense and the wave train is shifted equatorward. Significant changes also occur within the subtropics and tropics. The Rossby wave train sets up, combined with the traveling synoptic period weather systems (i.e., cyclones and anticyclones), the geographic extent of storm zones (or storm tracks) within the NH. A variety of circulation features will be presented which indicate contrasts between the RAC and nonRAC cases, and which highlight key effects radiatively-active clouds have on physical and dynamical processes active in the current climate of Mars.

GCM-global climate model↗
NASA NTRS2016

Synoptic Traveling Weather Systems on Mars: Effects of Radiatively-Active Water Ice Clouds

Atmospheric aerosols on Mars are critical in determining the nature of its thermal structure, its large-scale circulation, and hence the overall climate of the planet. We conduct multi-annual simulations with the latest version of the NASA Ames Mars global climate model (GCM), gcm2.3+, that includes a modernized radiative-transfer package and complex water-ice cloud microphysics package which permit radiative effects and interactions of suspended atmospheric aerosols (e.g., water ice clouds, water vapor, dust, and mutual interactions) to influence the net diabatic heating. Results indicate that radiatively active water ice clouds profoundly affect the seasonal and annual mean climate. The mean thermal structure and balanced circulation patterns are strongly modified near the surface and aloft. Warming of the subtropical atmosphere at altitude and cooling of the high latitude atmosphere at low levels takes place, which increases the mean pole-to-equator temperature contrast (i.e., "baroclinicity"). With radiatively active water ice clouds (RAC) compared to radiatively inert water ice clouds (nonRAC), significant changes in the intensity of the mean state and forced stationary Rossby modes occur, both of which affect the vigor and intensity of traveling, synoptic period weather systems. Such weather systems not only act as key agents in the transport of heat and momentum beyond the extent of the Hadley circulation, but also the transport of trace species such as water vapor, water ice-clouds, dust and others. The northern hemisphere (NH) forced Rossby waves and resultant wave train are augmented in the RAC case: the modes are more intense and the wave train is shifted equatorward. Significant changes also occur within the subtropics and tropics. The Rossby wave train sets up, combined with the traveling synoptic-period weather systems (i.e., cyclones and anticyclones), the geographic extent of storm zones (or storm tracks) within the NH. A variety of circulation features will be presented which indicate contrasts between the RAC and nonRAC cases, and which highlight key effects radiatively-active clouds have on physical and dynamical processes active in the current climate of Mars.

NASA Ames Mars global climate model (GCM)↗
DOE OSTI2024

Criticality Safety Calculations for Inadvertent PuF6 Formation

During a review of the Surplus Plutonium Disposition (SPD) at Savannah River Site (SRS) project Safety Basis Strategy a comment was made about the risk of inadvertent formation of plutonium hexafluoride, PuF6, during a plutonium fire suppressed by the NovecTM 1230 fire suppressant. NovecTM 1230 is a fluorine rich non-hydrogenous extinguishing agent. Hydrogenous materials, like water, increase reactivity of fissile material by adding moderation to the system and thus are generally not used as firefighting agents in fissile material areas.

Wade, Brindley↗
NASA NTRS2018

Evolving Relationship between Humans and Machines

Traditional design typically consists of a master-servant relationship between humans and machines where the human directly controls what the machine will do and when it will do it through an interface. The current archetypical path encompasses moving from informational displays, where the human directly controls the machine based on information displayed, to automation where the human still directs the machine that then caries out the request using predefined set of instructions. Rapid pace of technological advancement makes it possible now, or in a near future, for machines to reach a level of intelligence that enables for systems to execute tasks/missions without predefined specific instructions; thus attaining a status of non- human autonomous agents. Now the course of human-machine interface technology changes from an information system to automation to an autonomous agent—essentially moving from a master-servant relationship to teammates. This paper discusses these changing relationships and challenges associated with progressing from a master-servant relationship with technology to more of an equal teammate. Examples of this progression includes current work encompassing rotorcraft noise minimization for urban air mobility.

Trujillo, Anna C.↗
DOE OSTI2020

An agent-based approach to study the diffusion rate and the effect of policies on joint placement of photovoltaic panels and green roof under climate change uncertainty

As two of the highest trending green technologies, photovoltaic panels and green roofs are proven to be effective practices for energy generation and energy saving. The achievable impact from the widespread installation of such technologies is, however, not clearly established. This is mainly because the degree of this impact highly depends on the inherently uncertain environmental and climate factors, as well as the unknown adoption rates of these technologies, which in turn depend on different characteristics of decision makers and interactions among them. To that end, this study aims to investigate the diffusion rate of these green technologies under uncertainties caused by climate change, characteristics of adopters, and their interactions. An integrated framework is developed to capture the interplay between financial and attitudinal aspects, as well as the uncertainties due to both the stochastic nature of system parameters and the interactions among agents involving human beings. Specifically, this framework consists of a integer programming model to optimize the green roof and/or photovoltaic panel installation settings for a given building under climate change uncertainty, and an agent-based model to factor in the role of human behavior and interactions. A case study for the city of Knoxville, TN, is presented to evaluate the effects of different policies on the diffusion rate of the green technologies of interest. The results show that the affordability of green technologies and public awareness are the key drivers of the adoption of these technologies, which highlight the important role of the decision makers in impacting the diffusion rate.

14 SOLAR ENERGY↗
DOE OSTI2026

Enhancing Operational Safety via Agentic Dialogue Hazard Identification Analysis

Operational safety in high-stakes domains such as industrial process control, autonomous, and safety-critical systems demand reliable hazard identification. While large language models (LLMs) have shown promise in automating safety analysis tasks, single-turn, monolithic inference is brittle: it lacks the self-correction, deliberation, and contextual refinement that safety engineers apply iteratively. In this paper, we introduce HAZDIAL, a framework that investigates whether structured agentic dialogue (multi-agent, multi-turn interactions) improves the quality of NLP-based hazard identification over single-pass baselines. We systematically compare two dialogue modalities: adversarial debate and constructive discussion, and propose an genetic algorithm-based agentic interaction optimization. We evaluate all configurations against a curated golden dataset using standard classification metrics (accuracy, precision, recall, F1) and a novel dialogue metrics. This work advances the intersection of dialogue systems, multi-agent reasoning, and AI safety, providing empirical evidence for dialogue-driven hazard analysis.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗
DOE OSTI2023

Self-healing, self-assembling islanded power systems using only local measurements

This SAND report collects the results from the LDRD project “SHAZAM”, which aimed to push the limits of performance for self-healing, self-assembling power systems whose sectionalizing and load-control agents rely on local measurements only (i.e., only what they can measure at their own terminals, with no data sharing between agents). This work includes self-networking microgrids. The key objectives of this work were a) to demonstrate how high the performance of local-measurement-only self-assembling power systems can be; and b) to solve certain technical problems associated with such systems, such as their inability to prevent the accidental formation of closed loops and their tendency to thermally overload some conductors. “SHAZAM” investigators a) demonstrated that the performance of such systems can be surprisingly high, b) demonstrated that such systems are quite robust to all kinds of variations, and c) developed and demonstrated solutions to several key challenges associated with this type of system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2002

Brahms Mobile Agents: Architecture and Field Tests

We have developed a model-based, distributed architecture that integrates diverse components in a system designed for lunar and planetary surface operations: an astronaut's space suit, cameras, rover/All-Terrain Vehicle (ATV), robotic assistant, other personnel in a local habitat, and a remote mission support team (with time delay). Software processes, called agents, implemented in the Brahms language, run on multiple, mobile platforms. These mobile agents interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. The Brahms-based mobile agent architecture (MAA) uses a novel combination of agent types so the software agents may understand and facilitate communications between people and between system components. A state-of-the-art spoken dialogue interface is integrated with Brahms models, supporting a speech-driven field observation record and rover command system (e.g., return here later and bring this back to the habitat ). This combination of agents, rover, and model-based spoken dialogue interface constitutes a personal assistant. An important aspect of the methodology involves first simulating the entire system in Brahms, then configuring the agents into a run-time system.

Clancey, William J.↗
DOE OSTI2020

Development and Validation of a Simulation Testbed for the Intelligent Building Agents Laboratory (IBAL) Using TRNSYS

This paper documents the development and validation of a dynamic primary cooling and thermal storage system simulation testbed. The system simulation testbed, sIBAL, is based on the Intelligent Building Agents Laboratory (IBAL) at the National Institute of Standards and Technology (NIST), which is a research infrastructure and testbed for the development, evaluation, and demonstration of intelligent control algorithms. The sIBAL testbed developed in this project will serve as a virtual twin of the real facility for future control algorithm development. The details of the methodologies used to develop and validate the simulation testbed, which replicates the dynamic behaviors of the primary cooling and ice storage system in the IBAL facility, are presented. The simulation testbed was developed in TRNSYS using built-in component models and MATLAB functions to replicate the two water-cooled chillers, a thermal storage tank, pumps, valves and other components for four different operation modes. Experiments on IBAL components were designed and executed to generate experimental data for model development and verification of the simulation platform. The validation of the simulation results was carried out in two phases: 1) independent component simulations for the chillers and thermal storage tank, and 2) a combined testbed simulation of the entire hydronic system. Comparison of simulation results to the experimental data obtained from the IBAL facility showed errors within 1 °C for the temperatures outputs of both the chiller and the thermal storage model. The error is within an acceptable range for further intelligent control algorithms development. The findings from the study are summarized and presented along with areas where additional research is needed. In addition, data filtering procedures and model refinement measures utilized to improve the accuracy and accelerate the computation time of the simulation are presented.

cooling systems↗
DOE OSTI2020

Distributed Conditions for Small-signal Stability of Power Grids and Local Control Design

Operating modern power grids with stability guarantees is markedly important. Typical methods for analyzing and certifying power grid stability are largely centralized relying on the ability of the system operator to gather network-wide information and accurately compute the system's eigenvalues. These methods are oftentimes not privacy-preserving and computationally burdensome. They are therefore, not well-suited to modern power grids where small-signal stability has to be evaluated timely, efficiently and in a privacy-preserving fashion. Herein, we introduce a distributed methodology for certifying small-signal stability of power grids and designing the local controllers. First, we analytically derive distributed conditions for network-wide stability that bus agents can inspect using local information. By leveraging these conditions, we then introduce a distributed control design algorithm (DCDA) that can guide the local control design so that stability of the interconnected system is guaranteed. The agents that adopt the proposed distributed algorithm are responsible for tuning their local controllers, producing their local control commands and ensuring that their local stability condition is met. The system operator is only responsible for verifying network-wide stability upon receiving affirmative responses from all agents and, announcing, that the overall system is stable. The proposed DCDA algorithm is numerically validated via simulations using the IEEE 39-bus system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Summary of Technical Interchange Meetings (TIMs) Designed to Enable Earth Independent Medical Operations (EIMO)

The Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program hosted a series of TIMs in 2023-2024 designed to stimulate discussion around specific topics with the goal of enabling EIMO. In context of the thematic constituent elements of EIMO, namely pre-mission planning, acute/emergent/prolonged medical decision making, supply/resource management and task load management, subject matter experts from industry, academia and government (NASA and other Agencies) provided valuable and actionable guidance and recommendations. Earth-based medical experts will remain indispensable for pre-mission planning, however, management of acute/emergent medical contingencies will require a gradual transition of medical care and decision making from terrestrial to space-based assets to enable support of astronaut health and performance and reduce overall mission risk. Key to achieving these enhancements is providing an integrated data system platform capable of utilizing multiple data streams in concert with a variety of on-board databases and passive monitoring of video and wearable sensors to enable a multi-modal, agentic AI-based clinical decision support system (CDSS) to support crew medical officer (CMO) medical decision-making. The EIMO series of TIMs (I-V) have proven to be instructive and portend a significant paradigm shift will be necessary to maintain crew health and performance on exploration class missions. Importantly, since the expected paradigm shift will be significantly different from the methods of operation that have been employed for the majority of missions from the inception of human spaceflight to date, any proposed methods must be deployed in the setting of ongoing operations early and be “tested, reviewed and practiced” while reliable back-up is available to facilitate an Enterprise-wide level of comfort and acceptance. Serious constraints on data transmission coupled with a large and expanding universe of on-board medical informatics data streams will necessitate implementation of a CDSS to supplant the current reliance on support provided by ground-based SMEs. Establishment of trust in the system by CMO/crew and the ground-based medical support team will be essential. Co-development of a CDSS with industry partners will assure that state of the art tools can be employed, and industry efficiencies can be leveraged. Training regimens, materials and tools must evolve to be responsive (just-in-time training) and facilitate autonomous execution of procedures. Proficiency metrics should be established and be based on validated competencies or milestones as opposed to a prescribed number of training hours. Training should be prioritized for broad, translatable skills that have universal application across a variety of medical conditions. Repetition was deemed to be the key to achieving proficiency and emphasis should lie in procedural training which is known to extinguish more rapidly than diagnostic skills. Advanced tools, e.g., extended reality, can provide more realistic and effective training. Use of advanced probabilistic risk assessment tools will be essential to optimize the medical system capability while carefully balancing risk relative to mass/power/volume limitations. Importance of factoring use-life of medical supplies and maintaining awareness of redundancy and opportunity to re-purpose under off nominal situations was emphasized. Consideration of adopting optimized performance standards vs. “good-enough” performance thresholds is warranted. The use of legacy systems as opposed to creating new systems may be preferable. Managing task load and associated cognitive load will be essential to maintain operational safety and behavioral health. ExMC aspires to create a shared EIMO paradigm and strategic vision for advancing medical system design through novel technologies, training, protocols, and support capabilities, built upon the spirit of successful strategies and innovations over the past six decades of space medicine operations.

Jay Lemery↗
DOE OSTI2024

Exploring the role of judgement and shared situation awareness when working with AI recommender systems

Abstract AI-advised Decision Making is a form of human-autonomy teaming in which an AI recommender system suggests a solution to a human operator, who is responsible for the final decision. This work seeks to examine the importance of judgement and shared situation awareness between humans and automated agents when interacting together in the form of a recommender systems. We propose manipulating both human judgement and shared situation awareness by providing the human decision maker with relevant information that the automated agent (AI), in the form of a recommender system, uses to generate possible courses of action. This paper presents the results of a two-phase between-subjects study in which participants and a recommender system jointly make a high-stakes decision. We varied the amount of relevant information the participant had, the assessment technique of the proposed solution, and the reliability of the recommender system. Findings indicate that this technique of supporting the human’s judgement and establishing a shared situation awareness is effective in (1) boosting the human decision maker’s situation awareness and task performance, (2) calibrating their trust in AI teammates, and (3) reducing overreliance on an AI partner. Additionally, participants were able to pinpoint the limitations and boundaries of the AI partner’s capabilities. They were able to discern situations where the AI’s recommendations could be trusted versus instances when they should not rely on the AI’s advice. This work proposes and validates a way to provide model-agnostic transparency into recommender systems that can support the human decision maker and lead to improved team performance.

Srivastava, Divya↗
NASA NTRS2011

Microencapsulation of Self Healing Agents for Corrosion Control Coatings

Corrosion, the environmentally induced degradation of materials, is a very costly problem that has a major impact on the global economy. Results from a 2-year breakthrough study released in 2002 by the U.S. Federal Highway Administration (FHWA) showed that the total annual estimated direct cost associated with metallic corrosion in nearly every U.S. industry sector was a staggering $276 billion, approximately 3.1% of the nation's Gross Domestic Product (GOP). Corrosion protective coatings are widely used to protect metallic structures from the detrimental effects of corrosion but their effectiveness can be seriously compromised by mechanical damage, such as a scratch, that exposes the metallic substrate. The incorporation of a self healing mechanism into a corrosion control coating would have the potential to significantly increase its effectiveness and useful lifetime. This paper describes work performed to incorporate a number of microcapsule-based self healing systems into corrosion control coatings. The work includes the preparation and evaluation of self-healing systems based on curable epoxy, acrylate, and siloxane resins, as well as, microencapsulated systems based on passive, solvent born, healing agent delivery. The synthesis and optimization of microcapsule-based self healing systems for thin coating (less than 100 micron) will be presented.

Jolley, S. T.↗
NASA NTRS2005

Multi-Agent Modeling and Simulation Approach for Design and Analysis of MER Mission Operations

A space mission operations system is a complex network of human organizations, information and deep-space network systems and spacecraft hardware. As in other organizations, one of the problems in mission operations is managing the relationship of the mission information systems related to how people actually work (practices). Brahms, a multi-agent modeling and simulation tool, was used to model and simulate NASA's Mars Exploration Rover (MER) mission work practice. The objective was to investigate the value of work practice modeling for mission operations design. From spring 2002 until winter 2003, a Brahms modeler participated in mission systems design sessions and operations testing for the MER mission held at Jet Propulsion Laboratory (JPL). He observed how designers interacted with the Brahms tool. This paper discussed mission system designers' reactions to the simulation output during model validation and the presentation of generated work procedures. This project spurred JPL's interest in the Brahms model, but it was never included as part of the formal mission design process. We discuss why this occurred. Subsequently, we used the MER model to develop a future mission operations concept. Team members were reluctant to use the MER model, even though it appeared to be highly relevant to their effort. We describe some of the tool issues we encountered.

Seah, Chin↗