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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 307 records · Page 17

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DOE OSTI2025

Harnessing Machine Learning for Agnostic Biodetection

The United States’ current list-based approach to biodefense is limited because it considers only known biological agents. Alternatively, developing and adopting a system based on agent-agnostic signatures would enable detection and characterization of both known and novel agents, thereby engendering greater adaptability in the face of an evolving threat landscape. Machine learning (ML) could aid in such a transition, as it can recognize and encode highly complex patterns from multiple input data modalities and has already demonstrated success in many healthcare and defense applications. Functionalizing ML for environmental biodetection requires understanding current technical capabilities. In this article, we provide a systematic review of existing ML platforms and discuss anticipated development efforts needed to achieve effective ML-enabled, agnostic biodetection.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1993

Toxicity study of dimethylethoxysilane (DMSES), the waterproofing agent for the Orbiter heat protective system

DMES, a volatile liquid, is used by NASA to waterproof the Orbiter thermal protective system. During waterproofing operations at the Oribter Processing Facility at KSC, workers could be exposed to DMES vapor. To assess the toxicity of DMES, acute and subchronic (2-week and 13-week) inhalation studies were conducted with rats. Studies were also conducted to assess the potential of DMES. Inhalation exposure concentrations ranged from 40 ppm to 4000 ppm. No mortality was observed during the studies. Exposures to 2100 ppm produced narcosis and ataxia. Post-exposure recovery from these CNS effects was rapid (less than 1 hr). These effects were concentration-dependent and relatively independent of exposure length. Exposure to 3000 ppm for 2 weeks (5 h/d, 5 d/wk) produced testicular toxicity. The 13-week study yielded similar results. Results from the genotoxicity assays (in vivo/in vitro unscheduled DNA synthesis in rat primary heptaocytes, chromosomal aberrations in rat bone marrow cells; reverse gene mutation in Salmonella typhimurium; and forward mutation in Chinese hamster culture cells) were negative. These studies indicated that DMES is mildly to moderately toxic but not a multagen.

Lam, Chiu-Wing↗

NASA NTRS2014

A Comprehensive Analysis of the X-15 Flight 3-65 Accident

The November 15, 1967, loss of X-15 Flight 3-65-97 (hereafter referred to as Flight 3-65) was a unique incident in that it was the first and only aerospace flight accident involving loss of crew on a vehicle with an adaptive flight control system (AFCS). In addition, Flight 3-65 remains the only incidence of a single-pilot departure from controlled flight of a manned entry vehicle in a hypersonic flight regime. To mitigate risk to emerging aerospace systems, the NASA Engineering and Safety Center (NESC) proposed a comprehensive review of this accident. The goal of the assessment was to resolve lingering questions regarding the failure modes of the aircraft systems (including the AFCS) and thoroughly analyze the interactions among the human agents and autonomous systems that contributed to the loss of the pilot and aircraft. This document contains the outcome of the accident review.

Dennehy, Cornelius J.↗

DOE OSTI2020

Transactive Energy Systems: The Market-based Coordination of Distributed Energy Resources

This paper synthesizes a unifying framework that captures a large class of transactive energy systems studied in the literature. The framework consists of four key elements: agent preferences, control decisions, information structure, and solution concept. Among them, agent preference specifies the preferred outcome by each agent and models the conflict of interest in decision making. Control decision specifies the set of decisions for each agent to maximize its payoff. Information structure describes the information available to each agent before it makes a decision. Solution concept encodes the rationality assumptions of each agent in the system. These elements are important in identifying and distinguishing different transactive energy systems. In this paper, we use them to analyze a number of important ones, including the competitive equilibrium, Stackelberg game, reverse Stackelberg game, and mechanism design. Each class of these problems is formulated as a special case of the proposed transactive energy systems. Their connections and differences are discussed. Available tools and results for each category of problems are surveyed.

Li, Sen↗

NASA NTRS2014

Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms

Dynamic environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal paths through these environments. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially with the number of agents in the system. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance.

Coevolution↗

NASA NTRS1967

Solvent permits solid curing agents to be used at room temperatures

Solvent system dissolves the solid curing agents used with polyurethane resins in adhesive systems. The system developed yields bond strengths comparable to 100 percent solid formulations. The optimum solvent chosen was a 55.5 percent solution in anhydrous tetrahydrofuran.

St. Cyr, M. C.↗

DOE OSTI2024

The safety of magnetic resonance imaging contrast agents

Gadolinium-based contrast agents are increasingly used in clinical practice. While these pharmaceuticals are verified causal agents in nephrogenic systemic fibrosis, there is a growing body of literature supporting their role as causal agents in symptoms associated with gadolinium exposure after intravenous use and encephalopathy following intrathecal administration. Gadolinium-based contrast agents are multidentate organic ligands that strongly bind the metal ion to reduce the toxicity of the metal. The notion that cationic gadolinium dissociates from these chelates and causes the disease is prevalent among patients and providers. We hypothesize that non-ligand-bound (soluble) gadolinium will be exceedingly low in patients. Soluble, ionic gadolinium is not likely to be the initial step in mediating any disease. The Kidney Institute of New Mexico was the first to identify gadolinium-rich nanoparticles in skin and kidney tissues from magnetic resonance imaging contrast agents in rodents. In 2023, they found similar nanoparticles in the kidney cells of humans with normal renal function, likely from contrast agents. We suspect these nanoparticles are the mediators of chronic toxicity from magnetic resonance imaging contrast agents. This article explores associations between gadolinium contrast and adverse health outcomes supported by clinical reports and rodent models.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2004

Clarissa Spoken Dialogue System for Procedure Reading and Navigation

Speech is the most natural modality for humans use to communicate with other people, agents and complex systems. A spoken dialogue system must be robust to noise and able to mimic human conversational behavior, like correcting misunderstandings, answering simple questions about the task and understanding most well formed inquiries or commands. The system aims to understand the meaning of the human utterance, and if it does not, then it discards the utterance as being meant for someone else. The first operational system is Clarissa, a conversational procedure reader and navigator, which will be used in a System Development Test Objective (SDTO) on the International Space Station (ISS) during Expedition 10. In the present environment one astronaut reads the procedure on a Manual Procedure Viewer (MPV) or paper, and has to stop to read or turn pages, shifting focus from the task. Clarissa is designed to read and navigate ISS procedures entirely with speech, while the astronaut has his eyes and hands engaged in performing the task. The system also provides an MPV like graphical interface so the procedure can be read visually. A demo of the system will be given.

Hieronymus, James↗

DOE OSTI2021

Assessing Adaptive Irrigation Impacts on Water Scarcity in Nonstationary Environments—A Multi‐Agent Reinforcement Learning Approach

Abstract One major challenge in water resource management is to balance the uncertain and nonstationary water demands and supplies caused by the changing anthropogenic and hydroclimate conditions. To address this issue, we developed a reinforcement learning agent‐based modeling (RL‐ABM) framework where agents (agriculture water users) are able to learn and adjust water demands based on their interactions with the water systems. The intelligent agents are created by a reinforcement learning algorithm adapted from the Q‐learning algorithm. We illustrated this framework in a case study where the RL‐ABM is two‐way coupled with the Colorado River Simulation System (CRSS), a long‐term planning model used for the administration of the Colorado River Basin, for assessing agriculture water uses impacts on water scarcity. Seventy‐eight intelligent agents are simulated, which can be grouped into three categories based on their parameter values: the “aggressive” (swift actions; low regrets), the “forward‐looking conservative” (mild actions; high regrets; fast learning), and the “myopic conservative” (mild actions; median regrets; slow learning). The ABM‐CRSS results showed that the major reservoirs in the Upper Colorado Basin might experience more frequent water shortages due to the increasing water uses compared to the original CRSS results. If the drought continues, the case study also demonstrates that agents can learn and adjust their demands.

Hung, Fengwei↗

DOE OSTI2022

Methods and systems for low to ultra-low magnetic field nuclear magnetic resonance for detecting chemical nerve agents

A nuclear magnetic resonance (NMR) system is configured to detect chemical threat material. The system comprises a magnet configured to generate a magnetic field of about 300 millitesla or less; and a probe configured to detect nuclear relaxation of at least two nuclei selected from the group consisting of 1H, 19F, 31P and 14N, and detect the spin density of nuclei selected from the group consisting of 1H, 19F, 31P and 14N, following excitation.

Williams, Robert F.↗

DOE OSTI2025

DOE Repository Metadata Profile (DRMP): A Metadata Framework for Advancing Interoperability and AI Readiness Across Scientific Repositories

The Department of Energy (DOE) funds a diverse and distributed ecosystem of repositories that steward scientific data, publications, and software across its research programs, user facilities, and national laboratories. While significant progress has been made in standardizing dataset-level metadata, the metadata describing repositories themselves (their identity, governance, access interfaces, policies, and technical capabilities) remains inconsistent and fragmented across DOE-funded systems. This variability limits discoverability, interoperability, automated validation, and AI-driven analysis, all of which are increasingly essential for modern scientific workflows. To address this gap, the DOE Data Curation Working Group (DCWG) developed the DOE Repository Metadata Profile (DRMP). The DRMP is a practical, community-driven framework that defines how repositories can describe themselves in a consistent, machine-actionable, and scalable manner. The DRMP is not a new metadata schema. Instead, it is a mapping profile and structured element set capturing the essential characteristics of DOE repositories. It harmonizes repository-level metadata across six widely adopted community schemas: RE3Data; DCAT-US v3; Schema.org; Dublin Core; DataCite 4.6; and PREMIS 3.0. This harmonization eliminates reinvention and enables interoperability within DOE and across the broader scientific ecosystem. A core objective of the DRMP is to reduce burden on repositories by allowing them to reuse their existing metadata through a Rosetta-style crosswalk rather than redesigning local implementations. The profile introduces a three-level conformance model that supports incremental adoption: • Level 1 – Minimum Viable Record (MVR): foundational identification elements required for workflows, project registration, and basic repository presence. • Level 2 – Interoperable: structured metadata enabling alignment with national and international discovery systems. • Level 3 – AI-Ready: enhanced provenance, policy transparency, fixity, semantic context, and capabilities that support automated reasoning, model training governance, and machine-assisted curation. To support implementation, the DRMP includes JSON Schema definitions, OpenAPI patterns, and MCP templates that allow repositories to publish machine-readable metadata directly within existing platforms. These resources are modular and lightweight, enabling adoption without major architectural change. Adopting the DRMP enables repositories to: • Enhance discoverability and interoperability by aligning identifiers, classifications, and descriptive elements across widely used schema standards. • Support federated discovery and cross-registration across DOE systems, Data.gov, and international catalogs. • Enable AI agents and workflow orchestration systems to interpret repository-level metadata within the American Science Cloud (AmSC) through Model Context Protocol (MCP)-based context publication. • Demonstrate alignment with DOE’s open science, stewardship, and FAIR data priorities. This guidance represents a community-driven step forward. Through voluntary adoption and continued feedback, the DRMP advances a cohesive, machine-actionable description of DOE repositories that supports FAIR data practices, preparing the infrastructure for AI-enabled research, and strengthening the discoverability and reuse of DOE’s scientific outputs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NASA NTRS2016

Tholins as Coloring Agents on Pluto and Other Icy Solar System Bodies

Tholins are refractory organic solids of complex structure and high molecular weight, with a wide range of color ranging from yellow and orange to dark red, and through tan to black. They are made in the laboratory by energy deposition (photons or charged particles) in gases and ices containing the simple molecules (e.g., N2, CH4, CO) found in planetary atmospheres or condensed on planetary surfaces. They are widely implicated in providing the colors and albedos, particularly in the region 0.3-1.0 microns, of several outer Solar System bodies, including Pluto, as well as aerosols in planetary atmospheres such as Titan. Recent color images of Pluto with the New Horizons spacecraft show concentrations of coloring agent(s) in some regions of the surface, and apparent near-absence in other regions. Tholins that may to some degree represent surface chemistry on Pluto have been synthesized in the laboratory by energetic processing of mixtures of the ices (N2, CH4, CO) known on Pluto's surface, or the same molecules in the gas phase. Details of the composition and yield vary with experimental conditions. Chemical analysis of Pluto ice tholins shows evidence of amides, carboxylic acids, urea, carbodiimides, and nitriles. Aromatic/olefinic, amide, and other functional groups are identified in XANES analysis. The ice tholins produced by e- irradiation have a higher concentration of N than UV ice tholins, with N/C approx. 0.9 (versus approx. 0.5 for UV tholins) and O/C approx.0.2. Raman spectra of the electron tholin show a high degree of structural disorder, while strong UV fluorescence indicates a large aromatic content. EUV photolysis of a Pluto gaseous atmosphere analog yields pale yellow solids relatively transparent in the visual, and with aliphatic CH bonds prominent in IR spectra. This or similar material may be responsible for Pluto's hazes.

Tholins↗

NASA NTRS1992

Multi-agent planning and scheduling, execution monitoring and incremental rescheduling: Application to motorway traffic

This article describes a planning method applicable to agents with great perception and decision-making capabilities and the ability to communicate with other agents. Each agent has a task to fulfill allowing for the actions of other agents in its vicinity. Certain simultaneous actions may cause conflicts because they require the same resource. The agent plans each of its actions and simultaneously transmits these to its neighbors. In a similar way, it receives plans from the other agents and must take account of these plans. The planning method allows us to build a distributed scheduling system. Here, these agents are robot vehicles on a highway communicating by radio. In this environment, conflicts between agents concern the allocation of space in time and are connected with the inertia of the vehicles. Each vehicle made a temporal, spatial, and situated reasoning in order to drive without collision. The flexibility and reactivity of the method presented here allows the agent to generate its plan based on assumptions concerning the other agents and then check these assumptions progressively as plans are received from the other agents. A multi-agent execution monitoring of these plans can be done, using data generated during planning and the multi-agent decision-making algorithm described here. A selective backtrack allows us to perform incremental rescheduling.

Mourou, Pascal↗

NASA NTRSDate not supplied

A Framework for Assessment of Autonomy Challenges in Air Traffic Management

Traditionally, air traffic management services have been provided by air traffic controllers and managers stationed in ground facilities, employed or contracted by the public sector, and supported by automation. These centralized, human-centric air traffic management services do not scale to accommodate increasing demands from conventional and new entrant operations for access to the national airspace system. One transformation that provides much needed scalability is increasing the level of autonomy of air traffic management by enabling edge agents of the system, including vehicles, operators, and third-party service suppliers, to collectively self-manage independently from the centralized service providers and enabling the automation to also take on more independent traffic management responsibility from the human agents. This paper identifies challenges to increasing the level of autonomy of air traffic management services. It describes a framework to enable a systematic identification of these challenges. The framework consists of a functional breakdown of air traffic management services and several dimensions characterizing different autonomy scales. The autonomy dimensions include the automation level between human and machine agents, the locus of control between centralized and distributed edge agents, cognitive activities for autonomous situation awareness and decision making, intelligence levels ranging from skill-based to expertise-based autonomous behavior, and uncertainty levels of the dynamics and environment in which autonomous agents operate. Several challenges are identified and categorized using the different dimensions of the autonomy framework.

automation, autonomy framework, collective autonom↗

NASA NTRS2005

Beyond the Prototype: The Design Evolution of a Deployed AI System

Our previous experiences with deployed intelligent control agents for NASA advanced life support systems (Schreckenghost et al., 2002) inspired us to develop the Distributed Collaboration and Interaction (DCI) system to help humans and mostly-autonomous software agents work together. We discovered many unaddressed needs for human interaction with control agents that operate continuously over months to years to monitor and perform process control for regenerative life support systems. These systems recover usable water or air from the waste products created by biological systems over time. Through the DCI project, we have addressed the needs for interaction between humans and autonomous control systems. This paper describes the software engineering aspects of our experiences, first, in designing and developing a prototype of the DCI system, and later, in adjusting the implementation to make the leap from initial prototype to a system ready to be applied under varying circumstances to meet different needs. The details in the paper focus primarily on the second stage of development. The DCI system is currently deployed, operating 24/7, to assist humans to interact with an advanced Water Recovery System (WRS). In addition, we have demonstrated an application of DCI to support ground personnel in mission support roles.

Martin, C.↗

NASA NTRS2004

Beyond the Prototype: The Design Evolution of a Deployed AI System

Martin, Cheryl↗

NASA NTRS2010

Verification of Faulty Message Passing Systems with Continuous State Space in PVS

We present a library of Prototype Verification System (PVS) meta-theories that verifies a class of distributed systems in which agent commu nication is through message-passing. The theoretic work, outlined in, consists of iterative schemes for solving systems of linear equations , such as message-passing extensions of the Gauss and Gauss-Seidel me thods. We briefly review that work and discuss the challenges in formally verifying it.

Pilotto, Concetta↗

DOE OSTI2022

Biosensor and optogenetics for systems biology of yeast branched-chain alcohol production and tolerance

In this project we combined synthetic biology, systems biology, protein engineering and metabolic engineering to study, control, and improve the production of branched chain alcohols (BCAs), a class of advanced biofuels preferred by the DOE, in the yeast Saccharomyces cerevisiae. This involved the development and application of optogenetic systems as a new modality of dynamic control of native and engineered metabolic pathways, using light as inducible or repressible agent. The optogenetic systems include gene circuits for light control of gene expression, as well as light-assembled synthetic organelles and photo-switchable protein binders to control metabolic and protein function with light at the protein level. In addition, we developed the first genetically encoded biosensor for BCA production in yeast, which we used to design high throughput assays to identify highly productive strains, pathways, and enzymes. We also showed that this biosensor can be functionally co-expressed with optogenetic circuits in the same strain, raising the possibility of establishing, for the first time, computer-interfaced closed-loop controls of engineered metabolic pathways. The yeast gene deletion library was also utilized to conduct the first systems-level study on BCA toxicity in yeast, which uncovered key fundamental principles of yeast sensitivity and tolerance to these alcohols, allowing us to design highly tolerant strains with increased BCA production. This project, thus comprises the development of several new technologies, which we integrated to make new discoveries on the dynamics of BCA production and their mechanisms of cellular toxicity and tolerance, as well as to establish new paradigms to engineer and control metabolic pathways and microbial fermentations with light, for the production of BCAs and other products of interest to the DOE.

2-metyl-1-butanol↗