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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Pulse-Flow Microencapsulation System

The pulse-flow microencapsulation system (PFMS) is an automated system that continuously produces a stream of liquid-filled microcapsules for delivery of therapeutic agents to target tissues. Prior microencapsulation systems have relied on batch processes that involve transfer of batches between different apparatuses for different stages of production followed by sampling for acquisition of quality-control data, including measurements of size. In contrast, the PFMS is a single, microprocessor-controlled system that performs all processing steps, including acquisition of quality-control data. The quality-control data can be used as real-time feedback to ensure the production of large quantities of uniform microcapsules.

Morrison, Dennis R.↗
DOE OSTI2024

Self-driving laboratories to autonomously navigate the protein fitness landscape

Abstract Protein engineering has nearly limitless applications across chemistry, energy and medicine, but creating new proteins with improved or novel functions remains slow, labor-intensive and inefficient. Here we present the Self-driving Autonomous Machines for Protein Landscape Exploration (SAMPLE) platform for fully autonomous protein engineering. SAMPLE is driven by an intelligent agent that learns protein sequence–function relationships, designs new proteins and sends designs to a fully automated robotic system that experimentally tests the designed proteins and provides feedback to improve the agent’s understanding of the system. We deploy four SAMPLE agents with the goal of engineering glycoside hydrolase enzymes with enhanced thermal tolerance. Despite showing individual differences in their search behavior, all four agents quickly converge on thermostable enzymes. Self-driving laboratories automate and accelerate the scientific discovery process and hold great potential for the fields of protein engineering and synthetic biology.

Rapp, Jacob T. (ORCID:0000000226835204)↗
NASA NTRS1997

New Approaches to Waterproofing of Space Shuttle Insulating Materials

Future reusable space vehicles will be in service much more frequently than current space shuttles. Therefore, rapid reconditioning of spacecraft will be required. Currently, the waterproofing of space shuttles after each re-entry takes 72 hours and requires substantial labor. In addition, the currently used waterproofing reagent, DiMethylEthoxySilane (DMES), is considered toxic, and ethanol fumes are released during its hydrolytic activation. Consequently, a long time period, which is not acceptable for future operations, is needed to ensure that 0 the excess volatile compounds are removed before further maintenance of the space vehicle can be performed. The objective of this project was to assist NASA Ames in finding improved waterproofing systems by identifying suitable waterproofing agents that can be applied by vapor phase deposition and will be less toxic, bond more rapidly to the insulation material surface, and potentially have higher thermal stability than the DMES system. Several approaches to achieve faster waterproofing with less toxicity were assessed using the following alternatives: Reactive volatile compounds that are rapidly deposited by chemical bonding at the surface and leave no toxic volatiles. Reactive reagents that are the least toxic. Nonvolatile reagents that are very reactive and bond strongly to the insulating material surface. Three specific types of potential reagents were chosen for evaluation in this project: 1. Volatile reagents with Si-Cl functional groups for vapor deposition 2. Volatile reagents with Si-H functional groups for vapor deposition 3. Nonvolatile oligomeric or polymeric reactive siloxanes that are assumed to have higher thermal stability and/or strong bonding to the insulating material. The chemistry involved in the project was targeted at the generation of intermediates having reactive Si-OH bonds for the formation of either volatile species or polymeric species that bond rapidly to the surface and also cure rapidly. We focused on two chemical reactions@-hydrolysis of Si-Cl bonds and catalytic dehydrocoupling of Si-H bonds.

Blum, Yigal D.↗
DOE OSTI2026

A transfer learning approach to energy-efficient control of small and medium-sized commercial buildings

Model-free reinforcement learning (RL) provides a data-driven and adaptive approach to optimize building energy use while satisfying occupant comfort. This powerful tool does not need any prior knowledge about the environment and system it is optimizing and can adapt its policy based on the changes in captures. Like any other data-driven tool, it faces high training costs due to the extensive agent-environment interactions required to capture long-term building dynamics and user comfort. Transfer learning, particularly policy distillation, offers a promising way to accelerate training by leveraging pretrained RL agents in different building and system types. Here, this study investigates online student distillation, in which the student model updates its neural network weights using outputs from teacher models. The work introduces a student distillation strategy designed for efficient knowledge transfer, along with a teacher selection method that ensures high-quality guidance. The approach is validated using a highly calibrated whole building energy model for a small/medium commercial building test facility. Results show substantial reductions in training time and data requirements while surpassing the performance of ASHRAE Guideline 36, an advanced rule-based control strategy. The distilled RL model required 45% less data and achieved 20% higher cumulative rewards than a state-of-the-art RL model, with faster convergence and lower energy consumption. These outcomes demonstrate that effective transfer learning enables a scalable and data-efficient energy management solution for commercial buildings.

ASHRAE guideline 36↗
NASA NTRS2007

Automating CapCom Using Mobile Agents and Robotic Assistants

Mobile Agents (MA) is an advanced Extra-Vehicular Activity (EVA) communications and computing system to increase astronaut self-reliance and safety, reducing dependence on continuous monitoring and advising from mission control on Earth. MA is voice controlled and provides information verbally to the astronauts through programs called "personal agents." The system partly automates the role of CapCom in Apollo-including monitoring and managing navigation, scheduling, equipment deployment, telemetry, health tracking, and scientific data collection. Data are stored automatically in a shared database in the habitat/vehicle and mirrored to a site accessible by a remote science team. The program has been developed iteratively in authentic work contexts, including six years of ethnographic observation of field geology. Analog field experiments in Utah enabled empirically discovering requirements and testing alternative technologies and protocols. We report on the 2004 system configuration, experiments, and results, in which an EVA robotic assistant (ERA) followed geologists approximately 150 m through a winding, narrow canyon. On voice command, the ERA took photographs and panoramas and was directed to serve as a relay on the wireless network.

Clancey, William J.↗
DOE OSTI2021

Exploring PV Circularity by Modeling Socio-Technical Dynamics of Modules’ End-of-Life Management

The circular economy (CE) tackles environmental and resource scarcity issues by maximizing value retention in the economy. The concept implies design strategies such as reducing the use of materials or improving products’ durability and end-of-life (EOL) strategies, for example, reusing products and components and recycling materials. With an estimated 80 million tons of global cumulative EOL photovoltaic (PV) modules, applying CE principles to the PV industry could alleviate resource scarcity issues while also providing economic benefits. However, transitioning to a CE may imply changes in organizations and consumer behaviors. In this context, assessment of CE strategies may require accounting for behavioral change, a requirement that methods from complex system science such as agent-based modeling meet. Thus, this paper uses an agent-based modeling (ABM) approach to study circularity in the photovoltaics supply chain. Four types of agents are represented in the ABM: PV owners, installers, recyclers, and manufacturers. Moreover, five possible EOL options – including three CE strategies – are modeled. Departing from traditional techno-economic analysis, the model includes techno-economic factors as well as social factors to model EOL management decisions. Results show that each dollar decrease in the recycling fees improves the recycling rate by roughly 1.1%. However, excluding social factors underestimates the effect that lower recycling prices have on material circularity.

agent-based modeling↗
NASA NTRS2005

Multi-Agent Software Design and Engineering for Human Centered Collaborative Autonomous Space Systems: NASA Intelligent Systems

Detailed results of this three-year project are available in 37 publications, including 7 book chapters, 3 journal articles, and 27 refereed conference proceedings. In addition, various aspects of the project were the subject of 31 invited presentations and 6 tutorials at international conferences and workshops. Good descriptions of prior and ongoing work on foundational technologies in Brahms, KAoS, NOMADS, and the PSA project can be found in numerous publications not listed here.

Bradshaw, Jeffrey M.↗
DOE OSTI2024

HybridSystemsSimulations.jl - Solving the Merchant Collocated Facilities with JuMP

The development of new clean-generation technologies also leads to new plant-level architectures that combine several generation and storage assets behind the point of connection. These co-located generation resources (Hybrid Systems) primarily operate as merchant assets that employ automated market bidding models and internal Energy Management Systems (EMS) to comply with the operator's signals. Formulating an optimal bidding model requires embedding the EMS control model into the bidding algorithm, resulting in a bi-level optimization problem. In this presentation, we first showcase using JuMP to formulate and solve this problem effectively for multiple merchant systems and the bidding outcomes considering different model formulations. Second, the bidding outcomes are later integrated into a PowerSimulations.jl (also built with JuMP) simulation to study the system-level effects of the various merchant bidding and the interactions between market-clearing models and the embedded EMS model. We will showcase simulations conducted in the RTS system considering different levels of merchant hybrid systems participation. The presentation provides the following specific insights on JuMP usage: 1) the Formulation of specialized bi-level problems with custom cuts to solve the merchant hybrid system bidding problem; 2) the integration of a modular model within a complex simulation workflow supported by JuMP in PowerSimulations.jl; 3) Accelerating the solution of power systems operations simulation that employ agent optimization problems using JuMP.

energy markets↗
NASA NTRS2011

Process Algebra Approach for Action Recognition in the Maritime Domain

The maritime environment poses a number of challenges for autonomous operation of surface boats. Among these challenges are the highly dynamic nature of the environment, the onboard sensing and reasoning requirements for obeying the navigational rules of the road, and the need for robust day/night hazard detection and avoidance. Development of full mission level autonomy entails addressing these challenges, coupled with inference of the tactical and strategic intent of possibly adversarial vehicles in the surrounding environment. This paper introduces PACIFIC (Process Algebra Capture of Intent From Information Content), an onboard system based on formal process algebras that is capable of extracting actions/activities from sensory inputs and reasoning within a mission context to ensure proper responses. PACIFIC is part of the Behavior Engine in CARACaS (Cognitive Architecture for Robotic Agent Command and Sensing), a system that is currently running on a number of U.S. Navy unmanned surface and underwater vehicles. Results from a series of experimental studies that demonstrate the effectiveness of the system are also presented.

process algebras↗
DOE OSTI2021

Evaluate the System-Level Impact of Connected and Automated Vehicles Coupled with Shared Mobility: An Agent-based Simulation Approach

With the rapid growth of information and communication technologies, Connected and Automated Vehicles (CAVs) are deemed to be disruptive with the potential to significantly improve overall transportation system efficiency, however, may bring Vehicle Miles Traveled (VMT) increase or other issues. Further, shared mobility systems are another disruptive force that is reshaping our travel patterns. To quantify the combined impact of CAV and shared mobility on travel behavior, traffic performance and energy efficiency, we develop a mesoscopic simulation-based framework for mobility and energy efficiency evaluation considering the disruptive transportation technologies. Under this framework, we develop novel models for energy intensity and modal activity, and evaluated a variety of energy scenarios for different combinations of CAV applications, various levels of automation, roadway characteristics, and traffic conditions, while also varying different vehicle types and fuel/powertrain technologies. Based applying this modeling suite to a calibrated BEAM simulation network in Riverside California, it was found that cooperative automated driving in general will improve mobility, but automated vehicles, even when deployed in a shared autonomous fleet, will likely bring an increase of VMT (up to 36%) due to mode shifts and deadheading. Ride-hailing vehicles typically have better energy efficiency and a higher share of electric vehicles, which helps offset the negative impact from VMT increases when estimating the system-level energy consumption. In general, simulation results show a 6% increase in energy consumption for the scenarios with an increasing shift to ride-hailing modes.

42 ENGINEERING↗
NASA NTRS1995

Charged Particle Alterations of Surfaces in the Solar System

The surfaces of 'airless' bodies in the solar system are exposed to the ambient plasma, micrometeorites, and the solar UV. The effects of these space weathering agents on surfaces in the solar system has been studied in this project. In the last three years work was carried out on volatile depletion at Mars, on sputtering of the lunar surface, on absorption by implanted S in vapor-deposited H2O and its relevance to observations of Europa's surface in the UV, and on the spectral changes produced on irradiating SO2 and its possible relevance to Io. In addition, the role of plasma-induced charging of E-ring grains was evaluated because of its relevance to E-ring particle source and the lifetime of the E-ring. Finally, the detection of sputtered material from Dione by the CAPS instrument on CASSINI was evaluated as a tool for analysis of satellite surface composition, and the role of sputtering on the ambient OH in the vicinity of the ice satellites and the E-ring was evaluated.

Johnson, R. E.↗
NASA NTRS2003

Neuroprotection trek--the next generation: neuromodulation II. Applications--epilepsy, nerve regeneration, neurotrophins

Three examples of neuroprotective applications of electrical stimulation-neuromodulation-are considered: (1) the diagnosis and treatment of epilepsy, (2) the augmentation of peripheral nerve regeneration after transection, and (3) the interaction between electrical stimulation and neurotrophins (notably brain derived neurotrophic factor [BDNF]) in various neuroprotective situations. The research cited demonstrates clear benefit from appropriate electrical stimulation in the treatment of (1) certain patients with medication-refractory epilepsy, and (2) the functional regeneration of peripheral nerves after transection and surgical repair. Furthermore, neuromodulation of peripheral nerve regeneration has been associated with an increase in the neurotrophin BDNF. The roles of BDNF and other neurotrophins in several disorders of the nervous system are discussed in the context of neuromodulation and its augmentation of neurotrophins. Neuromodulation-at least in part through its effect on BDNF and other neurotrophins-will likely play a major role in the treatment (and possibly prevention) of disorders of the nervous system for which neuroproteive pharmacologic agents have traditionally been sought.

Review↗
NASA NTRSDate not supplied

LSMS–L35, Miniature Crane for Payload Offloading and Manipulation: Development, and Application

The Lightweight Surface Manipulation System (LSMS) is a robotic agent for autonomous surface construction activities on planetary surfaces, that was designed at NASA Langley Research Center and has over a decade of research and development. The LSMS is a key component to achieving many goals of the NASA Artemis program. The LSMS is lightweight, structurally efficient system that can be easily packaged for launch and deployment on-surface, capable of a suite of surface activities enabled by modular end-effectors at the wrist. The focus of recent development work has been on using the LSMS for payload offloading and handling from lunar landers. Discussed in the paper is the development of the LSMS-L35 hardware (35 kg wrist lifting capacity on the lunar surface), designed to integrate with a Commercial Lunar Payload Services (CLPS) lander to offload payloads to the surface. The LSMS-L35 hardware development is part of a larger effort to enable autonomous payload handling and manipulation.

Iok M. Wong↗
DOE OSTI2024

SEDONA and ERDE: Portable Detection of Chemical Agents by Low Magnetic Field Nuclear Magnetic Resonance [Slides]

Two spectrometer systems have been developed at LANL for hazardous and/or toxic chemical agent detection and forensic analysis: SpEctroscopic Detection Of Nerve Agents (SEDONA) is a portable bottle scanner; and Earth’s field Resonance Detection and Evaluation (ERDE) Devices are fieldable J-coupled Earth’s Field - NMR (EF-NMR) spectrometers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

Miniature Laboratory for Detecting Sparse Biomolecules

A miniature laboratory system has been proposed for use in the field to detect sparsely distributed biomolecules. By emphasizing concentration and sorting of specimens prior to detection, the underlying system concept would make it possible to attain high detection sensitivities without the need to develop ever more sensitive biosensors. The original purpose of the proposal is to aid the search for signs of life on a remote planet by enabling the detection of specimens as sparse as a few molecules or microbes in a large amount of soil, dust, rocks, water/ice, or other raw sample material. Some version of the system could prove useful on Earth for remote sensing of biological contamination, including agents of biological warfare. Processing in this system would begin with dissolution of the raw sample material in a sample-separation vessel. The solution in the vessel would contain floating microscopic magnetic beads coated with substances that could engage in chemical reactions with various target functional groups that are parts of target molecules. The chemical reactions would cause the targeted molecules to be captured on the surfaces of the beads. By use of a controlled magnetic field, the beads would be concentrated in a specified location in the vessel. Once the beads were thus concentrated, the rest of the solution would be discarded. This procedure would obviate the filtration steps and thereby also eliminate the filter-clogging difficulties of typical prior sample-concentration schemes. For ferrous dust/soil samples, the dissolution would be done first in a separate vessel before the solution is transferred to the microbead-containing vessel.

Lin, Ying↗
NASA NTRS1986

Ultrasonic Mixing of Epoxy Curing Agents

New ultrasonic mixing technique used to mix several curing agents/epoxy combinations. Major component of commercially available base epoxy resin used in tetraglycidylmethylenedianiline (TGMDA). In ultrasonic mixing system cup holds resin and curing agent during acoustic excitation. Samples placed in cup with top to ultrasonic horn forming bottom of cup. Ultrasonically treated until amber colored and transparent. Because ultrasonic agitation drives out entrapped air, degassing not necessary before cure.

Hodges, W. T.↗
NASA NTRS2006

Integrated Vehicle Health Management (IVHM) for Aerospace Systems

To achieve NASA's ambitious Integrated Space Transportation Program objectives, aerospace systems will implement a variety of new concept in health management. System level integration of IVHM technologies for real-time control and system maintenance will have significant impact on system safety and lifecycle costs. IVHM technologies will enhance the safety and success of complex missions despite component failures, degraded performance, operator errors, and environment uncertainty. IVHM also has the potential to reduce, or even eliminate many of the costly inspections and operations activities required by current and future aerospace systems. This presentation will describe the array of NASA programs participating in the development of IVHM technologies for NASA missions. Future vehicle systems will use models of the system, its environment, and other intelligent agents with which they may interact. IVHM will be incorporated into future mission planners, reasoning engines, and adaptive control systems that can recommend or execute commands enabling the system to respond intelligently in real time. In the past, software errors and/or faulty sensors have been identified as significant contributors to mission failures. This presentation will also address the development and utilization of highly dependable sohare and sensor technologies, which are key components to ensure the reliability of IVHM systems.

Baroth, Edmund C.↗
DOE OSTI2025

Multi-agent AI collaboration for digital twin development and assessment

Developing a digital twin (DT) model involves different steps that encompass formulating requirements, model development, implementation, and assessment with respect to real applications. Human expertise is required to coordinate and implement different steps in the DT development and assessment process. However, certain parts of this process can be automated using artificial intelligence (AI) agents for efficient workflow development. In this work, we test and analyze a multiagent AI collaboration with humans in the loop to automate different elements of the DT development and assessment process. To implement the workflow for multiagent AI DT development and assessment, we use Autogen, a multiagent framework developed by Microsoft. Autogen offers a modular and flexible framework for configuring and designing task-specific multiagent workflows. In this framework, large language models (LLMs) form the core intelligence of the AI agents where the quality and performance of the automated element is governed by the inherent capabilities and knowledge base of the LLM. We use retrieval augmented generation to supplement the LLM with relevant domain-specific information for DT requirement formulation. We illustrate this multiagent workflow using a case study on a thermal energy storage system, focusing on how AI agents can collaborate with humans to expedite and optimize different elements of DT development and assessment process.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗