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At least 451 records · Page 25

The AI Bus architecture for distributed knowledge-based systems

The AI Bus architecture is layered, distributed object oriented framework developed to support the requirements of advanced technology programs for an order of magnitude improvement in software costs. The consequent need for highly autonomous computer systems, adaptable to new technology advances over a long lifespan, led to the design of an open architecture and toolbox for building large scale, robust, production quality systems. The AI Bus accommodates a mix of knowledge based and conventional components, running on heterogeneous, distributed real world and testbed environment. The concepts and design is described of the AI Bus architecture and its current implementation status as a Unix C++ library or reusable objects. Each high level semiautonomous agent process consists of a number of knowledge sources together with interagent communication mechanisms based on shared blackboards and message passing acquaintances. Standard interfaces and protocols are followed for combining and validating subsystems. Dynamic probes or demons provide an event driven means for providing active objects with shared access to resources, and each other, while not violating their security.

Schultz, Roger D.↗

Air Traffic Management Technology Demonstration-1 (ATD-1) Avionics Phase 2 Flight Test Training for Interval Management

Prior to the successful flight test validation of a new avionics prototype, participants from Boeing, Honeywell, and United Airlines underwent group training at NASA Langley Research Center. New prototype software for an algorithm which enables greater efficiency in high-density airspace, called Interval Management, was to be incorporated into Electronic Flight Bags and placed in the cockpit for pilot usage. The goals of the training were to teach the flight test pilots how to operate the new software, establish techniques to simultaneously position three aircraft prior to each test scenario, and ensure a common communication protocol among team members when coordinating the position of aircraft for the next scenario. The multi-tiered interactive training regimen consisted of a process that continually built upon previous foundational material. The primary learning elements were 1) a portable computer-based trainer that was provided to the pilots prior to classroom training sessions, 2) classroom learning, 3) full mock-up simulator training, and 4) refresher training just prior to the flight test. Each part of the regimen was designed to repeat and build upon the previous element. The purpose of this Technical Memorandum is to inform the aviation industry how flight training for Interval Management was conducted at Langley Research Center in order to reduce overall development costs of future Interval Management training programs. Secondly, the paper provides insight regarding the decision-making process when attempting to conduct a flight test.

Roper, Roy D.↗

Qudit Dynamical Decoupling on a Superconducting Quantum Processor

Multilevel qudit systems are increasingly being explored as alternatives to traditional qubit systems due to their denser information storage and processing potential. However, qudits are more susceptible to decoherence than qubits due to increased loss channels, noise sensitivity, and crosstalk. To address these challenges, we develop protocols for dynamical decoupling (DD) of qudit systems based on the Heisenberg-Weyl group. We implement and experimentally verify these DD protocols on a superconducting transmon processor that supports qudit operation based on qutrits (d = 3) and ququarts (d = 4). Specifically, we demonstrate single-qudit DD sequences to decouple qutrits and ququarts from system-bath-induced decoherence. Here we also introduce two-qudit DD sequences designed to suppress the detrimental cross-Kerr couplings between coupled qudits. This allows us to demonstrate a significant improvement in the fidelity of time-evolved qutrit Bell states. Our results highlight the utility of leveraging DD to enable scalable qudit-based quantum computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Framework to Demonstrate a DNP3 Interface With a CIM-Based Data Integration Platform: Preprint

The contemporary electrical grid is characterized by its complexity and abundance of data. A control-rich environment supported by information and communication technologies within an Advanced Distribution Management System (ADMS) presents a viable and cost-effective option for utility companies aiming to implement advanced real-time analytical schemes for monitoring and remotely controlling distribution feeders. Modular platform-based approaches to distribution operations require a structured framework for acquiring field device measurements, performing analytics, converting the setpoint to the correct protocol, and sending it on the appropriate communications network to the field devices. We present the development and deployment of an application service to integrate an open-source standardsbased platform with an ADMS test bed with field devices using the Distributed Network Protocol (DNP3) for data exchange. The step-by-step procedure for establishing the DNP3-Master service on an open-source distribution platform is outlined, comprehensively explaining the Master setup process. Moreover, sample use case results highlight the capabilities of the DNP3- Master service setup. Results demonstrate the scalability and configurability of the DNP3-Master service, making it adaptable for integration with other relevant applications, thus providing potential opportunities for real-world field trials and real-time assessments.

ADMS↗

Black-box optimization of CT acquisition and reconstruction parameters: a reinforcement learning approach

Protocol optimization is critical in Computed Tomography (CT) for achieving desired diagnostic image quality while minimizing radiation dose. Due to the inter-effect of influencing CT parameters, traditional optimization methods rely on the testing of exhaustive combinations of these parameters. This poses a notable limitation due to the impracticality of exhaustive parameter testing. This study introduces a novel methodology leveraging Virtual Imaging Trials (VITs) and reinforcement learning to more efficiently optimize CT protocols. Computational phantoms with liver lesions were imaged using a validated CT simulator and reconstructed with a novel CT reconstruction Toolkit. The optimization parameter space included tube voltage, tube current, reconstruction kernel, slice thickness, and pixel size. The optimization process was done using a Proximal Policy Optimization (PPO) agent which was trained to maximize the Detectability Index (d’) of the liver lesion for each reconstructed image. Results showed that our reinforcement learning approach found the absolute maximum d’ across the test cases while requiring 79.7% fewer steps compared to an exhaustive search, demonstrating both accuracy and computational efficiency, offering a efficient and robust framework for CT protocol optimization. The flexibility of the proposed technique allows for use of varying image quality metrics as the objective metric to maximize for. Our findings highlight the advantages of combining VIT and reinforcement learning for CT protocol management.

Fenwick, David [Duke University Medical Center]↗

Electrolyte Design for Fast‐Charging Lithium‐Based Batteries

Fast charging is essential for the widespread adoption of lithium (Li)-ion batteries, but it is fundamentally limited by sluggish interfacial kinetics, Li plating, and electrolyte instability at high current densities. Over the past decade, electrolyte engineering has emerged as a key strategy to address these challenges. This review summarizes the development of fast-charging electrolytes over the past ten years and outlines a design framework. Electrolyte formulations are first deconstructed into their main components—solvents, salts, and functional additives—and representative strategies for tuning solvation structure and interphase chemistry are discussed to suppress Li plating and improve interfacial kinetics. The discussion then extends to advanced electrolyte systems, particularly localized high-concentration electrolytes (LHCEs), and their compatibility with different anode chemistries. Advanced characterization techniques are also summarized and categorized based on destructiveness, spatial and temporal resolution, quantitative analysis, and the chemical species or processes probed across multiple length scales. Recent progress in AI-enabled electrolyte discovery and battery management system (BMS) strategies for optimized fast-charging protocols is further highlighted. Finally, perspectives are presented on translating electrolyte innovations from academic research to practical applications, with emphasis on cell format, realistic operating conditions, and manufacturability.

25 ENERGY STORAGE↗

MXene-Derived Potassium-Preintercalated Bilayered Vanadium Oxide Nanostructures for Cathodes in Nonaqueous K-Ion Batteries

Bilayered vanadium oxides (BVOs) are promising cathode materials for beyond-Li-ion batteries due to their tunable chemistries and high theoretical capacities. However, the large size of beyond-Li + ions limits electrochemical cycling and rate capability of BVO electrodes. Recent reports of MXene-derived BVOs with nanoscale flower-like morphology have shown improved electrochemical stability at high rates up to 5C in nonaqueous lithium-ion batteries. Here, we report how morphological stabilization can lead to improved rate capability in potassium-ion batteries (PIBs) through the synthesis and electrochemical characterization of MXene-derived K-preintercalated BVOs (MD-KVOs), which were derived from two V 2 CT x precursor materials prepared using two different etching protocols. We show that the etching conditions affect the surface chemistry of the MXene, which plays a role in the MXene-to-oxide transformation process. MXene derived from a milder etchant transformed into a nanoflower MD-KVO with two-dimensional (2D) nanosheet petals (KVO-DMAE) while a more aggressive etchant produced a MXene that transformed into a MD-KVO with one-dimensional (1D) nanorod morphology (KVO-CMAE). Electrochemical cycling of the produced MD-KVOs after drying at 200 °C under vacuum (KVO-DMAE-200 and KVO-CMAE-200) in PIBs showed that electrochemical stability of MD-KVO at high rates improved through the morphological stabilization of 2D particles combined with the control of interlayer water and K + ion content. Structure refinement of KVO-DMAE-200 further corroborates the behavior observed during K + ion cycling, connecting structural and compositional characteristics to the improved rate capability. This work demonstrates how proper synthetic methodology can cause downstream effects in the control of structure, chemical composition, and morphology of nanostructured layered oxide materials, which is necessary for development of future materials for beyond-Li-ion battery technologies.

25 ENERGY STORAGE↗

Stable Symmetry-Protected Topological Phases in Systems with Heralded Noise

Here, we present a family of local quantum channels whose steady-states exhibit stable mixed-state symmetry-protected topological (SPT) order. Motivated by recent experimental progress on "erasure conversion" techniques that allow one to identify ($\textit{herald}$) decoherence processes, we consider open systems with biased erasure noise, which leads to strongly symmetric heralded errors. We utilize this heralding to construct a local correction protocol that effectively confines errors into short-ranged pairs in the steady-state. Using a combination of numerical simulations and mean-field analysis, we show that our protocol stabilizes SPT order against a sufficiently low rate of decoherence. As the rate of heralded noise increases, SPT order is eventually lost through a directed percolation transition. We further find that while introducing unheralded errors destroys SPT order in the limit of long length- and time-scales, the correction protocol is sufficient for ensuring that local SPT order persists, with a correlation length that diverges as $\xi \sim (1-f_e)^{-1/2}$, where $f_e$ is the fraction of errors that are heralded.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The Thermococcales as a model system: historical perspectives and emerging tools

Thermococcales are among the most widely studied hyperthermophilic Archaea and have become key models for understanding life at extreme temperatures. Early work in the 1980s culminated in the isolation of novel Thermococcales species from hydrothermal vents that grew rapidly, tolerated extreme heat, and metabolized diverse substrates, making them uniquely amenable for laboratory studies. Their thermostable enzymes and emerging genetic tools facilitated detailed investigations of core processes such as DNA replication, repair, and transcription under conditions that challenge most life forms. These practical advantages, together with the accumulation of tools and protocols, cemented the role of Thermococcales as a model system. Here, we recount how chance discoveries, environmental adaptations, and experimental practicality intersected to establish Thermococcales as a central model for studying archaeal biology and extremophile physiology.

59 BASIC BIOLOGICAL SCIENCES↗

An open-access simulated earthquake ground-motion database for an M7 Hayward Fault earthquake in the San Francisco Bay Region

Comprehensive understanding of earthquake ground motions, particularly in the near-fault region of large-magnitude events, is limited by gaps in strong-motion data. This challenge is prominent in areas with high seismic hazard but infrequent large earthquakes where data is sparse and difficult to interpret. These data limitations lead to uncertainties in the development of site-specific ground motions, which are crucial for engineering risk assessments. To address these challenges, physics-based regional-scale ground-motion simulations have been developed. With the emergence of exaflop-scale computing ecosystems, it is now possible to simulate regional earthquake processes at unprecedented fidelity and generate the large number of fault rupture realizations necessary to characterize both intra- and inter-event ground-motion variability. This article introduces a new database of simulated earthquake ground motions, created for applications in earthquake engineering, earthquake planning, and emergency response. The inaugural version of the database features simulated ground motions for a magnitude 7 Hayward Fault earthquake in the San Francisco Bay Region (SFBR), using the EarthQuake SIMulation (EQSIM) simulation framework and the Graves–Pitarka kinematic rupture model. The aim is to provide high-fidelity, spatially dense, three-component motions generated on the Department of Energy’s (DOE) newest generation of graphics processing unit (GPU)-accelerated supercomputers. These motions are being made openly available to the engineering, scientific, and disaster planning communities. In addition, this work develops protocols for the efficient dissemination of these large data sets and emphasizes community engagement to build confidence in their application. This article discusses the methodology behind the data, underlying software verification and validation, scalable data management, and a user interface for data access. The goal is to facilitate widespread use and elicit expert feedback to maximize the utility and exploitation of simulated motions. While the initial focus is on the San Francisco Region, simulations for additional regions will be added as the DOE program progresses.

Simulated ground-motion database↗

Specifying real-time systems with interval logic

Pure temporal logic makes no reference to time. An interval temporal logic and an extension to that logic which includes real time constraints are described. The application of this logic by giving a specification for the well-known lift (elevator) example is demonstrated. It is shown how interval logic can be extended to include a notion of process. How the specification language and verification environment of EHDM could be enhanced to support this logic is described. A specification of the alternating bit protocol in this extended version of the specification language of EHDM is given.

Rushby, John↗

Atmospheric Correction Inter-Comparison eXercise

The Atmospheric Correction Inter-comparison eXercise (ACIX) is an international initiative with the aim to analyse the Surface Reflectance (SR) products of various state-of-the-art atmospheric correction (AC) processors. The Aerosol Optical Thickness (AOT) and Water Vapour (WV) are also examined in ACIX as additional outputs of AC processing. In this paper, the general ACIX framework is discussed; special mention is made of the motivation to initiate the experiment, the inter-comparison protocol, and the principal results. ACIX is free and open and every developer was welcome to participate. Eventually, 12 participants applied their approaches to various Landsat-8 and Sentinel-2 image datasets acquired over sites around the world. The current results diverge depending on the sensors, products, and sites, indicating their strengths and weaknesses. Indeed, this first implementation of processor inter-comparison was proven to be a good lesson for the developers to learn the advantages and limitations of their approaches. Various algorithm improvements are expected, if not already implemented, and the enhanced performances are yet to be assessed in future ACIX experiments.

Processors inter-comparison↗

A Distributed Approach to High-Rate Delay Tolerant Networking Within a Virtualized Environment

The High-Rate Delay Tolerant Networking (HDTN) project has taken a distributed service-based approach to the development of a highly efficient delay tolerant networking (DTN) implementation. Through the analysis of many DTN implementations, system and mission requirements as well as the DTN protocol specifications, HDTN has worked to infuse modern computing technologies into the NASA approach to interplanetary networking. The initial use case of the HDTN software runs on a hypervisor representative of the International Space Station (ISS) DTN Gateway. In this scenario, multiple emulated payloads will send science data through HDTN to a mission operations center. HDTN will provide store and forward capability as well as network flow management. This paper discusses the infusion path of cognitive networking technologies in the NASA SCaN networks using the DTN architecture and protocols as the basis for cognitive routing and network management capabilities. HDTN has been developing the Bundle Protocol encoding and decoding mechanisms and messaging framework that can be used as the basis for integrating DTN with various learning and decision-making processes. The concepts of distributed computing, network virtualization, software defined networking and delay tolerant networking are basic building blocks which will further the development of cognitive networking. In addition to discussion of the HDTN software development and testing, this paper examines the role that each of these technologies play in the evolution of the current state of space networking into an intelligent network of networks.

Delay Tolerant Networking↗

A Distributed Approach to High-Rate Delay Tolerant Networking Within a Virtualized Environment

The High-Rate Delay Tolerant Networking (HDTN) project has taken a distributed service-based approach to the development of a highly efficient delay tolerant networking (DTN) implementation. Through the analysis of many DTN implementations, system and mission requirements as well as the DTN protocol specifications, HDTN has worked to infuse modern computing technologies into the NASA approach to interplanetary networking. The initial use case of the HDTN software runs on a hypervisor representative of the International Space Station (ISS) DTN Gateway. In this scenario, multiple emulated payloads will send science data through HDTN to a mission operations center. HDTN will provide store and forward capability as well as network flow management. This paper discusses the infusion path of cognitive networking technologies in the NASA Space Communications and Navigation (SCaN) networks using the DTN architecture and protocols as the basis for cognitive routing and network management capabilities. HDTN has been developing the Bundle Protocol encoding and decoding mechanisms and messaging framework that can be used as the basis for integrating DTN with various learning and decision-making processes. The concepts of distributed computing, network virtualization, software defined networking and delay tolerant networking are basic building blocks which will further the development of cognitive networking. In addition to discussion of the HDTN software development and testing, this paper examines the role that each of these technologies play in the evolution of the current state of space networking into an intelligent network of networks.

Rachel Mary Dudukovich↗

Investigating Neighbor Discovery for High-Rate Delay Tolerant Networking

A neighbor discovery protocol that enables the dynamic discovery of nodes for NASA Glenn Research Center’s High Rate Delay Tolerant Networking (HDTN) project is needed to satisfy mission scalability and interoperability objectives. The purpose of this study is to primarily examine a DTN IP neighbor discovery (IPND) implementation to understand the inner workings of the protocol before approaching a neighbor discovery implementation for the HDTN project. Using a rust-based DTN IPND implementation, this study analyzed the neighbor discovery process. DTN IPND was found to help meet both mission scalability and interoperability objectives by enabling dynamic routing capabilities. This study definitively answers the question regarding mission scalability and interoperability concerns. Further studies are needed to establish the most optimal neighbor discovery implementation for HDTN.

Prash Choksi↗

Location, location: deciphering the significance of in-situ hydrogen analyses of Martian meteorite phases

Understanding how inner planets acquired their volatiles such as hydrogen (H) is fundamental to constrain models of solar system formation [e.g. 1]. One avenue of estimating the H content and isotopic characteristics of differentiated planets is to analyze the samples we have from them as meteorites. Ideally, the H content and isotopic characteristic of the mantle sources of these igneous rocks should give insight into the volatile origin of each planetary body. The mantle H signatures can be estimated from that of the parent melt, which in turn may be derived from that of the first crystallized phases. However, we will illustrate the processes that can modify the H content and D/H ratios of pyroxene, olivine and feldspar in selected Martian meteorites relative to those of their mantle sources, with two key protocols for SIMS analysis. The first key is to put each analysis in textural context ("location, location"). In particular, of prime importance is whether an analysis is done at the center or the edge of a mineral grain, close or far from a shock disturbed area, and in a mineral crystallized at the beginning or late in the differentiation sequence. Accompanying the H analyses done by SIMS with major and trace element data at the same analysis locations allows to constrain the history of crystallization, cooling, alteration and shock of the meteorite. For example, volcanic degassing can be evidenced by decreasing water contents and increasing D/H ratios from core to edge of nakhlite pyroxenes [2]. Traverses of H analyses in pyroxene and maskelynite in shergottite LAR 06319 provide examples of H contents and D/H ratios modified during degassing following shock [3]. The second key is to assess if the area analyzed by SIMS has shock generated damage of the mineral structure, as will be shown in pyroxene and olivine from shergottite RBT 04262. Olivine in shergottites have too high water contents to be explained with an igneous origin and their D/H ratios are more consistent with terrestrial alteration, as observed before [4]. A review of all these processes shows how careful one has to be prior to using H measurements in meteorites to infer the origin and amount of water in differentiated planetary interiors.

A.H. Peslier↗

Modular Processing of Flare Gas for Carbon Nanoproducts

This project demonstrated the technical viability and economic promise of a modular system for converting flared natural gas into valuable carbon nanoproducts (CNPs) through catalytic chemical vapor deposition (CVD). All major project milestones were successfully completed, including reactor design and commissioning, catalyst development, process optimization, technoeconomic analysis, and application testing in concrete systems. The overarching goal was to create a scalable, field-deployable process that valorizes stranded methane by producing high-value carbon materials for use in cementitious composites. At the lab scale, the team designed and built a fluidized bed reactor optimized for use with silica fume-supported nickel catalysts synthesized via atomic layer deposition (ALD). A statistically designed sintering study enabled precise tuning of nickel nanoparticle size, identifying the influence of oxygen partial pressure, time, and temperature on catalyst morphology and performance. These insights allowed the team to target catalyst conditions that maximize carbon nanofilament growth. Subsequent CVD experiments achieved up to 31.8 wt% carbon deposition under optimized conditions, with TEM confirming the presence of nanofilament structures and sustained hydrogen evolution during reaction. Reactor upgrades and empirical fluidization studies supported the development of reliable, repeatable experimental protocols. The modular pilot-scale skid reactor was fully constructed, instrumented, and commissioned. Capable of operating at 675–800°C and pressures up to 290 psig, the system was designed for continuous operation at a carbon production rate of 1 kg/hr. Initial demonstration runs confirmed solids handling, thermal control, and system leak-tightness, although a critical reactor component (the downfeed tube) was inadvertently omitted during final assembly. This omission limited gas–solid contact and prevented meaningful carbon deposition during pilot-scale CVD runs. Nonetheless, the system operated safely under design conditions, and the root cause of performance limitations was clearly identified. Complementary work on UHPC formulations demonstrated that small additions of carbon nanoproducts, including those derived from flare gas, can significantly enhance mechanical performance while preserving workability. A comprehensive study of CNF dispersion techniques and mix design optimization led to a clear protocol for integrating these nanomaterials into concrete. Incorporation of CNPs improved flexural toughness and reduced porosity, supporting their use in high-performance infrastructure applications. A technoeconomic analysis (TEA) confirmed that this process can produce CNP-loaded catalyst material at a levelized cost below $\$$7/kg across a range of catalyst loadings and reaction yields. With estimated market values for the carbon composite product ranging from $\$$14 to over $\$$60/kg, and the ability to blend CNPs into concrete at sub-percent levels with less than 10% added cost, the system presents a compelling economic case. While additional engineering work is needed to optimize fluidization and heat transfer at scale, this project establishes a strong foundation for commercial development. The process is not only technically sound but also economically promising, representing a viable pathway for flare gas mitigation through modular carbon nanomaterial production.

03 NATURAL GAS↗

Modelling high data rate communication network access protocol

Modeling of high data rate communication systems is different from the low data rate systems. Three simulations were built during the development phase of Carrier Sensed Multiple Access/Ring Network (CSMA/RN) modeling. The first was a model using SIMCRIPT based upon the determination and processing of each event at each node. The second simulation was developed in C based upon isolating the distinct object that can be identified as the ring, the message, the node, and the set of critical events. The third model further identified the basic network functionality by creating a single object, the node which includes the set of critical events which occur at the node. The ring structure is implicit in the node structure. This model was also built in C. Each model is discussed and their features compared. It should be stated that the language used was mainly selected by the model developer because of his past familiarity. Further the models were not built with the intent to compare either structure or language but because the complexity of the problem and initial results contained obvious errors, so alternative models were built to isolate, determine, and correct programming and modeling errors. The CSMA/RN protocol is discussed in sufficient detail to understand modeling complexities. Each model is described along with its features and problems. The models are compared and concluding observations and remarks are presented.

Khanna, S.↗