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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Kaona: Deep Searching and Curating Data from Aviation Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given to augmenting existing processes for mining these safety reporting system databases. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety database mining activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using publicly available NASA’s ASRS narratives and another using publicly available C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

ASRS↗
NASA NTRSDate not supplied

Kaona: Deep Searching and Curating Aviation Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given in augmenting existing processes of safety reporting systems. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety reporting systems activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using all public NASA's ASRS narratives and another using all public C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

asrs↗
DOE OSTI2023

Discovery of multi-functional polyimides through high-throughput screening using explainable machine learning

Polyimides have been widely used in modern industries because of their excellent mechanical and thermal properties, e.g., high-temperature fuel cells, displays, and aerospace composites. However, it usually takes decades of experimental efforts to develop a successful product. Aiming to expedite the discovery of high-performance polyimides, we utilize computational methods of machine learning (ML) and molecular dynamics (MD) simulations. Our study provides compelling evidence for the effectiveness of a data-driven approach in discovering novel polyimides. We first build a comprehensive library of more than 8 million hypothetical polyimides based on the polycondensation of existing dianhydride and diamine/diisocyanate molecules. Then we establish multiple ML models for the thermal and mechanical properties of polyimides based on their experimentally reported values, including glass transition temperature, Young’s modulus, and tensile yield strength. The obtained ML models demonstrate excellent predictive performance in identifying the key chemical substructures influencing the thermal and mechanical properties of polyimides. The use of explainable machine learning describes the effect of chemical substructures on individual properties, from which human experts can understand the cause of the ML model decision. Applying the well-trained ML models, we obtain property predictions of the 8 million hypothetical polyimides. Then, we screen the whole hypothetical dataset and identify three (3) best-performing novel polyimides that have better-combined properties than existing ones through Pareto frontier analysis. For an easy query of the discovered high-performing polyimides, we also create an online platform https://polyimide-explorer.herokuapp.com/ that embeds the developed ML model with interactive visualization. Furthermore, we validate the ML predictions through all-atom MD simulations and examine their synthesizability. The MD simulations are in good agreement with the ML predictions and the three novel polyimides are predicted to be easy to synthesize via Schuffenhauer’s synthetic accessibility score. Following the proposed ML guidance, we successfully synthesized a novel polyimide and the experimentally obtained high glass transition/thermal decomposition temperature demonstrated its excellent thermal stability. Here our study demonstrates an efficient way to expedite the discovery of novel polymers using ML prediction and MD validation. The high-throughput screening of a large computational dataset can serve as a general approach for new material discovery in other polymeric material exploration problems, such as organic photovoltaics, polymer membranes, and dielectrics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

Remote Sensing of Urban Thermal Landscape Characteristics and Their Affects on Local and Regional Meteorology and Air Quality: An Overview of NASA EOS-IDS Project Atlanta

As an entity, the city is a manifestation of human "management" of the land. The act of city-building, however, drastically alters the biophysical environment, which ultimately, impacts local and regional land-atmosphere energy exchange processes. Because of the complexity of both the urban landscape and the attendant energy fluxes that result from urbanization, remote sensing offers the only real way to synoptically quantify these processes. One of the more important land-atmosphere fluxes that occurs over cities relates to the way that thermal energy is partitioned across the heterogeneous urban landscape. The individual land cover and surface material types that comprise the city, such as pavements and buildings, each have their own thermal energy regimes. As the collective urban landscape, the individual thermal energy responses from specific surfaces come together to form the urban heat island phenomena, which prevails as a dome of elevated air temperatures over cities. Although the urban heat island has been known to exist for well over 150 years, it is not understood how differences in thermal energy responses for land covers across the city interact to produce this phenomenon, or how the variability in thermal energy responses from different surface types drive its development. Additionally, it can be hypothesized that as cities grow in size through time, so do their urban heat islands. The interrelationships between urban sprawl and the respective growth of the urban heat island, however, have not been investigated. Moreover, little is known of the consequential effects of urban growth, land cover change, and the urban heat island as they impact local and regional meteorology and air quality.

Quattrochi, Dale A.↗
DOE OSTI2021

Trust in Artificial Intelligence: Meta-Analytic Findings

Objective The present meta-analysis sought to determine significant factors that predict trust in artificial intelligence (AI). Such factors were divided into those relating to (a) the human trustor, (b) the AI trustee, and (c) the shared context of their interaction. Background There are many factors influencing trust in robots, automation, and technology in general, and there have been several meta-analytic attempts to understand the antecedents of trust in these areas. However, no targeted meta-analysis has been performed examining the antecedents of trust in AI. Method Data from 65 articles examined the three predicted categories, as well as the subcategories of human characteristics and abilities, AI performance and attributes, and contextual tasking. Lastly, four common uses for AI (i.e., chatbots, robots, automated vehicles, and nonembodied, plain algorithms) were examined as further potential moderating factors. Results Results showed that all of the examined categories were significant predictors of trust in AI as well as many individual antecedents such as AI reliability and anthropomorphism, among many others. Conclusion Overall, the results of this meta-analysis determined several factors that influence trust, including some that have no bearing on AI performance. Additionally, we highlight the areas where there is currently no empirical research. Application Findings from this analysis will allow designers to build systems that elicit higher or lower levels of trust, as they require.

Behavioral Sciences↗
DOE OSTI2024

2023 Southeast Decarbonization Workshop

Decarbonization refers to a large-scale shift away from fossil fuel sources for energy production and toward energy sources, energy end-use practices, and land management approaches that do not result in a net increase of carbon dioxide in the atmosphere. Decarbonization in the Southeastern United States is distinguished from that of other regions in the country by its potential impact on historically underserved populations and the ways this region’s human–environmental systems are predicted to fare in a climate-altered world. In parallel, ensuring a clean energy transition requires the ability to engage entire communities that are motivated to learn, build, and encourage the spread of so-called clean tech. In contrast to other technology trends from the past century, the foundation of clean tech is a shared sense of purpose—a collective strategy to mitigate the threats of climate change and support a better environment for everyone. As seen in the Office of Science and Technology Policy’s (OSTP’s) Net-Zero Technology Action Plan (2023), decarbonization is best accelerated by simultaneous investments in Innovation, Demonstration, and Deployment of technology in tandem with intentional policy and community-based solutions. The 2023 Southeast Decarbonization Workshop, hosted by the Georgia Institute of Technology (Georgia Tech) and Oak Ridge National Laboratory (ORNL), aimed to bring together members of our communities and a group of regional experts to strategize about opportunities in this important area, as well as to incorporate the important pillar of System Interactions to bridge the gap between clean tech’s intent and its impact.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Integration Test and Evaluation (IT&E) Flight Test Series 6 Live Virtual Constructive - Distributed Environment (LVC-DE) Test Report

The goals of the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) (also UAS-NAS) Project are to reduce the barriers for UAS access and its integration into the NAS. The UAS-NAS project and industry stakeholders conducted a series of flight tests integrating technologies from the Modeling & Simulation (M&S), Human Systems Integration (HSI), and Communication and Control (C2), and Integration, Test & Evaluation (IT&E) research areas. The last of the flight test series, Flight Test Series 6 (FT6) was conducted in late 2019 and focused on evaluating the interaction of the airborne non-cooperative surveillance system and the Detect and Avoid (DAA) technology. The DAA system generated conflict alert and guidance for pilots using a Research Ground Control System (RGCS) to avoid intruder aircraft. The conflict alerting and guidance information was presented on the RGCS’s display using symbology developed by the human factors team. The objective of FT6 was to investigate the interoperability of Low Size, Weight, and Power (Low SWaP) sensors with the DAA alerting, guidance, and display requirements. To support this goal, the distributed test environments (DTE) were developed at Ames Research Center (ARC) and Armstrong Flight Research Center (AFRC) and securely linked over a Virtual Private Network (VPN). These environments took advantage of existing Live Virtual Constructive (LVC) technologies to support research observation at both Centers with the insertion of live UAS and manned intruder aircraft into a simulated NAS environment with Air Traffic Control (ATC) and constructive manned aircraft. The experiment was distributed between AFRC flight operations and research facilities and the Distributed Simulation Research Laboratory (DSRL) and Software Development Laboratory (SDL) in building N243 at ARC. The Air Traffic Controller and pseudo pilots operated from the DSRL and SDL, respectively, using the Multi-Aircraft Control System (MACS). The test subject and researchers operated from the Research Ground Control Station (RGCS) at AFRC using the Vigilant Spirit Control Station (VSCS) and associated DAA software and displays. Flight Operation for the unmanned aircraft (UA) and manned intruder traffic was conducted at AFRC. Virtual traffic was managed by ARC. Voice distribution was accomplished using a combination of disparate communication systems at ARC and AFRC. The purpose of this document is to record the development, design, and execution of activities in support of the FT6 efforts from the perspective of the ARC IT&E team. Furthermore, the Armstrong IT&E team has published a thorough FT6 Test Report, with emphasis on flight test support, facilities and vehicle development; this report complements the Armstrong report. Analysis of collected FT6 data will be conducted and reported by the M&S and HSI teams and will be published in separate reports.

UAS-NAS↗
NASA NTRS1998

Intelligent Systems and Advanced User Interfaces for Design, Operation, and Maintenance of Command Management Systems

Historically Command Management Systems (CMS) have been large, expensive, spacecraft-specific software systems that were costly to build, operate, and maintain. Current and emerging hardware, software, and user interface technologies may offer an opportunity to facilitate the initial formulation and design of a spacecraft-specific CMS as well as a to develop a more generic or a set of core components for CMS systems. Current MOC (mission operations center) hardware and software include Unix workstations, the C/C++ and Java programming languages, and X and Java window interfaces representations. This configuration provides the power and flexibility to support sophisticated systems and intelligent user interfaces that exploit state-of-the-art technologies in human-machine systems engineering, decision making, artificial intelligence, and software engineering. One of the goals of this research is to explore the extent to which technologies developed in the research laboratory can be productively applied in a complex system such as spacecraft command management. Initial examination of some of the issues in CMS design and operation suggests that application of technologies such as intelligent planning, case-based reasoning, design and analysis tools from a human-machine systems engineering point of view (e.g., operator and designer models) and human-computer interaction tools, (e.g., graphics, visualization, and animation), may provide significant savings in the design, operation, and maintenance of a spacecraft-specific CMS as well as continuity for CMS design and development across spacecraft with varying needs. The savings in this case is in software reuse at all stages of the software engineering process.

Mitchell, Christine M.↗
NASA NTRS2016

Review of NASA's Evidence Reports on Human Health Risks

NASA has requested a study from the Institute of Medicine (IOM) to provide an independent review of more than 30 evidence reports on human health risks for long duration and exploration spaceflight. The evidence reports, which are publicly available, are categorized into five broad categories: (1) behavioral health and performance; (2) human health countermeasures (with a focus on bone metabolism and orthopedics, nutrition, immunology, and cardiac and pulmonary physiology); (3) radiation; (4) human factors issues; and (5) exploration medical capabilities. The reports are revised on an ongoing basis to incorporate new scientific information. In conducting this study, an IOM ad hoc committee will build on the 2008 IOM report Review of NASA's Human Research Program Evidence Books. That report provided an assessment of the process used for developing the evidence reports and provided an initial review of the evidence reports that had been completed at that time. Each year, NASA staff will identify a set of evidence reports for committee review. Over the course of the study all evidence reports will be reviewed. The committee will hold an annual scientific workshop to receive input on the evidence reports it is reviewing that year and an update on the recent literature. The committee will issue an annual letter report that addresses the following questions relevant to each evidence report: 1. Does the evidence report provide sufficient evidence, as well as sufficient risk context, that the risk is of concern for long-term space missions? 2. Does the evidence report make the case for the research gaps presented? 3. Are there any additional gaps in knowledge or areas of fundamental research that should be considered to enhance the basic understanding of this specific risk? 4. Does the evidence report address relevant interactions among risks? 5. Is input from additional disciplines needed? 6. Is the breadth of the cited literature sufficient? 7. What is the overall readability and quality? 8. Is the expertise of the authors sufficient to fully cover the scope of the given risk? 9. Has the evidence report addressed previous recommendations made by the IOM in the 2008 letter report?

Scott-Conner, Carol E. H.↗
NASA NTRS1992

Investigation of the effects of Extra Vehicular Activity (EVA) and Launch and Entry (LES) gloves on performance

Human capabilities such as dexterity, manipulability, and tactile perception are unique and render the hand as a very versatile, effective and a multipurpose tool. This is especially true for unknown environments such as the EVA environment. In the microgravity environment interfaces, procedures, and activities are too complex, diverse, and defy advance definition. Under these conditions the hand becomes the primary means of locomotion, restraint, and material handling. Facilitation of these activities, with simultaneous protection from the cruel EVA environment are the two, often conflicting, objectives of glove design. The objectives of this study was (1) to assess the effects of EVA gloves at different pressures on human hand capabilities, (2) to devise a protocol for evaluating EVA gloves, (3) to develop force time relations for a number of EVA glove pressure combinations, and (4) to evaluate two types of launch and entry suit gloves. The objectives were achieved through three experiments. The experiments for achieving objectives 1, 2, and 3 were performed in the glove box in building 34. In experiment 1 three types of EVA gloves were tested at five pressure differentials. A number of performance measures were recorded. In experiment 2 the same gloves as in experiment 1 were evaluated in a reduced number of pressure conditions. The performance measure was endurance time. Six subjects participated in both the experiments. In experiment 3 two types of launch and entry suit gloves were evaluated using a paradigm similar to experiment 1. Currently the data is being analyzed. However for this report some summary analyses have been performed. The results indicate that a) With EVA gloves strength is reduced by nearly 50 percent, b) performance decrements increase with increasing pressure differential, c) TMG effects are not consistent across the three gloves tested, d) some interesting gender glove interactions were observed, some of which may have been due to the extent (or lack of) fit of the glove to the hand, and e) differences in performance exist between partial pressure suit glove and full pressure suit glove, especially in the unpressurized condition.

Bishu, Ram R.↗
NASA NTRSDate not supplied

Quantifying Changes in Urban Albedo with NASA Earth Observations to Reduce the Urban Heat Island Effect in Cambridge, Massachusetts

Elevated temperatures resulting from the urban heat island (UHI) effect can have widespread impacts on human health, infrastructure, and ecosystems. These impacts can be exacerbated by changes in climate and extreme variation in regional temperature. By 2030, experts expect Cambridge, Massachusetts will experience warmer than average temperatures, more heat waves, and triple the number of abnormally warm days above 90°F per year. The NASA DEVELOP Program partnered with the City of Cambridge’s Community Development Department and the American Geophysical Union’s Thriving Earth Exchange to inform ongoing efforts aimed at reducing the impacts of urban heat in the city of Cambridge. The team used scenes obtained from High Resolution Orthoimagery and the National Agriculture Imagery Program in conjunction with building footprint data, to calculate rooftop albedo between 2008 and 2018. Using these results, maps displaying building-specific variation in albedo across Cambridge were created. A nighttime land surface temperature (LST) record for June, July, and August between 2003 and 2019 was constructed using the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) nighttime LST product. Lastly, temperature anomalies were calculated for Cambridge using seasonally averaged nighttime LST values obtained from Aqua MODIS to display ‘hot spots’ for summers between 2004 and 2019. The results of this project were then incorporated into an interactive ArcGIS Dashboard. This work will allow end users to explore spatial and temporal trends in albedo, nighttime LST, and temperature anomalies to assess whether the City of Cambridge is successfully reducing the effects of UHIs.

NASA DEVELOP↗
DOE OSTI2023

CASTLE: Conflict Analysis Strategy Testing Laboratory Environment v.1.0.0

SAND2024-01743O The Conflict Analysis Strategy Testing Laboratory Environment (CASTLE) is a software framework that enables and simplifies building a novel, turn-based strategy game in which it can define its own rules, maps, pieces, and interactions. The software is for novice to experienced programmers with some knowledge of Unity3D, a tool used in game production. CASTLE includes a library of common game mechanics used for strategic wargames and traditional board games, such as cards, tokens, dice, and grid maps. It follows design principles popularized by the video game industry and uses singletons for managing portions of the code. CASTLE builds on Unity's component-based design and can respond to engine events during execution. Among the numerous user-friendly features: Build games quickly and cost-effectively Network in real-time and apply data to new games developed on the framework Host multiple participants online Connect rule- or machine learning-based agents to a CASTLE game to serve as opponents or to simulate games Collect data collection from players and in-game behaviors Create a survey to gather demographics or opinions from players Store data locally or save it to an external database through Representational State Transfer (REST) functions CASTLE, which was prototyped using Microsoft Azure, is also designed for easily distributing online games using popular cloud services. The multiplayer functionality includes an agent interface, allowing developers to construct AI players that can substitute for humans in any of the games. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fabian, Nathan↗
NASA NTRS2007

Toxicity of Lunar and Martian Dust Simulants to Alveolar Macrophages Isolated from Human Volunteers

NASA is planning to build a habitat on the Moon and use the Moon as a stepping stone to Mars. JSC-1, an Arizona volcanic ash that has mineral properties similar to lunar soil, is used to produce lunar environments for instrument and equipment testing. NASA is concerned about potential health risks to workers exposed to these fine dusts in test facilities. The potential toxicity of JSC-1 and a Martian soil simulant (JSC-Mars-1, a Hawaiian volcanic ash) was evaluated using human alveolar macrophages (HAM) isolated from volunteers; titanium dioxide and quartz were used as reference dusts. This investigation is a prerequisite to studies of actual lunar dust. HAM were treated in vitro with these test dusts for 24 h; assays of cell viability and apoptosis showed that JSC-1 and TiO2 were comparable, and more toxic than saline control, but less toxic than quartz. HAM treated with JSC-1 or JSC-Mars 1 showed a dose-dependent increase in cytotoxicity. To elucidate the mechanism by which these dusts induce apoptosis, we investigated the involvement of the scavenger receptor (SR). Pretreatment of cells with polyinosinic acid, an SR blocker, significantly inhibited both apoptosis and necrosis. These results suggest HAM cytotoxicity may be initiated by interaction of the dust particles with SR. Besides being cytotoxic, silica is known to induce shifting of HAM phenotypes to an immune active status. The immunomodulatory effect of the simulants was investigated. Treatment of HAM with either simulant caused preferential damage to the suppressor macrophage subpopulation, leading to a net increase in the ratio of activator (RFD1+) to suppressor (RFD1+7+) macrophages, a result similar to treatment with silica. It is recommended that appropriate precautions be used to minimize exposure to these fine dusts in large-scale engineering applications.

Latch, Judith N.↗
NASA NTRSDate not supplied

NASA Earth System Digital Twins (ESDT) For a Sustainable Future

An Earth System Digital Twin (or ESDT) is an Information System for Understanding, Forecasting, and Conjecturing the complex interconnections among Earth systems, including anthropomorphic forcings and impacts to humanity. More specifically, an Earth System Digital Twin is a dynamic and interactive information system that first provides a digital replica of the past and current states of the Earth or Earth system, as accurately and timely as possible (i.e., the “What Now”); second allows for computing forecasts of future states under nominal assumptions and based on the current replica (i.e., the “What Next”); and third offers the capability to investigate many hypothetical scenarios under varying impact assumptions (i.e., the “What If”). The full power of digital twins is that, through an integrated representation and standardized tools and software technologies, the same digital replica can address the needs of multiple users at various resolutions (spatial and temporal) and for various applications (science, economic, policy, etc.) – “from farmer to scientist”. Since 2020, NASA’s Earth Science Technology’s Intelligent Systems Programs have started defining and investigating ESDTs. After several workshops, more than 15 projects have been funded to develop technologies and components as well as a few prototype ESDT systems. An ESDT architecture framework has been defined, and it is now being used to develop a Coastal Zone Digital Twin (CZ-DT), in coordination with NOAA and CNES. Additional projects have also just been selected to build additional ESDT technologies and prototypes. The details of these Programs will be detailed at the conference.

Earth Science Remote Sensing; Information Systems↗
NASA NTRSDate not supplied

Slippery Lubricant-Infused Silica Nanoparticulate Film Processing for Anti-Biofouling Applications

Microbial biofilm build-up in water distribution systems can pose a risk to human health and pipe material integrity. The impact is more devastating in space stations and to astronauts due to the isolation from necessary replacement parts and medical resources. As a result, there is a need for coatings to be implemented onto the inner region of the pipe to minimize the adherence and growth of biofilms. Lubricant-infused surfaces has been one such interesting material for anti-biofouling applications in which their slippery property promotes repellence to many liquids and thus prevents bacterial adherence. Textured and porous films are suitable substrate candidates to infuse and contain the lubricant. However, there is little investigation in utilizing a nanoporous thin film as the substrate material for lubricant infusion. A nanoporous film has high porosity within the structure which can promote greater lubricant infusion and retention. The implementation as a thin film structure aids to reduce material consumption and cost. In our study, we utilized a well-studied nanoporous thin film fabricated via layer-by-layer assembly of polycations and colloid silica and calcination for greater stability. The film was further functionalized to promote fluorinated groups upon the surface and pores of the film, which then could interact with a fluorinated lubricant. The pristine nanoporous film was characterized to determine its morphology, thickness, wettability, and porosity. The lubricant-infused film was then tested for its lubricant layer stability upon various washing conditions and its performance against bacterial biofilm adherence as a result of its slippery and thus anti-biofouling property.

biofilm↗
NASA NTRS2000

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

We use the term "Grid" to refer to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. This infrastructure includes: (1) Tools for constructing collaborative, application oriented Problem Solving Environments / Frameworks (the primary user interfaces for Grids); (2) Programming environments, tools, and services providing various approaches for building applications that use aggregated computing and storage resources, and federated data sources; (3) Comprehensive and consistent set of location independent tools and services for accessing and managing dynamic collections of widely distributed resources: heterogeneous computing systems, storage systems, real-time data sources and instruments, human collaborators, and communications systems; (4) Operational infrastructure including management tools for distributed systems and distributed resources, user services, accounting and auditing, strong and location independent user authentication and authorization, and overall system security services The vision for NASA's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks. Such Grids will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. Examples of these problems include: (1) Coupled, multidisciplinary simulations too large for single systems (e.g., multi-component NPSS turbomachine simulation); (2) Use of widely distributed, federated data archives (e.g., simultaneous access to metrological, topological, aircraft performance, and flight path scheduling databases supporting a National Air Space Simulation systems}; (3) Coupling large-scale computing and data systems to scientific and engineering instruments (e.g., realtime interaction with experiments through real-time data analysis and interpretation presented to the experimentalist in ways that allow direct interaction with the experiment (instead of just with instrument control); (5) Highly interactive, augmented reality and virtual reality remote collaborations (e.g., Ames / Boeing Remote Help Desk providing field maintenance use of coupled video and NDI to a remote, on-line airframe structures expert who uses this data to index into detailed design databases, and returns 3D internal aircraft geometry to the field); (5) Single computational problems too large for any single system (e.g. the rotocraft reference calculation). Grids also have the potential to provide pools of resources that could be called on in extraordinary / rapid response situations (such as disaster response) because they can provide common interfaces and access mechanisms, standardized management, and uniform user authentication and authorization, for large collections of distributed resources (whether or not they normally function in concert). IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: the scientist / design engineer whose primary interest is problem solving (e.g. determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user is the tool designer: the computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. The results of the analysis of the needs of these two types of users provides a broad set of requirements that gives rise to a general set of required capabilities. The IPG project is intended to address all of these requirements. In some cases the required computing technology exists, and in some cases it must be researched and developed. The project is using available technology to provide a prototype set of capabilities in a persistent distributed computing testbed. Beyond this, there are required capabilities that are not immediately available, and whose development spans the range from near-term engineering development (one to two years) to much longer term R&D (three to six years). Additional information is contained in the original.

Johnston, William E.↗
NASA NTRS2019

Current NASA In-Situ Resource Utilization (ISRU) Strategic Vision

Perform development to TRL 5/6 through ground demonstration in relevant environment. Perform component/subscale subsystem flight demonstrations on small/mid-size landers. Assess and characterize water in volatiles in lunar polar shadowed regions and craters. Reduce risk of ISRU for mission critical consumables through Integrated End-to-End Flight Demonstrations (pilot scale). Establish initial Human Mission Scale production capability to promote sustainable operations and as anchor for commercial involvement. Identify and characterize polar region environment and resources/volatiles for Science and future Exploration/Commercial applications. Provide ground-truth physical, mineral, and water/volatile resource characteristic information at multiple locations to provide geological context for science-focused theories of volatile placement and initial mining assessments.Test technologies and processes to reduce risk of future extraction/mining systems. Quantify concentration and lateral/vertical distribution of resources/volatiles. Utilize ISRU capabilities to Extend and Enhance Human Lunar Exploration Missions. Provide oxygen (and fuel) to enable reusable human lunar lander (10+ MT/yr O2)Process carbon-based crew waste/trash into gases and propellants; can reduce logistics while minimizing public perception issues (alternative is conversion to radiation shielding). Scavenge unused propellants and hardware from spent landers. Metal extraction from regolith as feedstock for in situ and in space manufacturing demonstrations. Civil engineering and construction aimed at future outpost/infrastructure build-up. Develop and Demonstrate ISRU for Human Mars Missions. ISRU for propellant production (10-15 MT/yr); Liquefy, store, transfer, and refuel ascent vehicle. Use Moon for operational experience and mission validation for Mars: Pre-deployment & remote activation and operation without crew. Storing and transferring mission consumables Landing crew with empty tanks with ISRU propellants already made and waiting. Support/Promote Commercialization of Space. Large scale polar ice mining (100+ MT/yr water)O2/H2 propulsion for landers/cis-lunar transportation with surface and in space depots. In situ construction and energy expansion at mining and human outpost site(s). ISRU Ground Development. Develop and advance ISRU technologies to enable acquisition of resources and processing into mission consumables. Utilize Multi-center collaboration with a portfolio that includes internal NASA work, external contracts, and collaborative agreements/partnerships. Where appropriate, develop lunar ISRU components and subsystems with a Mars-forward application. Engage industry through public-private partnerships to lay the foundation for long-term lunar and space economic development. Spin-in/spin-out technologies for terrestrial applications and industry (mining, oil & gas, alternative energy, construction). Flight Demonstration Path to Operational ISRU. Utilize small demonstrations with near off-the-shelf hardware to obtain critical information quickly on lunar resources and operations. Demonstrate critical technologies and processes that interact with lunar materials and environments. Perform 'pilot plant' demonstrations at architecture relevant scales and durations to reduce the risk for ISRU-provided products for critical human mission applications.

In-situ Resource Utilization↗
DOE OSTI2026

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗