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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
DOE OSTI2026

Chemical Recommender System: Replacement Suggestions for Small Molecules

The Chemical Recommender System (CRS) is an open-source, high-performance toolkit that enables real-time similarity searches across the complete PubChem database (over 50 million molecules) using commodity hardware. The CRS addresses critical limitations in existing chemical informatics platforms through a novel vector database infrastructure, extensible model integration capabilities, and complete algorithmic transparency. The system implements a vector database deployment with partitioned indexing that achieves a ~60x speedup over traditional approaches. A containerized model integration framework allows researchers to seamlessly incorporate custom predictive models into the full-scale search and scoring pipeline, while complete configurability of search parameters, filtering logic, and scoring functions provides capabilities not available in existing black-box solutions. Beyond structural similarity, the CRS integrates OPERA QSAR models for thermophysical and toxicity predictions, RDKit synthetic accessibility scoring, and user-defined models to compute weighted final replacement scores. The complete system is accessible through an interactive web application supporting real-time progress monitoring, post-processing score re-weighting, automated PDF reporting, and batch processing capabilities.

Nair, Parthiv Anand [Sandia National Laboratories ↗
DOE OSTI2025

Integration and Demonstration of Monitoring, Modeling, and Prediction of DV-1 Amendment Performance at the Bench Scale: DV-1 Amendment Demonstration

During fiscal years 2024 and 2025, the U.S. Department of Energy’s Hanford Field Office commissioned Pacific Northwest National Laboratory to conduct applied research aimed at reducing the cost, time, and uncertainty associated with in situ treatment of vadose zone contaminants at the Hanford Site. This report outlines the integration of three key research efforts into a meso-scale demonstration designed to advance field-scale solutions that aim to (1) optimize the delivery of chemical amendments to contaminated soils, (2) reduce uncertainty in amendment delivery performance assessment using advanced monitoring techniques, and (3) provide real-time insights into when and where amendment-induced precipitation reactions occur in the subsurface. To achieve these objectives, the tank-scale (~ 1 cubic meter) Geophysical Imaging of Flow and Transport (GIFT) system was developed. GIFT enables experimental testing of amendment delivery while incorporating automated multi-modal monitoring approaches, including pressure measurements, direct fluid sampling, and remote time-lapse geophysical imaging. The data generated from these monitoring techniques will serve as inputs for a generative artificial-intelligence-driven digital twin – a numerical simulation model designed to honor observed data while quantifying uncertainty in simulation accuracy. Using this simulator, researchers will refine an amendment injection strategy to maximize delivery efficiency within a low-permeability soil zone. Monitoring data will be interpreted through simulated outputs to enhance understanding of the injection process. The efficacy of this integrated approach will be evaluated through direct sampling at the conclusion of the experiment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1990

Generation and analysis of large reliability models

An effort has been underway for several years at NASA's Langley Research Center to extend the capability of Markov modeling techniques for reliability analysis to the designers of highly reliable avionic systems. This effort has been focused in the areas of increased model abstraction and increased computational capability. The reliability model generator (RMG), a software tool which uses as input a graphical, object-oriented block diagram of the system, is discussed. RMG uses an automated failure modes-effects analysis algorithm to produce the reliability model from the graphical description. Also considered is the ASSURE software tool, a parallel processing program which uses the ASSIST modeling language and SURE semi-Markov solution technique. An executable failure modes-effects analysis is used by ASSURE. The successful combination of the power of graphical representation, automated model generation, and parallel computation leads to the conclusion that large system architectures can now be analyzed.

Aerospace electronics↗
NASA NTRS2009

Integration of Weather Data into Airspace and Traffic Operations Simulation (ATOS) for Trajectory- Based Operations Research

Explicit integration of aviation weather forecasts with the National Airspace System (NAS) structure is needed to improve the development and execution of operationally effective weather impact mitigation plans and has become increasingly important due to NAS congestion and associated increases in delay. This article considers several contemporary weather-air traffic management (ATM) integration applications: the use of probabilistic forecasts of visibility at San Francisco, the Route Availability Planning Tool to facilitate departures from the New York airports during thunderstorms, the estimation of en route capacity in convective weather, and the application of mixed-integer optimization techniques to air traffic management when the en route and terminal capacities are varying with time because of convective weather impacts. Our operational experience at San Francisco and New York coupled with very promising initial results of traffic flow optimizations suggests that weather-ATM integrated systems warrant significant research and development investment. However, they will need to be refined through rapid prototyping at facilities with supportive operational users We have discussed key elements of an emerging aviation weather research area: the explicit integration of aviation weather forecasts with NAS structure to improve the effectiveness and timeliness of weather impact mitigation plans. Our insights are based on operational experiences with Lincoln Laboratory-developed integrated weather sensing and processing systems, and derivative early prototypes of explicit ATM decision support tools such as the RAPT in New York City. The technical components of this effort involve improving meteorological forecast skill, tailoring the forecast outputs to the problem of estimating airspace impacts, developing models to quantify airspace impacts, and prototyping automated tools that assist in the development of objective broad-area ATM strategies, given probabilistic weather forecasts. Lincoln Laboratory studies and prototype demonstrations in this area are helping to define the weather-assimilated decision-making system that is envisioned as a key capability for the multi-agency Next Generation Air Transportation System [1]. The Laboratory's work in this area has involved continuing, operations-based evolution of both weather forecasts and models for weather impacts on the NAS. Our experience has been that the development of usable ATM technologies that address weather impacts must proceed via rapid prototyping at facilities whose users are highly motivated to participate in system evolution.

Peters, Mark↗
NASA NTRS2018

Biocybernetic Adaptation Strategies: Machine Awareness of Human Engagement for Improved Operational Performance

Human operators interacting with machines or computers continually adapt to the needs of the system ideally resulting in optimal performance. In some cases, however, deteriorated performance is an outcome. Adaptation to the situation is a strength expected of the human operator which is often accomplished by the human through self-regulation of mental state. Adaptation is at the core of the human operator's activity, and research has demonstrated that the implementation of a feedback loop can enhance this natural skill to improve training and human/machine interaction. Biocybernetic adaptation involves a “loop upon a loop,” which may be visualized as a superimposed loop which senses a physiological signal and influences the operator’s task at some point. Biocybernetic adaptation in, for example, physiologically adaptive automation employs the “steering” sense of “cybernetic,” and serves a transitory adaptive purpose – to better serve the human operator by more fully representing their responses to the sys- tem. The adaptation process usually makes use of an assessment of transient cog- nitive state to steer a functional aspect of a system that is external to the operator’s physiology from which the state assessment is derived. Therefore, the objective of this paper is to detail the structure of biocybernetic systems regarding the level of engagement of interest for adaptive systems, their processing pipeline, and the adaptation strategies employed for training purposes, in an effort to pave the way towards machine awareness of human state for self-regulation and improved operational performance.

Stephens, Chad↗
NASA NTRSDate not supplied

Automated classification of scientific publications linked to GES DISC datasets

The data collections archived and distributedby the GES DISC NASA data center arewidely utilized for various Earth Science studies.As these collections are created, many researchworks are published regarding the collections, algorithms,validations and applications. SinceGES DISC collects these publications and providestheir citations for the users, it is helpful tocategorize them based on how they relate to the datasetsthey are associated with. Specifically,whether the publication that is linked to GES DISCdataset is using it for applicational research,or if it describes the algorithm for dataset creation,or the validation of the dataset, or providesthe general overview of the data collection. Currently,this process requires simple manuallabelling, and as such, may be possible to solve viaautomation. To approach this problem, wedeveloped machine learning classifiers to predictthe category a publication belongs to. We usedmanually labeled publications as training data forsupervised machine learning algorithms:Random Forest and Naive Bayes. We achieved classificationaccuracy that is substantially betterthan the baseline accuracy, thus greatly improvingthe efficiency of the publication internalanalysis.

Rohan Dayal↗
DOE OSTI2025

Language models for materials discovery and sustainability: Progress, challenges, and opportunities

Significant advancements have been made in one of the most critical branches of artificial intelligence: natural language processing (NLP). These advancements are exemplified by the remarkable success of OpenAI’s GPT-3.5/4 and the recent release of GPT-4.5, which have sparked a global surge of interest akin to an NLP gold rush. Here, in this article, we offer our perspective on the development and application of NLP and large language models (LLMs) in materials science. We begin by presenting an overview of recent advancements in NLP within the broader scientific landscape, with a particular focus on their relevance to materials science. Next, we examine how NLP can facilitate the understanding and design of novel materials and its potential integration with other methodologies. To highlight key challenges and opportunities, we delve into three specific topics: (i) the limitations of LLMs and their implications for materials science applications, (ii) the creation of a fully automated materials discovery pipeline, and (iii) the potential of GPT-like tools to synthesize existing knowledge and aid in the design of sustainable materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine learning-led semi-automated medium optimization reveals salt as key for flaviolin production in Pseudomonas putida

Although synthetic biology can produce valuable chemicals in a renewable manner, its progress is still hindered by a lack of predictive capabilities. Media optimization is a critical, and often overlooked, process which is essential to obtain the titers, rates and yields needed for commercial viability. Here, we present a molecule- and host-agnostic active learning process for media optimization that is enabled by a fast and highly repeatable semi-automated pipeline. Its application yielded 60% and 70% increases in titer, and 350% increase in process yield in three different campaigns for flaviolin production in Pseudomonas putida KT2440. Explainable Artificial Intelligence techniques pinpointed that, surprisingly, common salt (NaCl) is the most important component influencing production. The optimal salt concentration is very high, comparable to seawater and close to the limits that P. putida can tolerate. The availability of fast Design-Build-Test-Learn (DBTL) cycles allowed us to show that performance improvements for active learning are rarely monotonous. This work illustrates how machine learning and automation can change the paradigm of current synthetic biology research to make it more effective and informative, and suggests a cost-effective and underexploited strategy to facilitate the high titers, rates and yields essential for commercial viability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Guided combinatorial synthesis and automated characterization expedites the discovery of hard, electrically conductive Pt x Au 1-x films

Sputter-deposited Pt-Au thin films have been reported to develop a hard, stable, nanocrystalline structure, yet little is known about how these characteristics vary with Pt x Au 1-x composition and process conditions. Toward this end, this document describes an extensive, combinatorial Pt-Au thin film library including characterized film compositions, structure, and properties. Complemented by kinematic Monte Carlo simulations of codeposition, a broad range of Pt x Au 1-x compositions (from x ~ 0.02 to 0.93) was first established by sputtering with varied magnetron powers and gun tilt angles. Further, the produced films were subsequently interrogated using automated nanoindentation, x-ray reflectivity, x-ray diffraction, atomic force microscopy, surface profilometry, four-point probe sheet resistance techniques, and wavelength dispersive spectroscopy in order to determine how hardness, modulus, density, surface roughness, structure, and resistivity vary with film stoichiometry and process parameters. Combinatorial films displayed an assortment of properties with the hardness of some films exceeding values reported previously for this material system. High hardness, high modulus, and low resistivity were generally attained when using increased deposition energy and reduced angle-of-incidence processes. Overall, the research identified promising, new Pt x Au 1-x compositions for future study and pinpointed strategies for improved deposition.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Industry Level Integrated Fire Modeling Using Fire Risk Investigation in 3D (FRI3D)

The software Fire Risk Investigation in 3D (FRI3D) has been developed over the last 2 years to integrate 3D spatial modeling with existing fire probabilistic risk assessment (PRA) models and fire simulation codes. The goal of this research and development is to automate many of the fire analysis manual tasks to reduce industry efforts in the initial fire modeling and operational costs for the model maintenance and evaluations required during normal plant operations. The tasks for Fiscal Year (FY) 2021 include first testing the FRI3D modeling capabilities by importing an industry fire model into FRI3D and making a 3D model of a complex/high-risk significant area. (For this work, the switchgear room was chosen.) Then, the second task of FY 2021 is to develop a dynamic fire PRA process that can help optimize traditional fire PRA models. The switchgear room model will be used for the dynamic fire PRA work. This report describes the work and insights learned when using FRI3D software to model both a Nuclear Regulatory Report (NUREG) example models and a full industry switchgear room.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

Automated in situ observations of upper ocean biogeochemistry, bio-optics, and physics and their potential use for global studies

The processes controlling the flux of carbon in the upper ocean have dynamic ranges in space and time of at least nine orders of magnitude. These processes depend on a broad suite of inter-related biogeochemical, bio-optical, and physical variables. These variables should be sampled on scales matching the relevant phenomena. Traditional ship-based sampling, while critical for detailed and more comprehensive observations, can span only limited portions of these ranges because of logistical and financial constraints. Further, remote observations from satellite platforms enable broad horizontal coverage which is restricted to the upper few meters of the ocean. For these main reasons, automated subsurface measurement systems are important for the fulfillment of research goals related to the regional and global estimation and modeling of time varying biogeochemical fluxes. Within the past few years, new sensors and systems capable of autonomously measuring several of the critical variables have been developed. The platforms for deploying these systems now include moorings and drifters and it is likely that autonomous underwater vehicles (AUV's) will become available for use in the future. Each of these platforms satisfies particular sampling needs and can be used to complement both shipboard and satellite observations. In the present review, (1) sampling considerations will be summarized, (2) examples of data obtained from some of the existing automated in situ sampling systems will be highlighted, (3) future sensors and systems will be discussed, (4) data management issues for present and future automated systems will be considered, and (5) the status of near real-time data telemetry will be outlined. Finally, we wish to make it clear at the outset that the perspectives presented here are those of the authors and are not intended to represent those of the United States JGOFS program, the International JGOFS program, NOAA's C&GC program, or other global ocean programs.

Dickey, Tommy D.↗
NASA NTRS2003

The Successful Development of an Automated Rendezvous and Capture (AR&C) System for the National Aeronautics and Space Administration

During the 1990's, the Marshall Space Flight Center (MSFC) conducted pioneering research in the development of an automated rendezvous and capture/docking (AR&C) system for U.S. space vehicles. Development and demonstration of a rendezvous sensor was identified early in the AR&C Program as the critical enabling technology that allows automated proximity operations and docking. A first generation rendezvous sensor, the Video Guidance Sensor (VGS), was developed and successfully flown on STS-87 and STS-95, proving the concept of a video- based sensor. A ground demonstration of the entire system and software was successfully tested. Advances in both video and signal processing technologies and the lessons learned from the two successful flight experiments provided a baseline for the development, by the MSFC, of a new generation of video based rendezvous sensor. The Advanced Video Guidance Sensor (AGS) has greatly increased performance and additional capability for longer-range operation with a new target designed as a direct replacement for existing ISS hemispherical reflectors.

Roe, Fred D.↗
NASA NTRS2011

A Possible Approach for Addressing Neglected Human Factors Issues of Systems Engineering

The increasing complexity of safety-critical applications has led to the introduction of decision support tools in the transportation and process industries. Automation has also been introduced to support operator intervention in safety-critical applications. These innovations help reduce overall operator workload, and filter application data to maximize the finite cognitive and perceptual resources of system operators. However, these benefits do not come without a cost. Increased computational support for the end-users of safety-critical applications leads to increased reliance on engineers to monitor and maintain automated systems and decision support tools. This paper argues that by focussing on the end-users of complex applications, previous research has tended to neglect the demands that are being placed on systems engineers. The argument is illustrated through discussing three recent accidents. The paper concludes by presenting a possible strategy for building and using highly automated systems based on increased attention by management and regulators, improvements in competency and training for technical staff, sustained support for engineering team resource management, and the development of incident reporting systems for infrastructure failures. This paper represents preliminary work, about which we seek comments and suggestions.

Johnson, Christopher W.↗
NASA NTRS2012

Modernization of B-2 Data, Video, and Control Systems Infrastructure

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) Plum Brook Station (PBS) Spacecraft Propulsion Research Facility, commonly referred to as B-2, is NASA s third largest thermal-vacuum facility with propellant systems capability. B-2 has completed a modernization effort of its facility legacy data, video and control systems infrastructure to accommodate modern integrated testing and Information Technology (IT) Security requirements. Integrated systems tests have been conducted to demonstrate the new data, video and control systems functionality and capability. Discrete analog signal conditioners have been replaced by new programmable, signal processing hardware that is integrated with the data system. This integration supports automated calibration and verification of the analog subsystem. Modern measurement systems analysis (MSA) tools are being developed to help verify system health and measurement integrity. Legacy hard wired digital data systems have been replaced by distributed Fibre Channel (FC) network connected digitizers where high speed sampling rates have increased to 256,000 samples per second. Several analog video cameras have been replaced by digital image and storage systems. Hard-wired analog control systems have been replaced by Programmable Logic Controllers (PLC), fiber optic networks (FON) infrastructure and human machine interface (HMI) operator screens. New modern IT Security procedures and schemes have been employed to control data access and process control flows. Due to the nature of testing possible at B-2, flexibility and configurability of systems has been central to the architecture during modernization.

Cmar, Mark D.↗
NASA NTRS2012

Modernization of B-2 Data, Video, and Control Systems Infrastructure

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) Plum Brook Station (PBS) Spacecraft Propulsion Research Facility, commonly referred to as B-2, is NASA's third largest thermal-vacuum facility with propellant systems capability. B-2 has completed a modernization effort of its facility legacy data, video and control systems infrastructure to accommodate modern integrated testing and Information Technology (IT) Security requirements. Integrated systems tests have been conducted to demonstrate the new data, video and control systems functionality and capability. Discrete analog signal conditioners have been replaced by new programmable, signal processing hardware that is integrated with the data system. This integration supports automated calibration and verification of the analog subsystem. Modern measurement systems analysis (MSA) tools are being developed to help verify system health and measurement integrity. Legacy hard wired digital data systems have been replaced by distributed Fibre Channel (FC) network connected digitizers where high speed sampling rates have increased to 256,000 samples per second. Several analog video cameras have been replaced by digital image and storage systems. Hard-wired analog control systems have been replaced by Programmable Logic Controllers (PLC), fiber optic networks (FON) infrastructure and human machine interface (HMI) operator screens. New modern IT Security procedures and schemes have been employed to control data access and process control flows. Due to the nature of testing possible at B-2, flexibility and configurability of systems has been central to the architecture during modernization.

Cmar, Mark D.↗
NASA NTRS2014

An Architecture to Enable Autonomous Control of Spacecraft

Autonomy is required for manned spacecraft missions distant enough that light-time communication delays make ground-based mission control infeasible. Presently, ground controllers develop a complete schedule of power modes for all spacecraft components based on a large number of factors. The proposed architecture is an early attempt to formalize and automate this process using on-vehicle computation resources. In order to demonstrate this architecture, an autonomous electrical power system controller and vehicle Mission Manager are constructed. These two components are designed to work together in order to plan upcoming load use as well as respond to unanticipated deviations from the plan. The communication protocol was developed using "paper" simulations prior to formally encoding the messages and developing software to implement the required functionality. These software routines exchange data via TCP/IP sockets with the Mission Manager operating at NASA Ames Research Center and the autonomous power controller running at NASA Glenn Research Center. The interconnected systems are tested and shown to be effective at planning the operation of a simulated quasi-steady state spacecraft power system and responding to unexpected disturbances.

space power systems↗
NASA NTRS2015

Human Factors and Habitability Challenges for Mars Missions

As NASA is planning to send humans deeper into space than ever before, adequate crew health and performance will be critical for mission success. Within the NASA Human Research Program (HRP), the Space Human Factors and Habitability (SHFH) team is responsible for characterizing the risks associated with human capabilities and limitations with respect to long-duration spaceflight, and for providing mitigations (e.g., guidelines, technologies, and tools) to promote safe, reliable and productive missions. SHFH research includes three domains: Advanced Environmental Health (AEH), Advanced Food Technology (AFT), and Space Human Factors Engineering (SHFE). The AEH portfolio focuses on understanding the risk of microbial contamination of the spacecraft and on the development of standards for exposure to potential toxins such as chemicals, bacteria, fungus, and lunar/Martian dust. The two risks that the environmental health project focuses on are adverse health effects due to changes in host-microbe interactions, and risks associated with exposure to dust in planetary surface habitats. This portfolio also proposes countermeasures to these risks by making recommendations that relate to requirements for environmental quality, foods, and crew health on spacecraft and space missions. The AFT portfolio focuses on reducing the mass, volume, and waste of the entire integrated food system to be used in exploration missions, and investigating processing methods to extend the shelf life of food items up to five years, while assuring that exploration crews will have nutritious and palatable foods. The portfolio also delivers improvements in both the food itself and the technologies for storing and preparing it. SHFE sponsors research to establish human factors and habitability standards and guidelines in five risk areas, and provides improved design concepts for advanced crew interfaces and habitability systems. These risk areas include: Incompatible vehicle/habitat design, inadequate human-computer interaction, inadequate critical task design, inadequate human-automation/robotic interaction, and performance errors due to training deficiencies. To address the identified research gaps within each risk, SHFH's research plan includes studies in the laboratory, in analogs, and on International Space Station (ISS). In addition to establishing and maintaining the risk-based research portfolio, SHFH is also implementing a qualitative approach to determine how we at NASA evaluate human performance. Via interviews with experts, such as trainers, flight controllers, and flight surgeons, we are collecting the metrics by which they assess human performance, evidence of performance issues, and potential or actual consequences. The Human Performance Data Project will determine what human performance data have been collected in the past at NASA, and what data should be collected in the future in order to complete our knowledgebase and reduce risks related to human factors and habitability.

Whitmore, Mihriban↗
NASA NTRSDate not supplied

Cloud-Based Solutions for Monitoring Coastal Ecosystems and Prioritization of Restoration Efforts Across Belize

In recent years the availability of automated change detection algorithms in Google Earth Engine has permitted cloud-based processing of large time series of satellite imagery. Models such as the Continuous Change Detection and Classification (CCDC), CCDC-Spectral Mixture Analysis (CCDC-SMA), and Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) allow users to exploit decades of Earth Observations (EO) , leveraging the Landsat archive and data from other sensors to detect disturbance in forest ecosystems. Despite the wide adoption of these methods, robust documentation and growing community of users, little research has explored their use in mangrove environments. Mangroves are dynamic environments subject to changes due to not only the natural migration of mudflats but also coastal erosion, urban expansion, aquaculture practices, etc. This work aims to identify best practices for the application of these models to identify and monitor changes in the Belizean mangroves, which experienced an estimated 5.4% decrease in extent between 1980 and 2017 (Cherrington et al. 2020). Partnering directly with the Belizean Forest Department, our team will develop a replicable, efficient methodology to annually update the country’s mangrove extent employing EO-based change detection. This collaboration supports Belize’s marine conservation and climate resilience efforts, such as its Blue Bond agreement with the Nature Conservancy, building on national processes to monitor these critical ecosystems.

Mangroves↗