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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Workflow for Process Automation of Soil Gas Results from an Automated Soil Gas-Sampling System for Application in Carbon Storage Projects

Extended abstract for Geoconvention, Calgary, Alberta, Canada, May 12–14, 2025. The Energy & Environmental Research Center (EERC) developed an automated workflow for processing soil gas measurements collected from the automated soil gas-sampling systems deployed across the project site. Raw soil gas measurements are collected from each station every 4 hours and automatically uploaded to a cloud database. The workflow begins by writing code to download the data to a workstation automatically, then the data are published to an online dashboard that visualizes the measurements in time-series plots and a process-based decision-making framework. This automated workflow accelerates the time from data acquisition to decision-making. It supports carbon storage project operators by preparing and delivering a live, standardized dataset for quick analysis and source attribution to provide assurance of containment and overall permit compliance.

02 PETROLEUM↗

NASA NTRS1981

A Solution in Search of Problems

Ferrofluids offered vast-problem solving potential. Under license for the NASA technology, Dr. Ronald Moskowitz and Dr. Ronald Rosensweig formed Ferrofluids Corporation. First problem they found a solution for was related to the manufacture of semiconductor "chips" for use in electronic systems. They developed a magnetic seal composed of ferrofluid and a magnetic circuit. Magnetic field confines the ferrofluid in the regions between the stationary elements and the rotary shaft of the seal. Result is a series of liquid barriers that totally bar passage of contaminants. Seal is virtually wear-proof and has a lifetime measured in billions of shaft revolutions. It has reduced maintenance, minimizes "downtime" of production equipment, and reduces the cost of expensive materials that had previously been lost through seal failures. Products based on ferrofluid are exclusion seals for computer disc drives and inertia dampers for stepper motors. Uses are performance-improving, failure-reducing coolants for hi-fi loudspeakers. Other applications include analytical instrumentation, medical equipment, industrial processes, silicon crystal growing furnaces, plasma processes, fusion research, visual displays, and automated machine tools.

Source record↗

NASA NTRS1990

Artificial intelligence and design: Opportunities, research problems and directions

The issues of industrial productivity and economic competitiveness are of major significance in the U.S. at present. By advancing the science of design, and by creating a broad computer-based methodology for automating the design of artifacts and of industrial processes, we can attain dramatic improvements in productivity. It is our thesis that developments in computer science, especially in Artificial Intelligence (AI) and in related areas of advanced computing, provide us with a unique opportunity to push beyond the present level of computer aided automation technology and to attain substantial advances in the understanding and mechanization of design processes. To attain these goals, we need to build on top of the present state of AI, and to accelerate research and development in areas that are especially relevant to design problems of realistic complexity. We propose an approach to the special challenges in this area, which combines 'core work' in AI with the development of systems for handling significant design tasks. We discuss the general nature of design problems, the scientific issues involved in studying them with the help of AI approaches, and the methodological/technical issues that one must face in developing AI systems for handling advanced design tasks. Looking at basic work in AI from the perspective of design automation, we identify a number of research problems that need special attention. These include finding solution methods for handling multiple interacting goals, formation problems, problem decompositions, and redesign problems; choosing representations for design problems with emphasis on the concept of a design record; and developing approaches for the acquisition and structuring of domain knowledge with emphasis on finding useful approximations to domain theories. Progress in handling these research problems will have major impact both on our understanding of design processes and their automation, and also on several fundamental questions that are of intrinsic concern to AI. We present examples of current AI work on specific design tasks, and discuss new directions of research, both as extensions of current work and in the context of new design tasks where domain knowledge is either intractable or incomplete. The domains discussed include Digital Circuit Design, Mechanical Design of Rotational Transmissions, Design of Computer Architectures, Marine Design, Aircraft Design, and Design of Chemical Processes and Materials. Work in these domains is significant on technical grounds, and it is also important for economic and policy reasons.

Amarel, Saul↗

DOE OSTI2025

Open Specy 1.0: Automated (Hyper)spectroscopy for Microplastics

Microplastic spectral analysis is one of the most time-consuming processes in studying microplastic pollution, often requiring days per sample. Researchers are transitioning to automated batch and hyperspectral image analysis techniques to enhance efficiency. Open Specy, initially aimed at manual single-spectrum analysis, has now integrated automated methods. This updated version, Open Specy 1.0, introduces several new features, including two algorithms for automated processing (smoothing and particle compression), an extensive library containing over 40,000 open-source Raman and FTIR spectra, and two machine learning classifiers (logistic regression and k medoids) developed from this library. Furthermore, it includes a revamped user interface, an R package, and a benchmark data set for testing future advancements in automated techniques. Researchers evaluated various configurations for hyperspectral smoothing, particle identification, compression, and splitting, to achieve combined recovery rates between 50 and 150% particle counts, identities, and sizes with a coefficient of variation (CV) of less than 40% (the accredited standard). Mean absorbance times the standard deviation provided a consistent particle identification. Hyperspectral smoothing led to a 96% combined recovery rate and reduced variability (CV = 38%) compared to the 86% recovery (CV = 83%) of nonsmoothed controls. Additionally, compressing spectra for particles was significantly faster (>3x) and showed similar accuracy but with reduced variability than processing each pixel individually. Key challenges persist in automating spectral analysis, particularly in refining particle splitting algorithms, and improving identification routines to minimize false positives and negatives. In conclusion, new methods in sample preparation for better stabilization and dispersion of particles could overcome some of these issues.

13 HYDRO ENERGY↗

DOE OSTI2026

Vision and Development of a Design, Implementation, and Verification Automation (DIVA) Software Platform for DNA Construction

Abstract DNA construction, while a prerequisite to many biological endeavors, is often a time-consuming distraction from an individual’s primary research objectives. We envisioned that with the right software infrastructure and cultural mindset, a single person could execute in parallel the batched DNA construction tasks of an entire research institute, at scales realizing efficiency gains through process and laboratory automation. In pursuit of this vision, we developed the Design, Implementation, and Verification Automation (DIVA) software platform. DIVA’s web interface enables researchers to design DNA constructs (using visual biological computer-aided design tools and biological parts repositories), submit designs for construction to dedicated staff, and track DNA construction as it progresses. DIVA supports the dedicated staff through the DNA construction process and records both successful and unsuccessful attempts toward improving the overall process. The platform is publicly available at public-diva.jbei.org and its open-source code through github.com/JBEI/DIVA.

Plahar, Hector [DOE Agile BioFoundry , , ,; DOE Jo↗

DOE OSTI2023

Image Classification Using Convolutional Neural Networks to Automate Visual Inspection of CCO Containers (Rev. 1)

The Savannah River Site is automating the receipt and inspection of Criticality Control Overpack drums to aid in nuclear waste disposal. The Advanced Engineering group is automating this receipt and inspection process to assist the site’s goals. Part of this process includes visually inspecting CCO drums to ensure that no defects or security risks are present. This research focuses on developing a machine learning model to automatically classify drums as passing or failing inspection. The machine learning model was implemented using the open-source Tensorflow library and uses a Convolutional Neural Network architecture to extract features and differentiate between images. The model was able to achieve an average of 85% accuracy on a dataset of 288 drums. This project’s goal was to prove the validity of computer vision in an automation process and provide a starting place for continued research.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2007

Modeling and Parameter Estimation of Spacecraft Fuel Slosh with Diaphragms Using Pendulum Analogs

Prediction and control of liquid slosh in moving containers is an important consideration in the design of spacecraft and launch vehicle control systems. Even with modern computing systems, CFD type simulations are not fast enough to allow for large scale Monte Carlo analyses of spacecraft and launch vehicle dynamic behavior with slosh included. It is still desirable to use some type of simplified mechanical analog for the slosh to shorten computation time. Analytic determination of the slosh analog parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices such as elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks, these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the hand-derived equations of motion for the mechanical analog are evaluated and their results compared with the experimental results. This paper will describe efforts by the university component of a team comprised of NASA's Launch Services Program, Embry Riddle Aeronautical University, Southwest Research Institute and Hubert Astronautics to improve the accuracy and efficiency of modeling techniques used to predict these types of motions. Of particular interest is the effect of diaphragms and bladders on the slosh dynamics and how best to model these devices. The previous research was an effort to automate the process of slosh model parameter identification using a MATLAB/SimMechanics-based computer simulation. These results are the first step in applying the same computer estimation to a full-size tank and vehicle propulsion system. The introduction of diaphragms to this experimental set-up will aid in a better and more complete prediction of fuel slosh characteristics and behavior. Automating the parameter identification process will save time and thus allow earlier identification of potential vehicle performance problems.

Chatman, Yadira↗

NASA NTRSDate not supplied

Exploration and Manufacturing with Automated Fiber Placement

Highly repeatable and nearly defect-free fabrication of composite parts is critical to the success and widespread acceptance of composite materials. Through optimization using thin-ply materials, composite parts can be manufactured to be lighter and tailored more specifically to anticipated design loads than with standard prepreg materials alone. However, defects arising from the thin-ply manufacturing process are not always similar to defects found with standard tows. These new defects warrant evaluation. At NASA Langley Research Center, the manufacturing process parameters associated with automated fiber placement (AFP), a slit tape-based composite manufacturing process, were optimized for the use of a thin-ply prepreg carbon-epoxy material. Carbon-epoxy tows with areal weights of 30 g/m2 and 70 g/m2 were used in these manufacturing trials. The AFP process parameters of heater output, compaction force, tow feed rate, and tow tension were adjusted and optimized for successful manufacturing. This article documents an exploration of thin-ply fabrication on both flat and complex-shaped surfaces. Ultimately, aerospace-quality laminates were made from the 70-g/m2 material, but imperfections in the 30-g/m2 material itself and the fact that the AFP machine was not designed for such a thin material meant that more research and trials are required to obtain flight-quality 30-g/m2 laminates.

carbon-epoxy↗

NASA NTRSDate not supplied

Thin-Ply: Exploration and Manufacturing with Automated Fiber Placement

Abstract Highly repeatable and nearly defect-free fabrication of composite parts is critical to the success and widespread acceptance of composite materials. Through optimization using thin-ply materials, composite parts can be manufactured to be lighter and tailored more specifically to anticipated design loads than with standard prepreg materials alone. However, defects arising from the thin-ply manufacturing process are not always similar to defects found with standard tows. These new defects warrant evaluation. At NASA Langley Research Center, the manufacturing process parameters associated with automated fiber placement (AFP), a slit tape-based composite manufacturing process, were optimized for the use of a thin-ply prepreg carbon-epoxy material. Carbon-epoxy tows with areal weights of 30 g/m2 and 70 g/m2 were used in these manufacturing trials. The AFP process parameters of heater output, compaction force, tow feed rate, and tow tension were adjusted and optimized for successful manufacturing. This article documents an exploration of thin-ply fabrication on both flat and complex-shaped surfaces. Ultimately, aerospace-quality laminates were made from the 70-g/m2 material, but imperfections in the 30-g/m2 material itself and the fact that the AFP machine was not designed for such a thin material meant that more research and trials are required to obtain flight-quality 30-g/m2 laminates.

Carbon-expoxy↗

NASA NTRS2011

Rapid Automated Aircraft Simulation Model Updating from Flight Data

Techniques to identify aircraft aerodynamic characteristics from flight measurements and compute corrections to an existing simulation model of a research aircraft were investigated. The purpose of the research was to develop a process enabling rapid automated updating of aircraft simulation models using flight data and apply this capability to all flight regimes, including flight envelope extremes. The process presented has the potential to improve the efficiency of envelope expansion flight testing, revision of control system properties, and the development of high-fidelity simulators for pilot training.

Brian, Geoff↗

DOE OSTI2025

Monitoring installation of partially occluded subassemblies in modular construction factories using BIM, ray tracing, and computer vision

Modular and offsite construction methods are being increasingly adopted due to the advantages they offer in terms of project completion time, quality, and energy-efficiency. Despite these advantages, the current state of monitoring systems in modular construction factories highly relies on labor-intensive, subjective, and error-prone observational methods. A large body of research has aimed to automate the monitoring process using an array of sensors, such as IMUs and RFIDs, during the past two decades. Recently, computer vision-based methods have gained increasing interest as a non-intrusive technology to monitor the process inside modular construction factories. However, partial occlusion challenges have impeded their practical application on a large scale. This challenge is specifically important for monitoring the installation of subassemblies since they can obstruct the view of the monitoring camera, especially those that enable long-term monitoring like closed-circuit television (CCTV) fixed-view surveillance cameras. Here, this paper aims to address this challenge by proposing a novel computer vision-based method to monitor the installation of new subassemblies inside modular factories in highly occluded scenes. The proposed methodology identifies the subassemblies in the CCTV video footage using computer vision, analyzes the occlusions using BIM and ray casting techniques, and estimates the progress of assembly by comparing the BIM model with the detected subassemblies in the video. The proposed methodology was successfully validated on surveillance videos captured from a volumetric modular construction factory in the U.S., achieving 93% accuracy in identifying the installation of subassemblies. The results from this research show that the integration of BIM and computer vision is a promising method for monitoring the installation processes inside modular factories under severe occlusion.

97 MATHEMATICS AND COMPUTING↗

NASA NTRSDate not supplied

Populating a Graph Database to Run a Usage-Based Discovery Tool

Most dataset discovery tools for Earth Observation data rely on descriptions and other metadata of the datasets, using keyword searches or attribute filtering to determine relevance. However, these descriptions often do not include the potential uses of the data. Thus, a user working on floods will rarely see few if any rainfall datasets show up in such a search. The Usage Based Discovery tool, on the other hand, offers usage instances to the user, either research articles or applications, along with the datasets that those usage instances used. This allows a user, particularly one new to the world of Earth Observation data, to investigate which datasets are used in similar cases. The information that powers Usage-Based Discovery is a graph database of relationships of usage to dataset and usage to topic, allowing the user to narrow their search for similar cases. In order to scale out to a graph database rich enough to provide a satisfactory user experience, we combine manual and automated processes to populate the graph. The initial content of the graph has been seeded primarily via human-aided data curation methods, using sites like Google Scholar. To scale up this effort, we’ve employed crowdsourcing. It is easy for anyone to contribute to our graph using their Open Researcher and Contributor Identifier for authorization. We’re now experimenting with Machine Learning and Natural Language Processing to help automate population of the graph, starting with the classification of research articles by topic. Finding adequate training data in the absence of a comprehensive and open research article API continues to be a significant challenge.

Vincent Inverso↗

NASA NTRS1991

Systematic Identification Of Discrepant Hardware

CAMRAD, program designed for rapid input and retrieval of all data used in engineering-to-manufacturing support operations, aids engineer by automating material-review-disposition process. Facilitates research of material-review histories and provides for efficient processing of material-review documents. Three SmartWare project files control operation. Written in Smart programming language and designed to run on IBM PC compatibles with SmartWave version 3.1.

Hanna, Timothy L.↗

NASA NTRS2008

Multidisciplinary Design, Analysis, and Optimization Tool Development using a Genetic Algorithm

Multidisciplinary design, analysis, and optimization using a genetic algorithm is being developed at the National Aeronautics and Space A dministration Dryden Flight Research Center to automate analysis and design process by leveraging existing tools such as NASTRAN, ZAERO a nd CFD codes to enable true multidisciplinary optimization in the pr eliminary design stage of subsonic, transonic, supersonic, and hypers onic aircraft. This is a promising technology, but faces many challe nges in large-scale, real-world application. This paper describes cur rent approaches, recent results, and challenges for MDAO as demonstr ated by our experience with the Ikhana fire pod design.

Pak, Chan-gi↗

NASA NTRS2011

In Situ Analysis of Organics with a Portable Mass Spectrometer

The search for extra-terrestrial life starts at home. In order to find life on other planets, we start by examining life processes we understand on the earth. Though it may not be possible to see the life in the form of macroscopic organisms, telltale signs of life can exist in the form of small organic molecules such as peptides and amino acids. Our overall goal is to test a portable mass spectrometer (MS) system, the Mini 10.5, for astrobiological applications including in situ hydrocarbon analysis and sediments analysis using an additional automated sample processing system (ASPS). The collaborative research focuses on two current projects in the field of astrobiology. Both projects are geared towards examining organics distributed in extreme environments. One portion of study attempts to qualitatively analyze the effect of volatile organic compounds (VOC) produced by diesel exhaust on lichens growing in the desert. This requires measurements to be taken by bringing the instrument to the Mojave Desert and monitoring atmospheric composition of VOCs in situ. The second project is to evaluate the miniature MS system as a detector for the ASPS extraction system. A major obstacle of any chemometric in situ analysis is the suppression of analyte signal by concomitant signal from the surrounding environment. The ASPS extraction device has been developed at JPL to extract amino acids from sediment samples and elute them in solution. The solution is eluted at a high pH and needs to be conditioned to a more neutral pH so that dissolved amino acids can be readily protonated and subsequently analyzed by electrospray MS.

astrobiology↗

NASA NTRS1991

Automation of closed environments in space for human comfort and safety

The development of Environmental Control and Life Support Systems (ECLSS) for Space Station Freedom, future colonization of the Moon, and Mars missions presents new challenges for present technologies. ECLSS that operate during long-duration missions must be semi-autonomous to allow crew members environmental control without constant supervision. A control system for the ECLSS must address these issues as well as being reliable. The Kansas State University Advanced Design Team is in the process of researching and designing controls for the automation of the ECLSS for Space Station Freedom and beyond. The ECLSS for Freedom is composed of six subsystems. The temperature and humidity control (THC) subsystem maintains the cabin temperature and humidity at a comfortable level. The atmosphere control and supply (ACS) subsystem insures proper cabin pressure and partial pressures of oxygen and nitrogen. To protect the space station from fire damage, the fire detection and suppression (FDS) subsystem provides fire-sensing alarms and extinguishers. The waste management (WM) subsystem compacts solid wastes for return to Earth, and collects urine for water recovery. The atmosphere revitalization (AR) subsystem removes CO2 and other dangerous contaminants from the air. The water recovery and management (WRM) subsystem collects and filters condensate from the cabin to replenish potable water supplies, and processes urine and other waste waters to replenish hygiene water supplies. These subsystems are not fully automated at this time. Furthermore, the control of these subsystems is not presently integrated; they are largely independent of one another. A fully integrated and automated ECLSS would increase astronauts' productivity and contribute to their safety and comfort.

Source record↗

NASA NTRS1995

Implementation of a state of the art automated system for the production of cloud/water vapor motion winds from geostationary satellites

The research objectives in this proposal were part of a continuing program at UW-CIMSS to develop and refine an automated geostationary satellite winds processing system which can be utilized in both research and operational environments. The majority of the originally proposed tasks were successfully accomplished, and in some cases the progress exceeded the original goals. Much of the research and development supported by this grant resulted in upgrades and modifications to the existing automated satellite winds tracking algorithm. These modifications were put to the test through case study demonstrations and numerical model impact studies. After being successfully demonstrated, the modifications and upgrades were implemented into the NESDIS algorithms in Washington DC, and have become part of the operational support. A major focus of the research supported under this grant attended to the continued development of water vapor tracked winds from geostationary observations. The fully automated UW-CIMSS tracking algorithm has been tuned to provide complete upper-tropospheric coverage from this data source, with data set quality close to that of operational cloud motion winds. Multispectral water vapor observations were collected and processed from several different geostationary satellites. The tracking and quality control algorithms were tuned and refined based on ground-truth comparisons and case studies involving impact on numerical model analyses and forecasts. The results have shown the water vapor motion winds are of good quality, complement the cloud motion wind data, and can have a positive impact in NWP on many meteorological scales.

Velden, Christopher↗

DOE OSTI2025

Accessible Content Optimization for Research Needs (ACORN)

ACORN employs a set of automated processes for informing and/or enforcing defined content schemas to create standardized and highly structured data. Because of its standardized data source, ACORN easily applies computer automation to generate communication assets such as PDFs, Powerpoint presentations, and web pages. Built using the memory-safe Rust programming language, ACORN is portable and accessible for use on any Windows, Mac, or Linux machine.

Wohlgemuth, JasonHoward [Oak Ridge National Labora↗