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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Requirements, Verification, and Compliance (RVC) Database Tool

This paper describes the development, design, and implementation of the Requirements, Verification, and Compliance (RVC) database used on the International Space Welding Experiment (ISWE) project managed at Marshall Space Flight Center. The RVC is a systems engineer's tool for automating and managing the following information: requirements; requirements traceability; verification requirements; verification planning; verification success criteria; and compliance status. This information normally contained within documents (e.g. specifications, plans) is contained in an electronic database that allows the project team members to access, query, and status the requirements, verification, and compliance information from their individual desktop computers. Using commercial-off-the-shelf (COTS) database software that contains networking capabilities, the RVC was developed not only with cost savings in mind but primarily for the purpose of providing a more efficient and effective automated method of maintaining and distributing the systems engineering information. In addition, the RVC approach provides the systems engineer the capability to develop and tailor various reports containing the requirements, verification, and compliance information that meets the needs of the project team members. The automated approach of the RVC for capturing and distributing the information improves the productivity of the systems engineer by allowing that person to concentrate more on the job of developing good requirements and verification programs and not on the effort of being a "document developer".

Rainwater, Neil E., II↗
NASA NTRS2005

Distributed Optimization

We demonstrate a new framework for analyzing and controlling distributed systems, by solving constrained optimization problems with an algorithm based on that framework. The framework is ar. information-theoretic extension of conventional full-rationality game theory to allow bounded rational agents. The associated optimization algorithm is a game in which agents control the variables of the optimization problem. They do this by jointly minimizing a Lagrangian of (the probability distribution of) their joint state. The updating of the Lagrange parameters in that Lagrangian is a form of automated annealing, one that focuses the multi-agent system on the optimal pure strategy. We present computer experiments for the k-sat constraint satisfaction problem and for unconstrained minimization of NK functions.

Macready, William↗
NASA NTRS2017

Benefits of Using Pairwise Trajectory Management in the Central East Pacific

Pairwise Trajectory Management (PTM) is a concept that utilizes airborne and ground-based capabilities to enable airborne spacing operations in procedural airspace. This concept makes use of updated ground automation, Automatic Dependent Surveillance-Broadcast (ADS-B) and on board avionics generating real time guidance. An experiment was conducted to examine the potential benefits of implementing PTM in the Central East Pacific oceanic region. An explanation of the experiment and some of the results are included in this paper. The PTM concept allowed for an increase in the average time an aircraft is able to spend at its desired flight level and a reduction in fuel burn.

Chartrand, Ryan↗
NASA NTRS2020

Space Ground Sensorwebs for Volcano Monitoring

Increased space and ground sensing is enabling dramatic new measurements of a wide range of Earth Science and Applied Earth Science phenomena, including: volcanism, flooding, wildfires, weather, and many other phenomena. New Space ventures have produced significantly greater access to data and miniaturization of sensing has enabled cubesats and smallsats to deliver data of outstanding resolution. The advent of the internet of things has produced incredible amounts of relevant terrestrial data as well. Artificial Intelligence offers the potential to automate both data interpretation and resource allocation to best allocate sensing assets. We describe efforts to build and experiment with such “sensorweb” systems and offer some direction for the future sensorweb observation systems.

Zuleta, Ignacio↗
NASA NTRSDate not supplied

Impact of Latency and Reliability on Separation Assurance with Remotely Piloted Aircraft in Terminal Operations

Remotely Piloted Aircraft (RPA) for cargo operations in the national airspace system will impact safety due to, among other factors, the latency and reliability of command & control, and of communication. This paper investigates the safety impact with increasing mix of RPA amidst manned traffic in a generic arrival pattern with three merging flows. Latency was modelled as the response time between air traffic control's determination of a resolution and the RPAs' initiation of the maneuver. Reliability was modelled as a message drop probability. The experiment was repeated with two different aircraft types having different performance characteristics as representatives of RPA for conducting automated cargo operations. Overall response time above thirty seconds and message drop probability over twenty percent caused losses of separation. Specific results depended on the RPA aircraft type. The detailed impacts of latency and reliability with increasing mix of RPA traffic are provided. Applications of the approach for further studies at increasing levels of automation are also discussed.

Vishwanath Bulusu↗
NASA NTRS2022

Impact of Latency and Reliability on Separation Assurance with Remotely Piloted Aircraft in Terminal Operations

Remotely Piloted Aircraft (RPA) for cargo operations in the national airspace system will impact safety due to, among other factors, the latency and reliability of command & control, and of communication. This paper investigates the safety impact with increasing mix of RPA amidst manned traffic in a generic arrival pattern with three merging flows. Latency was modelled as the response time between air traffic control's determination of a resolution and the RPAs' initiation of the maneuver. Reliability was modelled as a message drop probability. The experiment was repeated with two different aircraft types having different performance characteristics as representatives of RPA for conducting automated cargo operations. Overall response time above thirty seconds and message drop probability over twenty percent caused losses of separation. Specific results depended on the RPA aircraft type. The detailed impacts of latency and reliability with increasing mix of RPA traffic are provided. Applications of the approach for further studies at increasing levels of automation are also discussed.

Vishwanath Bulusu↗
NASA NTRS1971

Automated Microbial Metabolism Laboratory

The effect of several environmental parameters on previously developed life detection systems is explored. Initial attempts were made to conduct all the experiments in a moist mode (high soil volume to water volume ratio). However, only labeled release and measurement of ATP were found to be feasible under conditions of low moisture. Therefore, these two life detection experiments were used for most of the environmental effects studies. Three soils, Mojave (California desert), Wyaconda (Maryland, sandy loam) and Victoria Valley (Antarctic desert) were generally used throughout. The environmental conditions studied included: incubation temperature 3 C to 80 C, ultraviolet irradiation of soils, variations in soil/liquid ratio, specific atmospheric gases, various antimetabolites, specific substrates, and variation in pH. An experiment designed to monitor nitrogen metabolism was also investigated.

Source record↗
NASA NTRS2016

Investigating the Simulink Auto-Coding Process

Model based program design is the most clear and direct way to develop algorithms and programs for interfacing with hardware. While coding "by hand" results in a more tailored product, the ever-growing size and complexity of modern-day applications can cause the project work load to quickly become unreasonable for one programmer. This has generally been addressed by splitting the product into separate modules to allow multiple developers to work in parallel on the same project, however this introduces new potentials for errors in the process. The fluidity, reliability and robustness of the code relies on the abilities of the programmers to communicate their methods to one another; furthermore, multiple programmers invites multiple potentially differing coding styles into the same product, which can cause a loss of readability or even module incompatibility. Fortunately, Mathworks has implemented an auto-coding feature that allows programmers to design their algorithms through the use of models and diagrams in the graphical programming environment Simulink, allowing the designer to visually determine what the hardware is to do. From here, the auto-coding feature handles converting the project into another programming language. This type of approach allows the designer to clearly see how the software will be directing the hardware without the need to try and interpret large amounts of code. In addition, it speeds up the programming process, minimizing the amount of man-hours spent on a single project, thus reducing the chance of human error as well as project turnover time. One such project that has benefited from the auto-coding procedure is Ramses, a portion of the GNC flight software on-board Orion that has been implemented primarily in Simulink. Currently, however, auto-coding Ramses into C++ requires 5 hours of code generation time. This causes issues if the tool ever needs to be debugged, as this code generation will need to occur with each edit to any part of the program; additionally, this is lost time that could be spent testing and analyzing the code. This is one of the more prominent issues with the auto-coding process, and while much information is available with regard to optimizing Simulink designs to produce efficient and reliable C++ code, not much research has been made public on how to reduce the code generation time. It is of interest to develop some insight as to what causes code generation times to be so significant, and determine if there are architecture guidelines or a desirable auto-coding configuration set to assist in streamlining this step of the design process for particular applications. To address the issue at hand, the Simulink coder was studied at a foundational level. For each different component type made available by the software, the features, auto-code generation time, and the format of the generated code were analyzed and documented. Tools were developed and documented to expedite these studies, particularly in the area of automating sequential builds to ensure accurate data was obtained. Next, the Ramses model was examined in an attempt to determine the composition and the types of technologies used in the model. This enabled the development of a model that uses similar technologies, but takes a fraction of the time to auto-code to reduce the turnaround time for experimentation. Lastly, the model was used to run a wide array of experiments and collect data to obtain knowledge about where to search for bottlenecks in the Ramses model. The resulting contributions of the overall effort consist of an experimental model for further investigation into the subject, as well as several automation tools to assist in analyzing the model, and a reference document offering insight to the auto-coding process, including documentation of the tools used in the model analysis, data illustrating some potential problem areas in the auto-coding process, and recommendations on areas or practices in the current Ramses model that should be further investigated. Several skills were required to be built up over the course of the internship project. First and foremost, my Simulink skills have improved drastically, as much of my experience had been modeling electronic circuits as opposed to software models. Furthermore, I am now comfortable working with the Simulink Auto-coder, a tool I had never used until this summer; this tool also tested my critical thinking and C++ knowledge as I had to interpret the C++ code it was generating and attempt to understand how the Simulink model affected the generated code. I had come into the internship with a solid understanding of Matlab code, but had done very little in using it to automate tasks, particularly Simulink tasks; along the same lines, I had rarely used shell script to automate and interface with programs, which I gained a fair amount of experience with this summer, including how to use regular expression. Lastly, soft-skills are an area everyone can continuously improve on; having never worked with NASA engineers, which to me seem to be a completely different breed than what I am used to (commercial electronic engineers), I learned to utilize the wealth of knowledge present at JSC. I wish I had come into the internship knowing exactly how helpful everyone in my branch would be, as I would have picked up on this sooner. I hope that having gained such a strong foundation in Simulink over this summer will open the opportunity to return to work on this project, or potentially other opportunities within the division. The idea of leaving a project I devoted ten weeks to is a hard one to cope with, so having the chance to pick up where I left off sounds appealing; alternatively, I am interested to see if there are any opening in the future that would allow me to work on a project that is more in-line with my research in estimation algorithms. Regardless, this summer has been a milestone in my professional career, and I hope this has started a long-term relationship between JSC and myself. I really enjoy the thought of building on my experience here over future summers while I work to complete my PhD at Missouri University of Science and Technology.

Gualdoni, Matthew J.↗
DOE OSTI2022

Statistical characterization of experimental magnetized liner inertial fusion stagnation images using deep-learning-based fuel–background segmentation

Significant variety is observed in spherical crystal x-ray imager (SCXI) data for the stagnated fuel–liner system created in Magnetized Liner Inertial Fusion (MagLIF) experiments conducted at the Sandia National Laboratories Z-facility. As a result, image analysis tasks involving, e.g., region-of-interest selection (i.e. segmentation), background subtraction and image registration have generally required tedious manual treatment leading to increased risk of irreproducibility, lack of uncertainty quantification and smaller-scale studies using only a fraction of available data. We present a convolutional neural network (CNN)-based pipeline to automate much of the image processing workflow. This tool enabled batch preprocessing of an ensemble of N scans = 139 SCXI images across N exp = 67 different experiments for subsequent study. The pipeline begins by segmenting images into the stagnated fuel and background using a CNN trained on synthetic images generated from a geometric model of a physical three-dimensional plasma. The resulting segmentation allows for a rules-based registration. Our approach flexibly handles rarely occurring artifacts through minimal user input and avoids the need for extensive hand labelling and augmentation of our experimental dataset that would be needed to train an end-to-end pipeline. Here we also fit background pixels using low-degree polynomials, and perform a statistical assessment of the background and noise properties over the entire image database. Our results provide a guide for choices made in statistical inference models using stagnation image data and can be applied in the generation of synthetic datasets with realistic choices of noise statistics and background models used for machine learning tasks in MagLIF data analysis. We anticipate that the method may be readily extended to automate other MagLIF stagnation imaging applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Enhancing Post-Irradiation Examination (PIE) Efficiency with High-Throughput Experiments

Nuclear materials testing is essential for understanding changes in reactor environments, but traditional methods are costly and time-consuming. High-Throughput Experimentation (HTE) enables rapid screening and optimization of material properties by significantly increasing the number of specimens in the experiment. In this work, HTE methods were employed to irradiate novel materials at the Advanced Test Reactor (ATR) at Idaho National Laboratory. A total of 367 sub-sized tensile specimens were irradiated using the standard capsule design. To facilitate HTE, automated systems such as the Automated Mechanical Testing System were implemented for mechanical testing within hot cell environments, thereby reducing the need for manual interaction with hot cell manipulators and significantly lowering both the cost and duration of experiments. Digital image correlation (DIC) was used to measure displacement during mechanical testing, providing precise, non-contact measurement capabilities. The methodologies developed in this research will support the advancement of HTE techniques for future nuclear materials testing experiments at ATR. This approach allows for more efficient and cost-effective evaluation of new materials, ultimately leading to improved reactor performance, enhanced safety, and extended longevity within the nuclear industry.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2012

Automated Operations Development for Advanced Exploration Systems

Automated space operations command and control software development and its implementation must be an integral part of the vehicle design effort. The software design must encompass autonomous fault detection, isolation, recovery capabilities and also provide "single button" intelligent functions for the crew. Development, operations and safety approval experience with the Timeliner system onboard the International Space Station (ISS), which provided autonomous monitoring with response and single command functionality of payload systems, can be built upon for future automated operations as the ISS Payload effort was the first and only autonomous command and control system to be in continuous execution (6 years), 24 hours a day, 7 days a week within a crewed spacecraft environment. Utilizing proven capabilities from the ISS Higher Active Logic (HAL) System, along with the execution component design from within the HAL 9000 Space Operating System, this design paper will detail the initial HAL System software architecture and interfaces as applied to NASA's Habitat Demonstration Unit (HDU) in support of the Advanced Exploration Systems, Autonomous Mission Operations project. The development and implementation of integrated simulators within this development effort will also be detailed and is the first step in verifying the HAL 9000 Integrated Test-Bed Component [2] designs effectiveness. This design paper will conclude with a summary of the current development status and future development goals as it pertains to automated command and control for the HDU.

Haddock, Angie T.↗
NASA NTRS1986

Automation software for a materials testing laboratory

A comprehensive software system for automating much of the experimental process has recently been completed at the Lewis Research Center's high-temperature fatigue and structures laboratory. The system was designed to support experiment definition and conduct, results analysis and archiving, and report generation activities. This was accomplished through the design and construction of several software systems, as well as through the use of several commercially available software products, all operating on a local, distributed minicomputer system. Experimental capabilities currently supported in an automated fashion include both isothermal and thermomechanical fatigue and deformation testing capabilities. The future growth and expansion of this system will be directed toward providing multiaxial test control, enhanced thermomechanical test control, and higher test frequency (hundreds of hertz).

Mcgaw, Michael A.↗
NASA NTRS1998

Automated pH Control of Nutrient Solution in a Hydroponic Plant Growth System

Over, the years, NASA has played an important role in providing to and the development of automated nutrient delivery and monitoring, systems for growing crops hydroponically for long term space missions. One example are the systems used in the Biomass Production Chamber (BPC) at Kennedy Space Center (KSC). The current KSC monitoring system is based on an engineering workstation using standard analog/digital input/output hardware and custom written software. The monitoring system uses completely separate sensors to provide a check of control sensor accuracy and has the ability to graphically display and store data form past experiment so that they are available for data analysis [Fortson, 1992]. In many cases, growing systems have not been fitted with the kind of automated control systems as used at KSC. The Center for Food and Environmental Systems for Human Exploration of Space (CFESH) located on the campus of Tuskegee University, has effectively grown sweetpotatoes and peanuts hydroponically for the past five years. However they have adjusted the pH electrical conductivity and volume of the hydroponic nutrient solution only manually at times when the solution was to be replenished or changed out according to its protocol (e.g. one-week, two-week, or two-day cycle). But the pH of the nutrient solution flowing through the channel is neither known nor controlled between the update, change out, or replenishment period. Thus, the pH of the nutrient solution is not held at an optimum level over the span of the plant's growth cycle. To solve this dilemma, an automated system for the control and data logging of pH data relative to sweetpotato production using the nutrient film technique (NFT) has been developed, This paper discusses a microprocessor-based system, which was designed to monitor, control, and record the pH of a nutrient solution used for growing sweetpotatoes using NFT.

Smith, B.↗
NASA NTRS1978

Recent advances in thermal-structural analysis and design

A continuing effort to develop a comprehensive capability for thermal-structural analysis and automated design (sizing) is reviewed. A principal role in the activity is played by the finite element program SPAR which contains both an efficient structural and thermal analysis capability. The benefit of having thermal and structural analyses in the same finite element program is illustrated by the application of SPAR to design calculations for the National Transonic Facility - a cryogenic wind tunnel under construction at Langley. Some experience with large-scale thermal structural analysis problems, particularly the space shuttle orbiter, has led to the identification of some analysis needs. Those needs include automated model generation and data output for lumped parameter thermal analysis, faster solution methods for nonlinear transient heat transfer, automated interpolation of temperature data from a thermal finite element model to a dissimilar structural finite model, and automated techniques to identify the times at which the critical combinations of transient heating and loads occur on a structure.

Adelman, H. M.↗
NASA NTRS1982

Automation of crew procedures using multifunction display and control systems

A multifunction display and control system (MFDCS) design concept has been developed for the Orbiter spacecraft. The system provides for automation of crew procedures, fault prioritization, incorporation of checklists and procedures into the display and control system and system flexibility in response to mission variation, increased experience and advancing display and control technology. Hardware included in the system includes a multifunction keyboard using programmable legend switches, a medium size flat panel display for presentation of alphanumeric information and a color CRT for the display of schematic diagrams. The access schema for the multifunction display and control system preserves the single function capability of the present set of dedicated switches while also providing for automation of many of the checklists and procedures. A basic design feature of the system is the ability to change the relative level of automation and crew interaction without modifying the system hardware or basic software operating system.

Spiger, R. J.↗
NASA NTRS2006

Fluorescent Approaches to High Throughput Crystallography

We have shown that by covalently modifying a subpopulation, less than or equal to 1%, of a macromolecule with a fluorescent probe, the labeled material will add to a growing crystal as a microheterogeneous growth unit. Labeling procedures can be readily incorporated into the final stages of purification, and the presence of the probe at low concentrations does not affect the X-ray data quality or the crystallization behavior. The presence of the trace fluorescent label gives a number of advantages when used with high throughput crystallizations. The covalently attached probe will concentrate in the crystal relative to the solution, and under fluorescent illumination crystals show up as bright objects against a dark background. Non-protein structures, such as salt crystals, will not incorporate the probe and will not show up under fluorescent illumination. Brightly fluorescent crystals are readily found against less bright precipitated phases, which under white light illumination may obscure the crystals. Automated image analysis to find crystals should be greatly facilitated, without having to first define crystallization drop boundaries as the protein or protein structures is all that shows up. Fluorescence intensity is a faster search parameter, whether visually or by automated methods, than looking for crystalline features. We are now testing the use of high fluorescence intensity regions, in the absence of clear crystalline features or "hits", as a means for determining potential lead conditions. A working hypothesis is that kinetics leading to non-structured phases may overwhelm and trap more slowly formed ordered assemblies, which subsequently show up as regions of brighter fluorescence intensity. Preliminary experiments with test proteins have resulted in the extraction of a number of crystallization conditions from screening outcomes based solely on the presence of bright fluorescent regions. Subsequent experiments will test this approach using a wider range of proteins. The trace fluorescently labeled crystals will also emit with sufficient intensity to aid in the automation of crystal alignment using relatively low cost optics, further increasing throughput at synchrotrons.

Pusey, Marc L.↗
DOE OSTI2025

End-to-end deep learning pipeline for real-time Bragg peak segmentation: from training to large-scale deployment

X-ray crystallography reconstruction, which transforms discrete X-ray diffraction patterns into three-dimensional molecular structures, relies critically on accurate Bragg peak finding for structure determination. As X-ray free electron laser (XFEL) facilities advance toward MHz data rates (1 million images per second), traditional peak finding algorithms that require manual parameter tuning or exhaustive grid searches across multiple experiments become increasingly impractical. While deep learning approaches offer promising solutions, their deployment in high-throughput environments presents significant challenges in automated dataset labeling, model scalability, edge deployment efficiency, and distributed inference capabilities. We present an end-to-end deep learning pipeline with three key components: (1) a data engine that combines traditional algorithms with our peak matching algorithm to generate high-quality training data at scale, (2) a modular architecture that scales from a few million to hundreds of million parameters, enabling us to train large expert-level models offline while deploying smaller, distilled models at the edge, and (3) a decoupled producer-consumer architecture that separates specialized data source layer from model inference, enabling flexible deployment across diverse computing environments. Using this integrated approach, our pipeline achieves accuracy comparable to traditional methods tuned by human experts while eliminating the need for experiment-specific parameter tuning. Although current throughput requires optimization for MHz facilities, our system's scalable architecture and demonstrated model compression capabilities provide a foundation for future high-throughput XFEL deployments.

Wang, Cong↗