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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Searchlight Source Code

SAND2024-01982O The Searchlight Source Code is software for creating, managing, and dismantling experiments. It also is a simple web server that mimics an online training module with scripts to automate a client. 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.

Robinson, Matthew↗
NASA NTRS1992

Improvement in the control aspect of laser frequency stabilization for SUNLITE project

Flight Electronics Division of Langley Research Center is developing a spaceflight experiment called the Stanford University and NASA Laser In-Space Technology (SUNLITE). The objective of the project is to explore the fundamental limits on frequency stability using an FM laser locking technique on a Nd:YAG non-planar ring (free-running linewidth of 5 KHz) oscillator in the vibration free, microgravity environment of space. Compact and automated actively stabilized terahertz laser oscillators will operate in space with an expected linewidth of less than 3 Hz. To implement and verify this experiment, NASA engineers have designed and built a state of the art, space qualified high speed data acquisition system for measuring the linewidth and stability limits of a laser oscillator. In order to achieve greater stability and better performance, an active frequency control scheme requiring the use of a feedback control loop has been applied. In the summer of 1991, the application of control theory in active frequency control as a frequency stabilization technique was investigated. The results and findings were presented in 1992 at the American Control Conference in Chicago, and have been published in Conference Proceedings. The main focus was to seek further improvement in the overall performance of the system by replacing the analogue controller by a digital algorithm.

Zia, Omar↗
NASA NTRS2004

Space Station Biological Research Project (SSBRP) Cell Culture Unit (CCU) and incubator for International Space Station (ISS) cell culture experiments

The CCU and Incubator are habitats under development by SSBRP for gravitational biology research on ISS. They will accommodate multiple specimen types and reside in either Habitat Holding Racks, or the Centrifuge Rotor, which provides selectable gravity levels of up to 2 g. The CCU can support multiple Cell Specimen Chambers, CSCs (18, 9 or 6 CSCs; 3, 10 or 30 mL in volume, respectively). CSCs are temperature controlled from 4-39 degrees C, with heat shock to 45 degrees C. CCU provides automated nutrient supply, magnetic stirring, pH/O2 monitoring, gas supply, specimen lighting, and video microscopy. Sixty sample containers holding up to 2 mL each, stored at 4-39 degrees C, are available for automated cell sampling, subculture, and injection of additives and fixatives. CSCs, sample containers, and fresh/spent media bags are crew-replaceable for long-term experiments. The Incubator provides a 4-45 degrees C controlled environment for life science experiments or storage of experimental reagents. Specimen containers and experiment unique equipment are experimenter-provided. The Specimen Chamber exchanges air with ISS cabin and has 18.8 liters of usable volume that can accommodate six trays and the following instrumentation: five relocatable thermometers, two 60 W power outlets, four analog ports, and one each relative humidity sensor, video port, ethernet port and digital input/output port.

NASA Center ARC↗
DOE OSTI2023

Machine-learning-assisted automation of single-crystal neutron diffraction

Neutron scattering is a powerful but expensive technique to study materials and discover new matter. Advanced detector technology has significantly improved the efficiency of neutron experiments, increasing the complexity of neutron data reduction and analysis. Machine learning (ML) brings new directions for neutron diffraction data reduction and experiment operation. Here, this work presents an ML-assisted data reduction and analysis method for precise recognition of Bragg peaks and the corresponding regions of interest; it can then automatically screen and align a measured crystal using the recognized peaks, and subsequently plan and optimize the data collection with user-provided information and uncertainty quantification values of detected peaks. This method shows robust performance in different complex sample environments and enables automated single-crystal neutron diffraction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Machine Learning Algorithms for Automated NIF Capsule Mandrel Selection

Small shells, approximately 2 mm in diameter, made from Poly(α-methylstyrene) (PAMS) are used as mandrels in the production of glow discharge polymer capsules located at the center of inertial confinement fusion experiments. The visual inspection process of microscope images of these shell mandrels, including detection of micron-sized defects on the shell surface as well as the handling and sorting, is a very labor-intensive, repetitive, and highly subjective process that stands to benefit greatly from automation. As part of an effort to decrease the number of labor hours spent in capsule handling, inspection, and metrology, the development of robotic systems was presented in a paper by Carlson et al., “Automation in Target Fabrication” [Fusion Sci. Technol., Vol. 70, p. 274 (2016)]. The current work expands the automated image acquisition systems developed previously and adds the use of convolutional neural networks to select capsules best suited for use in the downstream production process. Through the use of these machine learning algorithms, the selection process becomes robust, repeatable, and operator independent. Finally, as an added benefit the system developed as part of this work is able to provide defect statistics on entire shell batches and feed this information upstream to the production team.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Optode Images, and Dissolved Oxygen Data from Sand and Sediment Flow-through Column Experiments associated with: "2-D Imaging of Dissolved Oxygen Concentration in Flow-Through Sediment Columns"

This data package is associated with the publication "2-D Imaging of Dissolved Oxygen Concentration in Flow-Through Sediment Columns" submitted to Frontiers in Water (Garayburu-Caruso et al., 2022). This work presents a novel application of planar optode technology to sediment columns that allows the study of well-constrained flow fields without the need to assume completely homogeneous flow. We introduce a flow-through column with the interior coated in an oxygen sensing film and a series of sampling ports as a unique tool capable of capturing changes in dissolved oxygen (DO) at high frequency (10 s) and spatial (< 1 mm) resolution across the length of a column. In addition, we provide custom scripts that allows image processing steps to be automated and consistently reproduced over a variety of experimental conditions. This dataset is comprised of four folders (1) 01_Riverbed_Sediment_Experiment, (2) 02_Sand_Experiment, (3) 01_Riverbed_Sediment_Raw_Images, and (4) 02_Sand_Experiment_Raw_Images. 01_Riverbed_Sediment_Experiment contains (1) a subfolder with csv files that contain statistical parameters from the linear regressions applied to each optode image, (2) a subfolder with csv files from DO data measured by in-line sensors, (3) a subfolder with csv files containing column and injection specific input parameters for the image processing script, and (4) a subfolder with scripts used to process the images and create associated figures. 02_Sand_Experiment contains (1) a subfolder with csv files containing column and injection-specific input parameters for the image processing script, and (2) a subfolder with scripts used to process the images and create associated figures. 01_Riverbed_Sediment_Raw_Images (spited in 3 parts due to size) contains a subfolder with raw red, and green images from the optode system during the MilliQ Injection, Vanillin Injection or Vanillin + Sampling Injection respectively. 02_Sand_Experiment_Raw_Images contains a subfolder with raw red, and green images from the optode system. Outside of the main folders there is a csv containing file-level metadata and a csv data dictionary defining column headers for all csv files contained in the data package.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Large-Scale Spacecraft Fire Safety Experiments in ISS Resupply Vehicles

Our understanding of the fire safety risk in manned spacecraft has been limited by the small scale of the testing we have been able to conduct in low-gravity. Fire growth and spread cannot be expected to scale linearly with sample size so we cannot make accurate predictions of the behavior of realistic scale fires in spacecraft based on the limited low-g testing to date. As a result, spacecraft fire safety protocols are necessarily very conservative and costly. Future crewed missions are expected to be longer in duration than previous exploration missions outside of low-earth orbit and accordingly, more complex in terms of operations, logistics, and safety. This will increase the challenge of ensuring a fire-safe environment for the crew throughout the mission. Based on our fundamental uncertainty of the behavior of fires in low-gravity, the need for realistic scale testing at reduced gravity has been demonstrated. To address this concern, a spacecraft fire safety research project is underway to reduce the uncertainty and risk in the design of spacecraft fire safety systems by testing at nearly full scale in low-gravity. This project is supported by the NASA Advanced Exploration Systems Program Office in the Human Exploration and Operations Mission Directorate. The activity of this project is supported by an international topical team of fire experts from other space agencies to maximize the utility of the data and to ensure the widest possible scrutiny of the concept. The large-scale space flight experiment will be conducted on three missions; each in an Orbital Sciences Corporation Cygnus vehicle after it has deberthed from the ISS. Although the experiment will need to meet rigorous safety requirements to ensure the carrier vehicle does not sustain damage, the absence of a crew allows the fire products to be released into the cabin. The tests will be fully automated with the data downlinked at the conclusion of the test before the Cygnus vehicle reenters the atmosphere. The international topical team is collaborating with the NASA team in the definition of the experiment requirements and performing supporting analysis, experimentation and technology development.

Combustion↗
DOE OSTI2023

Automated X-Ray Tomographic Defect Analysis in High Density Carbon Capsules

High density carbon capsule ablators are of primary interest for National Ignition Facility experiments. Two of the major contributors to hydrodynamic instabilities in these capsules are voids and high-density inclusions, where the quantity and size of these defects can result in lower yields in inertial confinement fusion. To aid in capsule selection, General Atomics developed a LabVIEW analysis routine to quantify these defects based off a large field of view tomographic dataset and provide insight into the quality of the capsule. Furthermore, this analysis determines if there are large voids or inclusions that may affect shot performance and helps rank which capsules should be used.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

NUM-DAT File Format Specification: Used in M-9 Gun Experiment Data Archiving

The M-9 Shock and Detonation Physics group executes experiments on gun and explosive platforms with large numbers of oscilloscopes used for data acquisition. The data acquisition from these oscilloscopes was automated many years ago using a custom piece of software called RunDig . The default save format from this software is a custom structure referred to as "NUM-DAT" format. This file format includes a text ".DAT" file which is a header file used to interpret the binary ".NUM" file which contains the oscilloscope data. The data save format was originally developed by John Vorthman and has been in use by M-9 personnel for over 20 years. This data format has been used for archiving data from experiments performed by M-9 personnel at TA-40, TA-39, and the TA-55 Impact Test Facility. Numerous custom analysis and visualization programs have also been developed, and continue to be used, that utilize this data format. This document describes the NUM-DAT format and provides code examples for reading the format and converting it to other formats.

47 OTHER INSTRUMENTATION↗
NASA NTRS1985

Human factors in cockpit automation: A field study of flight crew transition

The factors which affected two groups of airline pilots in the transition from traditional airline cockpits to a highly automated version were studied. All pilots were highly experienced in traditional models of the McDonnell-Douglas DC-9 prior to their transition to the more automated DC-9-80. Specific features of the new aircraft, particularly the digital flight guidance system (DFGS) and other automatic features such as the autothrottle system (ATS), autobrake, and digital display were studied. Particular attention was paid to the first 200 hours of line flying experience in the new aircraft, and the difficulties that some pilots found in adapting to the new systems during this initial operating period. Efforts to prevent skill loss from automation, training methods, traditional human factors issues, and general views of the pilots toward cockpit automation are discussed.

Wiener, E. L.↗
DOE OSTI2023

Fast and efficient identification of anomalous galaxy spectra with neural density estimation

ABSTRACT Current large-scale astrophysical experiments produce unprecedented amounts of rich and diverse data. This creates a growing need for fast and flexible automated data inspection methods. Deep learning algorithms can capture and pick up subtle variations in rich data sets and are fast to apply once trained. Here, we study the applicability of an unsupervised and probabilistic deep learning framework, the probabilistic auto-encoder, to the detection of peculiar objects in galaxy spectra from the SDSS survey. Different to supervised algorithms, this algorithm is not trained to detect a specific feature or type of anomaly, instead it learns the complex and diverse distribution of galaxy spectra from training data and identifies outliers with respect to the learned distribution. We find that the algorithm assigns consistently lower probabilities (higher anomaly score) to spectra that exhibit unusual features. For example, the majority of outliers among quiescent galaxies are E+A galaxies, whose spectra combine features from old and young stellar population. Other identified outliers include LINERs, supernovae, and overlapping objects. Conditional modelling further allows us to incorporate additional information. Namely, we evaluate the probability of an object being anomalous given a certain spectral class, but other information such as metrics of data quality or estimated redshift could be incorporated as well. We make our code publicly available.

Böhm, Vanessa↗
DOE OSTI2020

An Approach to DevOps and Microservices

This report presents work performed in 2017 and is a reissue of the end-of-year report SAND2018-0240, A Proof-of-Concept Approach to DevOps and Microservices, January 2018, modified for unlimited release. This report describes the approach, investigation, and prototyping efforts to create an API management solution and automated deployment pipeline for REST-based microservices. Additionally, it reviews: the microservices created for testing purposes; our experiences and results in using an open-source API management tool; and future plans.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Artificial Intelligence in Nuclear Physics

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly developing fields providing data-driven algorithms to predict, classify, and make decisions based on data. Nuclear Physics Research is data-driven and AI/ML techniques have been implemented for experiment and accelerator control, in theoretical applications, and in data processing and analysis. These algorithms open possibilities for automation, thereby augmenting human capabilities. Additionally, Open Science is enabled by simultaneous analyses of multiple data sources, leading to scientific knowledge. This talk will summarize current applications of AI/ML in nuclear physics, as well as accelerator applications, and will cover upcoming initiatives and research in AI/ML.

Jeske, Torri↗
NASA NTRS1983

Human factors in space telepresence

The problems of interfacing a human with a teleoperation system, for work in space are discussed. Much of the information presented here is the result of experience gained by the M.I.T. Space Systems Laboratory during the past two years of work on the ARAMIS (Automation, Robotics, and Machine Intelligence Systems) project. Many factors impact the design of the man-machine interface for a teleoperator. The effects of each are described in turn. An annotated bibliography gives the key references that were used. No conclusions are presented as a best design, since much depends on the particular application desired, and the relevant technology is swiftly changing.

Akin, D. L.↗
NASA NTRS1986

A radar data processing and enhancement system

This report describes the space position data processing system of the NASA Western Aeronautical Test Range. The system is installed at the Dryden Flight Research Facility of NASA Ames Research Center. This operational radar data system (RADATS) provides simultaneous data processing for multiple data inputs and tracking and antenna pointing outputs while performing real-time monitoring, control, and data enhancement functions. Experience in support of the space shuttle and aeronautical flight research missions is described, as well as the automated calibration and configuration functions of the system.

Anderson, K. F.↗
NASA NTRS1987

Software-implemented fault insertion: An FTMP example

This report presents a model for fault insertion through software; describes its implementation on a fault-tolerant computer, FTMP; presents a summary of fault detection, identification, and reconfiguration data collected with software-implemented fault insertion; and compares the results to hardware fault insertion data. Experimental results show detection time to be a function of time of insertion and system workload. For the fault detection time, there is no correlation between software-inserted faults and hardware-inserted faults; this is because hardware-inserted faults must manifest as errors before detection, whereas software-inserted faults immediately exercise the error detection mechanisms. In summary, the software-implemented fault insertion is able to be used as an evaluation technique for the fault-handling capabilities of a system in fault detection, identification and recovery. Although the software-inserted faults do not map directly to hardware-inserted faults, experiments show software-implemented fault insertion is capable of emulating hardware fault insertion, with greater ease and automation.

Czeck, Edward W.↗
NASA NTRS1994

Microencapsulation of anti-tumor, antibiotic and thrombolytic drugs in microgravity

Encapsulation of cytotoxic or labile drugs enables targeted delivery and sustained release kinetics that are not available with intravenous injection. A new liquid-liquid diffusion process has been developed for forming unique microcapsules that contain both aqueous and hydrocarbon soluble drugs. Microgravity experiments, on sounding rockets (1989-92) and Shuttle missions STS-52 (1992) and STS-56 (1993) using an automated Materials Dispersion Apparatus, produced multi-lamellar microcapsules containing both Cis-platinum (anti-tumor drug) and iodinated poppy seed oil (a radiocontrast medium), surrounded by a polyglyceride skin. Microcapsules formed with amoxicillin (antibiotic) or urokinase (a clot dissolving enzyme), co-encapsulated with IPO, are still intact after two years. Microcapsules were formed with the drug so concentrated that crystals formed inside. Multi-layered microspheres, with both hydrophobic drug compartments, can enable diffusion of complementary drugs from the same microcapsule, e.g. antibiotics and immuno-stimulants to treat resistant infections or multiple fibrinolytic drugs to dissolve emboli. Co-encapsulation of enough radio-contrast medium enables oncologists to monitor the delivery of anti-tumor microcapsules to target tumors using computerized tomography and radiography that would track the distribution of microcapsules after release from the intra-arterial catheter. These microcapsules could have important applications in chemotheraphy of certain liver, kidney, brain and other tumors.

Morrison, Dennis R.↗
NASA NTRS1998

Directional Solidification of Mercury Cadmium Telluride in Microgravity

Mercury cadmium telluride (MCT) has been directionally solidified for ten days in the Advanced Automated Directional Solidification Furnace (AADSF) on the second United States Microgravity Payload Mission (USMP-2). A second growth experiment is planned for the USMP-4 mission in November 1997. Results from USMP-2 demonstrated significant changes between microgravity and ground-based experiments, particularly in the compositional homogeneity. Changes were also observed during the microgravity mission which were dependent on the attitude of the space shuttle and the relative magnitudes of axial and transverse residual accelerations with respect to the growth axis of the crystal. Issues of shuttle operation, especially those concerned with safety and navigation, and the science needs of other payloads dictated the need for changes in attitude. One consequence for solidification of MCT in the USMP4 mission is the desire for a shorter growth time to complete the experiment without subjecting the sample to shuttle maneuvers. By using a seeded technique and a pre-processed boule of MCT with an established diffusion layer quenched into the solid, equilibrium steady state growth can be established within 24 hours, rather than the three days needed in USMP-2. The growth of MCT in AADSF during the USMP-4 mission has been planned to take less than 72 hours with 48 hours of actual growth time. A review of the USMP-2 results will be presented, and the rationale for the USMP-4 explained. Pre-mission ground based tests for the USN4P-4 mission will be presented, as will any available preliminary flight results from the mission.

Lechoczhy, Sandor L.↗