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At least 325 records · Page 18

A Systematic Approach for Real-Time Operator Functional State Assessment

A task overload condition often leads to high stress for an operator, causing performance degradation and possibly disastrous consequences. Just as dangerous, with automated flight systems, an operator may experience a task underload condition (during the en-route flight phase, for example), becoming easily bored and finding it difficult to maintain sustained attention. When an unexpected event occurs, either internal or external to the automated system, the disengaged operator may neglect, misunderstand, or respond slowly/inappropriately to the situation. In this paper, we discuss an approach for Operator Functional State (OFS) monitoring in a typical aviation environment. A systematic ground truth finding procedure has been designed based on subjective evaluations, performance measures, and strong physiological indicators. The derived OFS ground truth is continuous in time compared to a very sparse estimation of OFS based on an expert review or subjective evaluations. It can capture the variations of OFS during a mission to better guide through the training process of the OFS assessment model. Furthermore, an OFS assessment model framework based on advanced machine learning techniques was designed and the systematic approach was then verified and validated with experimental data collected in a high fidelity Boeing 737 simulator. Preliminary results show highly accurate engagement/disengagement detection making it suitable for real-time applications to assess pilot engagement.

Zhang, Guangfan↗

An Autonomous System for Experimental Evolution of Microbial Cultures: Test Results Using Ultraviolet-C Radiation and Escherichia Coli.

At its core, the field of microbial experimental evolution seeks to elucidate the natural laws governing the history of microbial life by understanding its underlying driving mechanisms. However, observing evolution in nature is complex, as environmental conditions are difficult to control. Laboratory-based experiments for observing population evolution provide more control, but manually culturing and studying multiple generations of microorganisms can be time consuming, labor intensive, and prone to inconsistency. We have constructed a prototype, closed system device that automates the process of directed evolution experiments in microorganisms. It is compatible with any liquid microbial culture, including polycultures and field samples, provides flow control and adjustable agitation, continuously monitors optical density (OD), and can dynamically control environmental pressures such as ultraviolet-C (UV-C) radiation and temperature. Here, the results of the prototype are compared to iterative exposure and survival assays conducted using a traditional hood, UV-C lamp, and shutter system.

Microbial Cultures↗

Simulation of DWPF Chemical Process Cell Using a Reaction Calorimeter

The Defense Waste Processing Facility (DWPF) converts liquid radioactive waste into glass using a Sludge Receipt Adjustment Tank (SRAT) and Slurry Mix Evaporator (SME) in addition to other processes. The SRAT and SME processes can be simulated on a small-scale using the Mettler-Toledo Reaction Calorimeter (RC1). This equipment is able to automate the execution and monitoring of experiments involving nonradioactive chemical simulants. During the chemical processing of sludge in the SRAT process, foam begins to form and can foam over the reaction vessel. The current antifoam used at DWPF creates a risk of increased flammability and has a limited pH range. Usually, mercury is circulated back into the reaction vessel during the SRAT process, making it difficult to remove. To combat foam over, novel antifoams will be tested during the boil-up process using the RC1. To improve mercury extraction, 3D-printed coalescer columns will be tested within the Mercury Water Wash Tank (MWWT) of the RC1. Testing of Simulant Sludge Batch 6 (SB6) was performed to ensure: the sludge would form a stable foam at boiling during full SRAT/SME runs; the antifoam would reduce the amount of foam within the vessel The sludge and a Precipitate Reactor Feed Tank (PRFT) simulant with monosodium titanate (MST) were mixed separately, combined, and then heated to boiling. As shown below, the antifoam used was able to eliminate the foam within the vessel, as expected. The FormLabs Form2 3D Printer can be used to create roughly 3-inch tall and 1-inch diameter columns from clear and ceramic resins. The columns will utilize chemical and physical forces to draw the mercury out of a condensed offgas stream leaving the RC1 reaction vessel. These columns will be tested during full SRAT/SME runs on the basis of how well they are able to collect elemental mercury. In preparation for full-scale runs, the RC1 equipment was assembled onto a custom table and tested with water runs. The software used to control automation, iControl, has a user-friendly interface that allows the experiment to be altered as needed. An example of the data recorded during an experimental run is represented in Figure 1 below. Water runs were utilized as a way to prove if the RC1 system was functioning in the following areas: Boil-up rates, Chemical additions using pumps, Temperature readings, Balance readings, Probe readings, Offgas system, Agitation. Future Plans: Five novel antifoams will be tested during full SRAT/SME runs. The most effective antifoam will be utilized in DWPF's Chemical Process Cell. The design of the Mercury Extraction Coalescer can be further manipulated to increase the extraction of not only elemental mercury, but other heavy metals in environmental remediation processes as well.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Experiences with Text Mining Large Collections of Unstructured Systems Development Artifacts at JPL

Often repositories of systems engineering artifacts at NASA's Jet Propulsion Laboratory (JPL) are so large and poorly structured that they have outgrown our capability to effectively manually process their contents to extract useful information. Sophisticated text mining methods and tools seem a quick, low-effort approach to automating our limited manual efforts. Our experiences of exploring such methods mainly in three areas including historical risk analysis, defect identification based on requirements analysis, and over-time analysis of system anomalies at JPL, have shown that obtaining useful results requires substantial unanticipated efforts - from preprocessing the data to transforming the output for practical applications. We have not observed any quick 'wins' or realized benefit from short-term effort avoidance through automation in this area. Surprisingly we have realized a number of unexpected long-term benefits from the process of applying text mining to our repositories. This paper elaborates some of these benefits and our important lessons learned from the process of preparing and applying text mining to large unstructured system artifacts at JPL aiming to benefit future TM applications in similar problem domains and also in hope for being extended to broader areas of applications.

text mining↗

Experimental discovery of structure–property relationships in ferroelectric materials via active learning

Emergent functionalities of structural and topological defects in ferroelectric materials underpin an extremely broad spectrum of applications ranging from domain wall electronics to high dielectric and electromechanical responses. Many of these functionalities have been discovered and quantified via local scanning probe microscopy methods. However, the search has until now been based on either trial and error, or using auxiliary information such as the topography or domain wall structure to identify potential objects of interest on the basis of the intuition of operator or pre-existing hypotheses, with subsequent manual exploration. Here we report the development and implementation of a machine learning framework that actively discovers relationships between local domain structure and polarization-switching characteristics in ferroelectric materials encoded in the hysteresis loop. The hysteresis loops and their scalar descriptors such as nucleation bias, coercive bias and the hysteresis loop area (or more complex functionals of hysteresis loop shape) and corresponding uncertainties are used to guide the discovery of these relationships via automated piezoresponse force microscopy and spectroscopy experiments. As such, this approach combines the power of machine learning methods to learn the correlative relationships between high-dimensional data, as well as human-based physics insights encoded into the acquisition function. For ferroelectric materials, this automated workflow demonstrates that the discovery path and sampling points of on- and off-field hysteresis loops are largely different, indicating that on- and off-field hysteresis loops are dominated by different mechanisms. Here, the proposed approach is universal and can be applied to a broad range of modern imaging and spectroscopy methods ranging from other scanning probe microscopy modalities to electron microscopy and chemical imaging.

36 MATERIALS SCIENCE↗

Integrated edge-to-exascale workflow for real-time steering in neutron scattering experiments

We introduce a computational framework that integrates artificial intelligence (AI), machine learning, and high-performance computing to enable real-time steering of neutron scattering experiments using an edge-to-exascale workflow. Focusing on time-of-flight neutron event data at the Spallation Neutron Source, our approach combines temporal processing of four-dimensional neutron event data with predictive modeling for multidimensional crystallography. At the core of this workflow is the Temporal Fusion Transformer model, which provides voxel-level precision in predicting 3D neutron scattering patterns. The system incorporates edge computing for rapid data preprocessing and exascale computing via the Frontier supercomputer for large-scale AI model training, enabling adaptive, data-driven decisions during experiments. This framework optimizes neutron beam time, improves experimental accuracy, and lays the foundation for automation in neutron scattering. Although real-time experiment steering is still in the proof-of-concept stage, the demonstrated potential of this system offers a substantial reduction in data processing time from hours to minutes via distributed training, and significant improvements in model accuracy, setting the stage for widespread adoption across neutron scattering facilities and more efficient exploration of complex material systems.

97 MATHEMATICS AND COMPUTING↗

Operator versus computer control of adaptive automation

Adaptive automation refers to real-time allocation of functions between the human operator and automated subsystems. The article reports the results of a series of experiments whose aim is to examine the effects of adaptive automation on operator performance during multi-task flight simulation, and to provide an empirical basis for evaluations of different forms of adaptive logic. The combined results of these studies suggest several things. First, it appears that either excessively long, or excessively short, adaptation cycles can limit the effectiveness of adaptive automation in enhancing operator performance of both primary flight and monitoring tasks. Second, occasional brief reversions to manual control can counter some of the monitoring inefficiency typically associated with long cycle automation, and further, that benefits of such reversions can be sustained for some time after return to automated control. Third, no evidence was found that the benefits of such reversions depend on the adaptive logic by which long-cycle adaptive switches are triggered.

Hilburn, Brian↗

Microbial Vessel for Impedance Spectroscopy and Electrochemistry (Mvise): an Extensible, Interoperable Data Acquisition Platform for Liquid Culture Studies in Space Biology Research

The White House Office of Science and Technology Policy (OSTP) has declared 2023 to be the Year of Open Science following an initiative to democratize scientific knowledge. Simultaneously, new sensor technologies have broadened the experimental space available to bioastronautics research. With these open-science goals and technological advances in mind, we have designed and constructed a data acquisition platform for high-precision, real-time monitoring of liquid culture systems. The vessel rig is fitted with six Atlas Scientific probes (micro pH, electrical conductivity, dissolved oxygen, oxidation-reduction potential, liquid temperature, air CO2) and a custom optical density probe similar to the one on BioSentinel’s BioSensor payload. A custom dielectric spectroscopy probe is also planned. The structure of the vessel is resin 3-D printed on a hobbyist-level machine, reducing the production cost and iteration time by over 60% each while increasing extensibility. Data acquisition and storage is controlled with a standalone C state machine-based program running on a Raspberry Pi 3 Model B. When not running headless, an additional program automatically generates and updates plots for live data visualization. Validation of the rig as a data collection system was performed with a yeast liquid culture experiment. While the vessel rig is currently used for standalone experiments, it can also be used as the base perception unit in a self-driving laboratory (SDL). SDLs are high-throughput data collection systems that employ automation and artificial intelligence to conduct and manage routine experiments. Here, we envision an SDL driven by several vessel rigs in which an automated script compares key results, informing the design of future experiments. A vessel rig SDL would streamline many operations, including 1) strain selection for the Lunar Explorer Instrument for space biology Applications (LEIA) investigation and 2) the study of bioregenerative life support systems (BLSS). Ultimately, the datasets that can now be acquired will provide crucial information for accelerating bioastronautics application development in the era of commercial space.

Stephen Lantin↗

Automated Space Processing Payloads Study. Volume 1: Executive Summary

An investigation is described which examined the extent to which the experiment hardware and operational requirements can be met by automatic control and material handling devices; payload and system concepts are defined which make extensive use of automation technology. Topics covered include experiment requirements and hardware data, capabilities and characteristics of industrial automation equipment and controls, payload grouping, automated payload conceptual design, space processing payload preliminary design, automated space processing payloads for early shuttle missions, and cost and scheduling.

Source record↗

Payload crew training scheduler (PACTS) user's manual

The operation of the payload specialist training scheduler (PACTS) is discussed in this user's manual which is used to schedule payload specialists for mission training on the Spacelab experiments. The PACTS program is a fully automated interactive, computerized scheduling program equipped with tutorial displays. The tutorial displays are sufficiently detailed for use by a program analyst having no computer experience. The PACTS program is designed to operate on the UNIVAC 1108 computer system, and has the capability to load output into a PDP 11/45 Interactive Graphics Display System for printing schedules. The program has the capacity to handle up to three overlapping Spacelab missions.

Shipman, D. L.↗

Enhancing and Archiving the APS Catalog of the POSS I

We have worked on two different projects: 1) Archiving the APS Catalog of the POSS I for distribution to NASA's NED at IPAC, SIMBAD in France, and individual astronomers and 2) The automated morphological classification of galaxies. We have completed archiving the Catalog into easily readable binary files. The database together with the software to read it has been distributed on DVD's to the national and international data centers and to individual astronomers. The archived Catalog contains more than 89 million objects in 632 fields in the first epoch Palomar Observatory Sky Survey. Additional image parameters not available in the original on-line version are also included in the archived version. The archived Catalog is also available and can be queried at the APS web site (URL: http://aps.umn.edu) which has been improved with a much faster and more efficient querying system. The Catalog can be downloaded as binary datafiles with the source code for reading it. It is also being integrated into the SkyQuery system which includes the Sloan Digital Sky Survey, 2MASS, and the FIRST radio sky survey. We experimented with different classification algorithms to automate the morphological classification of galaxies. This is an especially difficult problem because there are not only a large number of attributes or parameters and measurement uncertainties, but also the added complication of human disagreement about the adopted types. To solve this problem we used 837 galaxy images from nine POSS I fields at the North Galactic Pole classified by two independent astronomers for which they agree on the morphological types. The initial goal was to separate the galaxies into the three broad classes relevant to issues of large scale structure and galaxy formation and evolution: early (ellipticals and lenticulars), spirals, and late (irregulars) with an accuracy or success rate that rivals the best astronomer classifiers. We also needed to identify a set of parameters derived from the digitized images that separate the galaxies by type. The human eye can easily recognize complicated patterns in images such as spiral arms which can be spotty, blotchy affairs that are difficult for automated techniques. A galaxy image can potentially be described by hundreds of parameters, all of which may have some relation to the morphological type. In the set of initial experiments we used 624 such parameters, in two colors, blue and red. These parameters include the surface brightness and color measured at different radii, ratios of these parameters at different radii, concentration indices, Fourier transforms and wavelet decomposition coefficients. We experimented with three different classes of classification algorithms; decision trees, k-nearest neighbors, and support vector machines (SVM). A range of experiments were conducted and we eventually narrowed the parameters to 23 selected parameters. SVM consistently outperformed the other algorithms with both sets of features. By combining the results from the different algorithms in a weighted scheme we achieved an overall classification success of 86%.

Humphreys, Roberta M.↗

Proceedings of the 20th International Symposium on Space Flight Dynamics

Topics include: Measuring Image Navigation and Registration Performance at the 3-Sigma Level Using Platinum Quality Landmarks; Flight Dynamics Performances of the MetOp A Satellite during the First Months of Operations; Visual Navigation - SARE Mission; Determining a Method of Enabling and Disabling the Integral Torque in the SDO Science and Inertial Mode Controllers; Guaranteeing Pointing Performance of the SDO Sun-Pointing Controllers in Light of Nonlinear Effects; SDO Delta H Mode Design and Analysis; Observing Mode Attitude Controller for the Lunar Reconnaissance Orbiter; Broken-Plane Maneuver Applications for Earth to Mars Trajectories; ExoMars Mission Analysis and Design - Launch, Cruise and Arrival Analyses; Mars Reconnaissance Orbiter Aerobraking Daily Operations and Collision Avoidance; Mars Reconnaissance Orbiter Interplanetary Cruise Navigation; Motion Parameters Determination of the SC and Phobos in the Project Phobos-Grunt; GRAS NRT Precise Orbit Determination: Operational Experience; Orbit Determination of LEO Satellites for a Single Pass through a Radar: Comparison of Methods; Orbit Determination System for Low Earth Orbit Satellites; Precise Orbit Determination for ALOS; Anti-Collision Function Design and Performances of the CNES Formation Flying Experiment on the PRISMA Mission; CNES Approaching Guidance Experiment within FFIORD; Maneuver Recovery Analysis for the Magnetospheric Multiscale Mission; SIMBOL-X: A Formation Flying Mission on HEO for Exploring the Universe; Spaceborne Autonomous and Ground Based Relative Orbit Control for the TerraSAR-X/TanDEM-X Formation; First In-Orbit Experience of TerraSAR-X Flight Dynamics Operations; Automated Target Planning for FUSE Using the SOVA Algorithm; Space Technology 5 Post-Launch Ground Attitude Estimation Experience; Standardizing Navigation Data: A Status Update; and A Study into the Method of Precise Orbit Determination of a HEO Orbiter by GPS and Accelerometer.

Woodard, Mark↗

Cloud identification using genetic algorithms and massively parallel computation

As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user's manual was written and distributed nationwide to scientists whose work might benefit from its availability. Several papers, including two journal articles, were produced.

Buckles, Bill P.↗

Cross-Facility Orchestration of Electrochemistry Experiments and Computations

Instrument-computing ecosystems supporting automated electrochemical workflows typically require the integration of disparate instruments such as syringe pump, fraction collector, and potentiostat, all connected to an electrochemical cell. These specialized instruments with custom software and interfaces are not typically designed for network integration and remote automation. We developed a networked ecosystem of these instruments and computing platforms, which includes software to enable automated workflow orchestration from remote computers. Specifically, we developed Python wrappers of APIs and custom Pyro client-server modules to support remote operation of these instruments over the ecosystem network. Herein, we describe a specific workflow for generating and validating voltammogram (I-V) measurements of an electrolyte solution pumped into the electrochemical cell. We demonstrate the orchestration of this workflow which is composed using a Jupyter notebook and executed on a remote computer.

Al Najjar, Anees↗

Automated space processing payloads study. Volume 2, book 1: Technical report

The extent was investigated to which experiment hardware and operational requirements can be met by automatic control and material handling devices; payload and system concepts that make extensive use of automation technology are defined. Hardware requirements for each experiment were established and tabulated, and investigations of applicable existing hardware were documented. The capabilities and characteristics of industrial automation equipment, controls, and techniques are presented in the form of a summary of applicable equipment characteristics in three basic mutually-supporting formats. Facilities for performing groups of experiments are defined along with four levitation groups and three furnace groups; major hardware elements required to implement them were identified. A conceptual design definition of ten different automated processing facilities is presented along with the specific equipment to implement each facility and the design layouts of the different units. Constraints and packaging, weight, and power requirements for six payloads postulated for shuttle missions in the 1979 to 1982 time period were examined.

Source record↗

Automated tracking of prefabricated components for areal-time evaluator to optimize and automateinstallation

Trade associations for prefabricated construction estimate that about 50% of prefabricated wall projects have alignment problems that lead to defects and rework. Additionally, component installation times average between 30 and 60 minutes per component. To address these issues, a real-time evaluator (RTE) system was introduced to decrease cost and automate prefabricated component installation by reducing the installation time, decreasing rework, and enhancing energy performance through higher installation quality. The RTE uses commonly available hardware and software to perform autonomous tracking to measure the real-time location and orientation of components as they are crane-lifted and installed. The hardware, software, and algorithms that allow the autonomous tracking of components are detailed. An algorithm to automate the initial search for a component with three attached retroreflectors is proposed. Algorithms to automate the measurement of component position and orientation are also proposed. Simple lab-scale proof-of-concept experiments were conducted to assess the algorithms for automation of component searching, measurement of real-time movement, and measurement of component orientation. With additional development, the system can be used as a tool to generate the commands for autonomous crane operation or single-task construction robots.

Hayes, Nolan↗

Exploring the working range of automated standard dilution analysis of nutrient elements in foods by inductively coupled plasma optical emission spectrometry

Inductively coupled plasma optical emission spectrometry (ICP-OES) is an important tool for measuring nutrient elements in food. ICP-OES methods typically determine analytical concentrations using external standard calibration but can be susceptible to matrix effects. The method of standard additions does not suffer from matrix effects but is time consuming and labor intensive. Automated standard dilution analysis (SDA) allows for online matrix matched calibration without preparing individual standard additions for each sample matrix. This approach may solve both time and matrix issues and has been described in the literature as an attractive alternative to standard additions. The working range of the method for nutrient elements, however, is an understudied feature of SDA that may be a potential drawback to routine analysis of foods. We evaluated automated SDA performance through the analysis of 10 reference materials and four fortified (i.e., spiked) foods spanning the AOAC food triangle. We evaluated the working range, accuracy, and precision for analyses of nutrient elements in foods. Accepted accuracy (80–120% recovery) was achieved for 10 nutrient elements, Ca, Cu, Fe, K, Mg, Mn, Na, P, S, and Zn, when the analytical solution concentration to standard concentration ratio was less than 10. This equates to a working range for each element spanning at least two orders of magnitude. Removing outliers, Z scores (n = 95) ranged from –1.8 to 0.88, and the average recovery (n = 85) from fortification experiments was 97 ± 12% (2σ). Therefore, automated SDA applied to ICP-OES may be used for nutrient elemental analyses in samples with difficult matrices such as foods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SATS HVO Concept Validation Experiment

A human-in-the-loop simulation experiment was conducted at the NASA Langley Research Center s (LaRC) Air Traffic Operations Lab (ATOL) in an effort to comprehensively validate tools and procedures intended to enable the Small Aircraft Transportation System, Higher Volume Operations (SATS HVO) concept of operations. The SATS HVO procedures were developed to increase the rate of operations at non-towered, non-radar airports in near all-weather conditions. A key element of the design is the establishment of a volume of airspace around designated airports where pilots accept responsibility for self-separation. Flights operating at these airports, are given approach sequencing information computed by a ground based automated system. The SATS HVO validation experiment was conducted in the ATOL during the spring of 2004 in order to determine if a pilot can safely and proficiently fly an airplane while performing SATS HVO procedures. Comparative measures of flight path error, perceived workload and situation awareness were obtained for two types of scenarios. Baseline scenarios were representative of today s system utilizing procedure separation, where air traffic control grants one approach or departure clearance at a time. SATS HVO scenarios represented approaches and departure procedures as described in the SATS HVO concept of operations. Results from the experiment indicate that low time pilots were able to fly SATS HVO procedures and maintain self-separation as safely and proficiently as flying today's procedures.

Consiglio, Maria↗