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At least 253 records · Page 14

Human Automation Teaming: Lessons Learned and Future Directions

Full autonomy seems to be the goal for system developers in almost every area of the economy. However, as we move from automated systems to autonomous systems, designers have needed to insert humans to oversee automation that has traditionally been brittle or incomplete. This creates its own problems as the operator is usually out of the loop when the automation hands over problems that it cannot handle. To better handle these situations, it has been proposed that we develop human automation teams that have shared goals and objectives to support task performance. This paper will describe an initial model of Human Automation Teaming (HAT) which has three elements: transparency, bi-directional communications, and human-directed execution. Transparency in our model is a method for giving insight into the reasoning behind automated recommendations and actions, bi-directional communication allows the operator to communicate directly with the automation, and finally the automation defers execution to the human. The model was implemented through a number of features on an electronic flight bag (EFB) which are described in the paper. The EFB was installed in a mid-fidelity flight simulator and used by 12 airline pilots to support diversion decisions during off-nominal flight scenarios. Pilots reported that working with the HAT automation made diversion decisions easier and reduced their workload. They also reported that the information provided about diversion airports was similar to what they would receive from ground dispatch, thus making coordination with dispatch easier and less time consuming. These HAT features engender more trust in the automation when appropriate, and less when not, allowing improved supervision of automated functions by flight crews.

Human-Autonomy Teaming↗

Capturing, using, and managing quality assurance knowledge for shuttle post-MECO flight design

Ascent initialization values used by the Shuttle's onboard computer for nominal and abort mission scenarios are verified by a six degrees of freedom computer simulation. The procedure that the Ascent Post Main Engine Cutoff (Post-MECO) group uses to perform quality assurance (QA) of the simulation is time consuming. Also, the QA data, checklists and associated rationale, though known by the group members, is not sufficiently documented, hindering transfer of knowledge and problem resolution. A new QA procedure which retains the current high level of integrity while reducing the time required to perform QA is needed to support the increasing Shuttle flight rate. Documenting the knowledge is also needed to increase its availability for training and problem resolution. To meet these needs, a knowledge capture process, embedded into the group activities, was initiated to verify the existing QA checks, define new ones, and document all rationale. The resulting checks were automated in a conventional software program to achieve the desired standardization, integrity, and time reduction. A prototype electronic knowledge base was developed with Macintosh's HyperCard to serve as a knowledge capture tool and data storage.

Peters, H. L.↗

Advanced Electron Microscopy of Nanophased Synthetic Polymers and Soft Complexes for Energy and Medicine Applications

After decades of developments, electron microscopy has become a powerful and irreplaceable tool in understanding the ionic, electrical, mechanical, chemical, and other functional performances of next-generation polymers and soft complexes. The recent progress in electron microscopy of nanostructured polymers and soft assemblies is important for applications in many different fields, including, but not limited to, mesoporous and nanoporous materials, absorbents, membranes, solid electrolytes, battery electrodes, ion- and electron-transporting materials, organic semiconductors, soft robotics, optoelectronic devices, biomass, soft magnetic materials, and pharmaceutical drug design. For synthetic polymers and soft complexes, there are four main characteristics that differentiate them from their inorganic or biomacromolecular counterparts in electron microscopy studies: (1) lower contrast, (2) abundance of light elements, (3) polydispersity or nanomorphological variations, and (4) large changes induced by electron beams. Since 2011, the Center for Nanophase Materials Sciences (CNMS) at Oak Ridge National Laboratory has been working with numerous facility users on nanostructured polymer composites, block copolymers, polymer brushes, conjugated molecules, organic–inorganic hybrid nanomaterials, organic–inorganic interfaces, organic crystals, and other soft complexes. This review crystalizes some of the essential challenges, successes, failures, and techniques during the process in the past ten years. It also presents some outlooks and future expectations on the basis of these works at the intersection of electron microscopy, soft matter, and artificial intelligence. Machine learning is expected to automate and facilitate image processing and information extraction of polymer and soft hybrid nanostructures in aspects such as dose-controlled imaging and structure analysis.

36 MATERIALS SCIENCE↗

Rendezvous radar for the orbital maneuvering vehicle

The Rendezvous Radar Set (RRS) was designed at Motorola's Strategic Electronics Division in Chandler, Arizona, to be a key subsystem aboard NASA's Orbital Maneuvering Vehicle (OMV). The unmanned OMV, which was under development at TRW's Federal Systems Division in Redondo Beach, California, was designed to supplement the Shuttle's satellite delivery, retrieval, and maneuvering activities. The RRS was to be used to locate and then provide the OMV with vectoring information to the target satellite (or Shuttle or Space Station) to aid the OMV in making a minimum fuel consumption approach and rendezvous. The OMV development program was halted by NASA in 1990 just as parts were being ordered for the RRS engineering model. The paper presented describes the RRS design and then discusses new technologies, either under development or planned for development at Motorola, that can be applied to radar or alternative sensor solutions for the Automated Rendezvous and Capture problem.

Locke, John W.↗

NASA Tech Briefs, April 2004

Topics covered include: Analysis of SSEM Sensor Data Using BEAM; Hairlike Percutaneous Photochemical Sensors; Video Guidance Sensors Using Remotely Activated Targets; Simulating Remote Sensing Systems; EHW Approach to Temperature Compensation of Electronics; Polymorphic Electronic Circuits; Micro-Tubular Fuel Cells; Whispering-Gallery-Mode Tunable Narrow-Band-Pass Filter; PVM Wrapper; Simulation of Hyperspectral Images; Algorithm for Controlling a Centrifugal Compressor; Hybrid Inflatable Pressure Vessel; Double-Acting, Locking Carabiners; Position Sensor Integral with a Linear Actuator; Improved Electromagnetic Brake; Flow Straightener for a Rotating-Drum Liquid Separator; Sensory-Feedback Exoskeletal Arm Controller; Active Suppression of Instabilities in Engine Combustors; Fabrication of Robust, Flat, Thinned, UV-Imaging CCDs; Chemical Thinning Process for Fabricating UV-Imaging CCDs; Pseudoslit Spectrometer; Waste-Heat-Driven Cooling Using Complex Compound Sorbents; Improved Refractometer for Measuring Temperatures of Drops; Semiconductor Lasers Containing Quantum Wells in Junctions; Phytoplankton-Fluorescence-Lifetime Vertical Profiler; Hexagonal Pixels and Indexing Scheme for Binary Images; Finding Minimum-Power Broadcast Trees for Wireless Networks; and Automation of Design Engineering Processes.

Source record↗

High-Throughput Microstructural Characterization and Process Correlation Using Automated Electron Backscatter Diffraction

The need to optimize the processing conditions of additively manufactured (AM) metals and alloys has driven advances in throughput capabilities for material property measurements such as tensile strength or hardness. High-throughput (HT) characterization of AM metal microstructure has fallen significantly behind the pace of property measurements due to intrinsic bottlenecks associated with the artisan and labor-intensive preparation methods required to produce highly polished surfaces. This inequality in data throughput has led to a reliance on heuristics to connect process to structure or structure to properties for AM structural materials. In this study, we show a transformative approach to achieve laser powder bed fusion (LPBF) printing, HT preparation using dry electropolishing and HT electron backscatter diffraction (EBSD). This approach was used to construct a library of > 600 experimental EBSD sample sets spanning a diverse range of LPBF process conditions for AM Kovar. This vast library is far more expansive in parameter space than most state-of-the-art studies, yet it required only approximately 10 labor hours to acquire. Build geometries, surface preparation methods, and microscopy details, as well as the entire library of >600 EBSD data sets over the two sample design versions, have been shared with intent for the materials community to leverage the data and further advance the approach. Using this library, we investigated process–structure relationships and uncovered an unexpected, strong dependence of microstructure on location within the build, when varied, using otherwise identical laser parameters.

Characterization and Analytical Technique↗

Analysis of Eye-Tracking Data with Regards to the Complexity of Flight Deck Information Automation and Management - Inattentional Blindness, System State Awareness, and EFB Usage

In the constant drive to further the safety and efficiency of air travel, the complexity of avionics-related systems, and the procedures for interacting with these systems, appear to be on an ever-increasing trend. While this growing complexity often yields productive results with respect to system capabilities and flight efficiency, it can place a larger burden on pilots to manage increasing amounts of information and to understand intricate system designs. Evidence supporting this observation is becoming widespread, yet has been largely anecdotal or the result of subjective analysis. One way to gain more insight into this issue is through experimentation using more objective measures or indicators. This study utilizes and analyzes eye-tracking data obtained during a high-fidelity flight simulation study wherein many of the complexities of current flight decks, as well as those planned for the next generation air transportation system (NextGen), were emulated. The following paper presents the findings of this study with a focus on electronic flight bag (EFB) usage, system state awareness (SSA) and events involving suspected inattentional blindness (IB).

Dill, Evan T.↗

Software Development for Data Visualization and Analysis of PN-Diodes & MOSFET Devices

The U.S. Department of Energy has a broad mission to ensure the nation’s security by addressing ongoing environmental challenges, developing novel energy production technologies, and mitigating nuclear security concerns. These efforts benefit from developing more effective semiconductor materials and devices. The research discussed in this report aims to further the development of these new electronics by improving implementations of vertical device structures, which offer theoretically better performance compared to lateral structures. Specifically, it reviews the background and development of a new and easy-to-use program for data processing and analysis from experiments run on vertical gallium nitride power devices. Current vertical structures fall short in critical performance metrics, such as On-Resistance and Breakdown Voltage, due to poor management of the device’s electric field. Junction termination extensions, or JTEs, are a field management technique that increases a device’s resilience to expected failure modes by controlling its surface electric fields. Each JTE design requires significant experimental validation, consisting of hundreds of tested devices, each outputting an enormous set of data points. The new software includes multiple methods of filtering large sets of device testing data to identify and remove flawed devices, automate device analyses, and provide statistical breakdowns for four metrics used to define the effectiveness of the JTE and the current carrying capacity of the device. These results can then be related back to fabrication techniques and device design, and in the future, be combined with processing simulations to further improve our understanding of the JTE mechanisms.

97 MATHEMATICS AND COMPUTING↗

Analysis of Technology for Compact Coherent Lidar

In view of the recent advances in the area of solid state and semiconductor lasers has created new possibilities for the development of compact and reliable coherent lidars for a wide range of applications. These applications include: Automated Rendezvous and Capture, wind shear and clear air turbulence detection, aircraft wake vortex detection, and automobile collision avoidance. The work performed by the UAH personnel under this Delivery Order, concentrated on design and analyses of a compact coherent lidar system capable of measuring range and velocity of hard targets, and providing air mass velocity data. The following is the scope of this work. a. Investigate various laser sources and optical signal detection configurations in support of a compact and lightweight coherent laser radar to be developed for precision range and velocity measurements of hard and fuzzy targets. Through interaction with MSFC engineers, the most suitable laser source and signal detection technique that can provide a reliable compact and lightweight laser radar design will be selected. b. Analyze and specify the coherent laser radar system configuration and assist with its optical and electronic design efforts. Develop a system design including its optical layout design. Specify all optical components and provide the general requirements of the electronic subsystems including laser beam modulator and demodulator drivers, detector electronic interface, and the signal processor. c. Perform a thorough performance analysis to predict the system measurement range and accuracy. This analysis will utilize various coherent laser radar sensitivity formulations and different target models.

Amzajerdian, Farzin↗

Solar Array Verification Analysis Tool (SAVANT) Developed

Modeling solar cell performance for a specific radiation environment to obtain the end-of-life photovoltaic array performance has become both increasingly important and, with the rapid advent of new types of cell technology, more difficult. For large constellations of satellites, a few percent difference in the lifetime prediction can have an enormous economic impact. The tool described here automates the assessment of solar array on-orbit end-of-life performance and assists in the development and design of ground test protocols for different solar cell designs. Once established, these protocols can be used to calculate on-orbit end-of-life performance from ground test results. The Solar Array Verification Analysis Tool (SAVANT) utilizes the radiation environment from the Environment Work Bench (EWB) model developed by the NASA Lewis Research Center s Photovoltaic and Space Environmental Effects Branch in conjunction with Maxwell Technologies. It then modifies and combines this information with the displacement damage model proposed by Summers et al. (ref. 1) of the Naval Research Laboratory to determine solar cell performance during the course of a given mission. The resulting predictions can then be compared with flight data. The Environment WorkBench (ref. 2) uses the NASA AE8 (electron) and AP8 (proton) models of the radiation belts to calculate the trapped radiation flux. These fluxes are integrated over the defined spacecraft orbit for the duration of the mission to obtain the total omnidirectional fluence spectra. Components such as the solar cell coverglass, adhesive, and antireflective coatings can slow and attenuate the particle fluence reaching the solar cell. In SAVANT, a continuous slowing down approximation is used to model this effect.

Bailey, Sheila G.↗

Automated reaction kinetics and network exploration (Arkane): A statistical mechanics, thermodynamics, transition state theory, and master equation software

The open-source statistical mechanics software described here, Arkane–Automated Reaction Kinetics and Network Exploration–facilitates computations of thermodynamic properties of chemical species, high-pressure limit reaction rate coefficients, and pressure-dependent rate coefficient over multi-well molecular potential energy surfaces (PES) including the effects of collisional energy transfer on phenomenological kinetics. Arkane can use estimates to fill in information for molecules or reactions where quantum chemistry information is missing. The software solves the internal energy master equation for complex unimolecular reaction systems. Inputs to the software include converged electronic structure computations performed by the user using a variety of supported software packages (Gaussian, Molpro, Orca, TeraChem, Q-Chem, Psi4). The software outputs high-pressure limit rate coefficients and pressure-dependent phenomenological rate coefficients, as well as computed thermodynamic properties (enthalpy, entropy, and constant pressure heat capacity) with added energy corrections. Some of the key features of Arkane include treatment of 1D, 2D or ND hindered internal rotation modes, treatment of free internal rotation modes, quantum tunneling effect consideration, transition state theory (TST) and Rice-Ramsperger-Kassel-Marcus (RRKM) rate coefficient computations, master equation solution with four implemented methods, inverse-Laplace transform of high-pressure limit rate coefficients into the energy domain, energy corrections based on bond-additivity or isodesmic reactions, automated and efficient PES exploration, and PES sensitivity analysis. The present work describes the design of Arkane, how it should be used, and refers to the theory that it employs. Arkane is distributed via the RMG-Py software suite (https://github.com/ReactionMechanismGenerator/RMG-Py).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Key Decision Record Creation and Approval Module

Retaining good key decision records is critical to ensuring the success of a project or operation. Having adequately documented decisions with supporting documents and rationale can greatly reduce the amount of rework or reinvention over a project's, vehicle's, or facility's lifecycle. Stennis Space Center developed and uses a software tool that automates the Key Decision Record (KDR) process for its engineering and test projects. It provides the ability for a user to log key decisions that are made during the course of a project. By customizing Parametric Technology Corporation's (PTC) Windchill product, the team was able to log all information about a decision, and electronically route that information for approval. Customizing the Windchill product allowed the team to directly connect these decisions to the engineering data that it might affect and notify data owners of the decision. The user interface was created in JSP and Javascript, within the OOTB (Out of the Box) Windchill product, allowing users to create KDRs. Not only does this interface allow users to create and track KDRs, but it also plugs directly into the OOTB ability to associate these decision records with other relevant engineering data such as drawings, designs, models, requirements, or specifications

Hebert, Barrt↗

Deep Neural Network Algorithm for CMC Microstructure Characterization and Variability Quantification

Microstructure characterization and variability quantification are crucial for understanding ceramic matrix composites (CMCs) mechanical behavior and deformation mechanisms across length scales. Traditionally, analyses of the micrographs obtained from microscopy are labor-intensive. However, with the vast improvement in computer vision (CV) and deep learning (DL), an automated algorithm can be designed to extract essential microstructure variability from micrographs which can then be used to construct a statistically representative volume element (SRVE). The DL-based algorithm spans the taxonomy of microstructure analyses, including semantic segmentation of microstructure constituents, secondary phases, matrix/fiber interface, and defects, and quantifying the microstructure variability in terms of probability distributions. In this work, C/SiNC and SiC/SiNC CMCs microstructures are semantically segmented through a deep convolutional neural network, followed by variability quantification through the implementation of a fully connected regression layer, hence forming a deep regression network. The deep regression network operates in a feedforward regime, in which the neuron output signal traverses through the network in a unidirectional manner. The weight tensor associated with each layer is updated through a backpropagation stochastic gradient descent approach. The input gray-scale image obtained through in-house scanning electron microscope and confocal microscope micrographs is augmented through affine transformations to increase the training set size, which is then processed through four strided convolutional layers. This compresses the image resolution by half at each layer while increasing the image depth by applying different filters (image encoding). The class activation maps (CAMs) corresponding to the applied filters highlight the key architectural features and assist with the semantic segmentation of the microstructure.

Hamza, Mohamed H.↗

Design, Fabrication, and Testing of Emissive Probes to Determine the Plasma Potential of the Plumes of Various Electric Thrusters

A significant problem in the use of electric thrusters in spacecraft is the formation of low-energy ions in the thruster plume. Low-energy ions are formed in the plume via random collisions between high-velocity ions ejected from the thruster and slow-moving neutral atoms of propellant effusing from the engine. The sputtering of spacecraft materials due to interactions with low-energy ions may result in erosion or contamination of the spacecraft. The trajectory of these ions is determined primarily by the plasma potential of the plume. Thus, accurate characterization of the plasma potential is essential to predicting low-energy ion contamination. Emissive probes were utilized to determine the plasma potential. When the ion and electron currents to the probe are balanced, the potential of such probes float to the plasma potential. Two emissive probes were fabricated; one utilizing a DC power supply, another utilizing a rectified AC power source. Labview programs were written to coordinate and automate probe motion in the thruster plume. Employing handshaking interaction, these motion programs were synchronized to various data acquisition programs to ensure precision and accuracy of the measurements. Comparing these experimental values to values from theoretical models will allow for a more accurate prediction of low-energy ion interaction.

Chen, Erinna M.↗

SSC Engineering Analysis

A package for the automation of the Engineering Analysis (EA) process at the Stennis Space Center has been customized. It provides the ability to assign and track analysis tasks electronically, and electronically route a task for approval. It now provides a mechanism to keep these analyses under configuration management. It also allows the analysis to be stored and linked to the engineering data that is needed to perform the analysis (drawings, etc.). PTC s (Parametric Technology Corp o ration) Windchill product was customized to allow the EA to be created, routed, and maintained under configuration management. Using Infoengine Tasks, JSP (JavaServer Pages), Javascript, a user interface was created within the Windchill product that allows users to create EAs. Not only does this interface allow users to create and track EAs, but it plugs directly into the out-ofthe- box ability to associate these analyses with other relevant engineering data such as drawings. Also, using the Windchill workflow tool, the Design and Data Management System (DDMS) team created an electronic routing process based on the manual/informal approval process. The team also added the ability for users to notify and track notifications to individuals about the EA. Prior to the Engineering Analysis creation, there was no electronic way of creating and tracking these analyses. There was also a feature that was added that would allow users to track/log e-mail notifications of the EA.

Ryan, Harry↗

Review on Preprocessing Strategies, Deactivation, Thermal Safety, and Future Perspectives in Lithium-Ion Battery Recycling

The rapid growth in the use of lithium-ion batteries (LIBs) in electric vehicles, consumer electronics, and renewable energy storage has made effective end-of-life management essential. Recycling LIBs is critical not only for resource recovery and environmental protection but also for ensuring safety and economic viability. This review focuses on the preprocessing technologies that precede typical recovery processes, including disassembly, sorting, discharging, electrolyte removal, dismantling, thermal treatment, separation, and flotation. These steps play a foundational role in determining the efficiency, safety, and environmental impact of LIB recycling. LIBs pose substantial fire and explosion risks due to residual charge, flammable electrolytes, and reactive materials. The conditions and successive progression of the exothermic reactions which lead to thermal runaway has been discussed. It also explores secure deactivation techniques such as external circuit discharge, saline immersion, and thermomechanical methods, alongside fire prevention strategies including the use of flame retardants, elimination of oxidants, and reduction of heat generation and accumulation. Challenges and future directions are outlined, highlighting the need for standardized designs, automation, and safer, more sustainable recycling infrastructure. Furthermore, this review is distinguished by its focused analysis of preprocessing and deactivation steps, with particular attention to the thermal safety engineering aspects of LIB recycling.

Battery deactivation↗

Space Station Furnace Facility Core. Requirements definition and conceptual design study. Volume 2: Technical report. Appendix 6: Technical summary reports

The Space Station Furnace Facility (SSFF) is a modular facility for materials research in the microgravity environment of the Space Station Freedom (SSF). The SSFF is designed for crystal growth and solidification research in the fields of electronic and photonic materials, metals and alloys, and glasses and ceramics and will allow for experimental determination of the role of gravitational forces in the solidification process. The facility will provide a capability for basic scientific research and will evaluate the commercial viability of low-gravity processing of selected technologically important materials. The facility is designed to support a complement of furnace modules as outlined in the Science Capabilities Requirements Document (SCRD). The SSFF is a three rack facility that provides the functions, interfaces, and equipment necessary for the processing of the furnaces and consists of two main parts: the SSFF Core Rack and the two Experiment Racks. The facility is designed to accommodate two experimenter-provided furnace modules housed within the two experiment racks, and is designed to operate these two furnace modules simultaneously. The SCRD specifies a wide range of furnace requirements and serves as the basis for the SSFF conceptual design. SSFF will support automated processing during the man-tended operations and is also designed for crew interface during the permanently manned configuration. The facility is modular in design and facilitates changes as required, so the SSFF is adept to modifications, maintenance, reconfiguration, and technology evolution.

Source record↗

Cryogenic probe station for use in automated microwave and noise figure measurements

A cryogenic measurement system capable of performing on-wafer RF testing of semiconductor devices and circuits has been developed. This 'CryoProbe Station' can wafer-probe devices and circuits at cryogenic temperatures, thus eliminating the need for wire bonds. The system operates under vacuum created by a sorption pump. It uses an open cycle cooling system that can be cooled with either liquid nitrogen or liquid helium. Presently, it can reach temperatures, as low as 80 K and 37 K for each of the coolants, respectively. The temperature can be raised using a heater and it is stabilized to within 0.2 K by use of a temperature controller. The CryoProbe Station features a 1 by 2 inch stage that can hold large circuits and calibration standards simultaneously. The system is used with a Hewlett Packard 8510C Automatic Network Analyzer (ANA) to obtain S-parameter data over the frequency range 0.045-26.5 GHz. S-parameter data on HEMT (high electron mobility transistors) devices has been obtained with this station. With the use of DEEMBED software from NIST, detailed transmission line studies have been performed. Although the CryoProbe Station is designed for frequencies up to 26.5 GHz, useful transmission line data has been obtained for frequencies as high as 40 GHz. The CryoProbe station has also been used with the ATN noise figure measurement system to perform automatic, temperature dependent noise figure measurements.

Taub, Susan R.↗