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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

A Closer Look at Automation Behavior During a Human-in-the-Loop Simulation

A 2012 Human-In-The-Loop air traffic control simulation investigated a gradual paradigm-shift in the allocation of functions between operators and automation. Air traffic controllers staffed five adjacent high-altitude en route sectors, and during the course of a two-week experiment, worked traffic under four different function allocation concepts aligned with increasingly mature NextGen operational environments. These NextGen time-frames ranged from near current-day operations to nearly fully-automated control, in which the ground systems automation was responsible for detecting conflicts, issuing strategic and tactical resolutions, and alerting controllers to exceptional circumstances. This paper continues the investigations reported in previous publications. Analyses of data surrounding the conflict-resolution task serve as the context in which we investigate the interactions between controllers and the automation.

Human-Automation Interaction↗
NASA NTRS1993

Mission Operations and Command Assurance: Automating an Operations TQM Task

A long-term program is in progress at JPL to reduce cost and risk of mission operations through defect prevention and error management. A major element of this program, Mission Operations and Command Assurance (MO&QA), provides a system level function on flight projects to instill quality in mission operations. MO&CA embodies the Total Quality Management (TQM) principle of Continuous Process Inprovement (CPI) and uses CPI in applying automation to mission operations to reduce risk and costs. MO&CA has led efforts to apply and has implemented automation in areas that impact the daily flight project environment including Incident Surprise Anomoly tracking and reporting; command data verification, tracking, and reporting; and command support data usage. MO&CA's future work in automation will take into account that future missions systems must be designed to avoid increasing error through the introduction of automation, while adapting to the demands of smaller flight teams.

automation↗
NASA NTRS2023

Leveraging Automated Fiber Placement Computer Aided Process Planning Framework for Defect Validation and Dynamic Layup Strategies

Process planning represents an essential stage of the Automated Fiber Placement (AFP) workflow. It develops useful and efficient machine processes based upon the working material, composite design, and manufacturing resources. The current state of process planning requires a high degree of interaction from the process planner and could greatly benefit from increased automation. Therefore, a list of key steps and functions are created to identify the more difficult and time-consuming phases of process planning. Additionally, a set of metrics must exist by which to evaluate the effectiveness of the manufactured laminate from the machine code created during the Process Planning stage. Layup strategies, in addition to dog ears, stagger shifts, steering constraints, and starting points, represented the group of functions labeled as process optimization and ranked the highest in terms of priority for automation. The laminates resulting from the selected parameters are evaluated through the occurrences of principal defect metrics such as fiber gaps, overlaps, angle deviation and steering violations. This document presents an automated software solution to the layup strategy and starting point selection phase of process planning. A series of ply scenarios are generated with variations of these ply parameters and evaluated according to a set of metrics entered by the Process Planner. These metrics are generated through use of the Analytical Hierarchy Process (AHP), where relative importance between each of the fiber features are defined. The ply scenarios are selected which reduce the overall fiber feature scores based on the defects the Process Planner wishes to minimize.

HiCAM↗
NASA NTRS2024

Integration of Automated Systems Test Campaign NC-IAS

NASA’s 2022 strategic plan included the goal to catalyze economic growth and drive innovation in the aviation industry, and to address challenges in air transportation and airspace management within the National Airspace System (NAS). The Aeronautics Research Mission Directorate (ARMD) specifically was tasked with leading aviation innovation to enable safe and sustainable air transportation through revolutionary vehicle advances and efficient flight operations. As a part of meeting these objectives and advancing air mobility concepts, NASA initiated the National Campaign (NC) in the Advanced Air Mobility (AAM) Project within the Airspace Operations and Safety Program (AOSP). The NC was designed to support operational demonstrations with industry as well as the research and development needed to support NASA-led research flight demonstrations. Within NC, the Integration of Automated Systems (IAS), an NC activity, tested and evaluated flight deck automation and airspace operations management functions needed to enable Urban Air Mobility (UAM) operations. This was accomplished through a partnership with Sikorsky Aircraft (specifically Sikorsky Innovations), a Lockheed Martin company, and DARPA (Defense Advanced Research Projects Agency), by leveraging two automation-enabled helicopters equipped with unique capabilities that enabled NASA to develop and test two-ship conflict encounters to demonstrate flight path management and hazard avoidance technologies. The enabler in this testing was NASA-developed “Middleware” (MW) software (also known as Expandable Variable Autonomy Architecture, or EVAA), which among other things allowed multiple algorithms to be incorporated into one software build that was hosted on the dissimilar-type Sikorsky helicopters. The IAS test campaign period of performance was from March 2022 through October 2023 and was structured as a phased, or spiral, approach that ultimately led to the first-ever demonstration of two-ship UAM/AAM operations designed to safely choreograph specific conflict encounters and mission scenarios to test the research algorithms for strategic and tactical aircraft deconfliction. Lessons learned are included in the body of the report. Data collected will be used to inform FAA and industry standards groups on the increasingly automated systems needed for future AAM operations. The test encounters developed for these flight tests were proven to be highly predictable, repeatable, and safely exercised flight path planning and Detect and Avoid (DAA) algorithms. These same test encounters should be leveraged by future flight test campaigns to verify that operational safety is not compromised as the AAM architecture matures. Next steps include repeating similar encounters using unmanned aircraft carrying DAA sensors in the National Airspace.

AAM↗
DOE OSTI2022

Automated Mobility Platforms (AMPs) for Versatile, Energy Efficient, Facility and District Scale Transport

The Automated Mobility Platforms (AMPs) concept is envisioned as an on-demand network of automated lightweight electric vehicles serving mobility needs in a large facility or district-scale setting. Supplanting the function of legacy automated people mover systems, AMPs is scalable to meet the needs of moving people in large interior spaces with destinations that are too distant for walking and in which larger motor vehicles would be unfeasible or undesirable. The AMPs system is designed for automated management and operation, extending to how and where the vehicles are sent to serve mobility needs, as organized through a supervisory management system. AMPs vehicles are requested by users via smartphone app or buttons located on interactive infrastructure elements. AMPs vehicles function similarly to elevators, though in the horizontal plane, wherein users summon vehicles, and are moved point-to-point, with user requested destinations set through intuitive interfaces. The concept targets extensibility, manageability, and performance improvements over legacy technologies, with accessibility and safety features integrally designed into the system.

ADA supportive modes↗
DOE OSTI2023

Maximizing Efficiency and Quality: Leveraging Automated Testing for Laboratory Commissioning

The traditional commissioning process for a building often implements sampling rates to select equipment for functional acceptance testing when large quantities of equipment are present. While this approach is generally effective in identifying wide-spread issues, it has several key shortfalls. (1) It provides a one-time validation of equipment operation in which the standard documentation is a simple checklist of pass/fail questions. (2) It fails to evaluate equipment not included in the sample rate selection. During the construction and commissioning process of the new Research and Innovation Laboratory (RAIL) in Golden, CO, the National Renewable Energy Laboratory team engaged Group14 Engineering to implement a Connected Commissioning process using fault detection and diagnostic software for automated functional acceptance testing. The goal of this presentation will be to highlight the advantages offered by automated functional testing in this critical laboratory setting. These are primarily (1) sampling 100% of BAS-connected equipment during functional testing, (2) testing results backed by data beyond the traditional pass/fail checklist, and (3) an automated test process that can be regularly executed by the building management team for ongoing commissioning throughout the life of the building. The presentation will also cover technical challenges associated with connected commissioning and the important conversations with the key stakeholders that need to occur well before functional acceptance testing in order to successfully implement the automated testing processes.

automated testing↗
DOE OSTI2024

Maximizing Efficiency and Quality: Leveraging Automated Testing for Laboratory Commissioning

The traditional commissioning process uses sampling to select equipment for functional acceptance testing when large quantities of equipment are present. Although this approach is generally effective in identifying wide-spread issues, it has several shortcomings: it fails to evaluate equipment not included in the sample, provides only a one-time validation of equipment operation, and the standard documentation is a simple checklist of pass/fail questions. During the construction and commissioning process of the new Research and Innovation Laboratory (RAIL) in Golden, CO, the National Renewable Energy Laboratory team engaged Group14 Engineering to implement a Connected Commissioning process using fault detection and diagnostic software for automated functional acceptance testing. This presentation highlights the advantages offered by automated functional testing in this critical laboratory setting: (1) sampling 100% of BAS-connected equipment during functional testing, (2) testing results backed by data beyond the traditional pass/fail checklist, and (3) an automated test process that can be regularly executed by the building management team for ongoing commissioning throughout the life of the building. The presentation will also cover technical challenges associated with Connected Commissioning and the important conversations with key stakeholders that need to occur well before functional acceptance testing in order to successfully implement the automated testing processes.

automated testing↗
DOE OSTI2023

Challenges and Strategies for Testing Automation Practices at Sandia National Laboratories

Sandia National Laboratories is a premier United States national security laboratory which develops science-based technologies in areas such as nuclear deterrence, energy production, and climate change. Computing plays a key role in its diverse missions, and within that environment, Research Software Engineers (RSEs) and other scientific software developers utilize testing automation to ensure quality and maintainability of their work. We conducted a Participatory Action Research study to explore the challenges and strategies for testing automation through the lens of academic literature. Through the experiences collected and comparison with open literature, we identify these challenges in testing automation and then present strategies for mitigation grounded in evidence-based practice and experience reports that other, similar institutions can assess for their automation needs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The B737 MAX 8 Accidents as Operational Experiences With Automation Transparency

Automation transparency has come into prominence in the human-machine systems literature, with researchers offering definitions, models, design frameworks, and empirical findings. However, missing from the literature are reflections on the actual operational experiences of human crews interacting with intelligent automation conceived from multiple transparency perspectives. The Boeing 737 MAX 8 accidents present a tragic case of a catastrophic failure of automation transparency. We explore this case with an emphasis on extracting design and regulatory insights for the nuclear power and other safety-critical domains.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Automated Ride Hailing - Status, Projections, and Critical Safety Review

Automated ride-hailing services, commonly known as 'robo-taxis' are beginning to proliferate and scale. Currently they are available in four major US cities with another 10 cities planning their implementation in the near future. In the US, automated ride-hailing services are dominated by a single provider, with announcements from several competitors of service offerings by end of calendar year 2025. Internationally, only three companies are currently in commercial operations, with many more planned. The scaling of robo-taxi services appears to be the leading application of automated vehicles (AVs), and provides evidence of their anticipated safety in comparison to conventional vehicles. This presentation will provide an overview of the status of deployments of fully operational AVs in ride-hailing services, projections of the number of trips, vehicles, and vehicle miles traveled for the immediate future, and a critical review of the safety data that has been reported, both in the US as well as internationally.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

PeakQC: A Software Tool for Omics-Agnostic Automated Quality Control of Mass Spectrometry Data

Mass spectrometry is broadly employed to study complex molecular mechanisms in various biological and environmental fields, enabling 'omics' research such as proteomics, metabolomics, and lipidomics. As study cohorts grow larger and more complex with dozens to hundreds of samples, the need for robust quality control (QC) measures through automated software tools becomes paramount to ensure the integrity, high quality, and validity of scientific conclusions from downstream analyses and minimize the waste of resources. Since existing QC tools are mostly dedicated to proteomics, automated solutions supporting metabolomics are needed. To address this need, we developed the software PeakQC, a tool for automated QC of MS data that is independent of omics molecular types (i.e., omics-agnostic). It allows automated extraction and inspection of peak metrics of precursor ions (e.g., errors in mass, retention time, arrival time) and supports various instrumentations and acquisition types, from infusion experiments or using liquid chromatography and/or ion mobility spectrometry front-end separations and with/without fragmentation spectra from data-dependent or independent acquisition analyses. Diagnostic plots for fragmentation spectra are also generated. Here, in this paper, we describe and illustrate PeakQC’s functionalities using different representative data sets, demonstrating its utility as a valuable tool for enhancing the quality and reliability of omics mass spectrometry analyses.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Development and experimental study of an automated laser-foil-printing additive manufacturing system

Purpose This paper aims to present the development and experimental study of a fully automated system using a novel laser additive manufacturing technology called laser foil printing (LFP), to fabricate metal parts layer by layer. The mechanical properties of parts fabricated with this novel system are compared with those of comparable methodologies to emphasize the suitability of this process. Design/methodology/approach Test specimens and parts with different geometries were fabricated from 304L stainless steel foil using an automated LFP system. The dimensions of the fabricated parts were measured, and the mechanical properties of the test specimens were characterized in terms of mechanical strength and elongation. Findings The properties of parts fabricated with the automated LFP system were compared with those of parts fabricated with the powder bed fusion additive manufacturing methods. The mechanical strength is higher than those of parts fabricated by the laser powder bed fusion and directed energy deposition technologies. Originality/value To the best knowledge of authors, this is the first time a fully automated LFP system has been developed and the properties of its fabricated parts were compared with other additive manufacturing methods for evaluation.

Engineering↗
DOE OSTI2024

Automated Calibration of Parallel and Distributed Computing Simulators: A Case Study

Many parallel and distributed computing research results are obtained in simulation, using simulators that mimic real-world executions on some target system. Each such simulator is configured by picking values for parameters that define the behavior of the underlying simulation models it implements. The main concern for a simulator is accuracy: simulated behaviors should be as close as possible to those observed in the real-world target system. This requires that values for each of the simulator's parameters be carefully picked, or “calibrated,” based on ground-truth real-world executions. Examining the current state of the art shows that simulator calibration, at least in the field of parallel and distributed computing, is often undocumented (and thus perhaps often not performed) and, when documented, is described as a labor-intensive, manual process. In this work we evaluate the benefit of automating simulation calibration using simple algorithms. Specifically, we use a real-world case study from the field of High Energy Physics and compare automated calibration to calibration performed by a domain scientist. Our main finding is that automated calibration is on par with or significantly outperforms the calibration performed by the domain scientist. Furthermore, automated calibration makes it straightforward to operate desirable tradeoffs between simulation accuracy and simulation speed.

Mc donald, Jesse↗
DOE OSTI2022

VAC: A Software Approach to Resilient SCADA Automation

To better secure critical infrastructure, especially power systems, this paper introduces a virtual SCADA automation controller. The automation controller is a gateway into a power subsystem, making it a valuable target for cyber-attacks that could cut it off from the control center and cause a loss of view and control. To prevent this, the Virtual Automation Controller (VAC) is a backup device that mirrors the capabilities of the physical controller. It can communicate via Modbus and DNP3 and is containerized so it can be deployed on a variety of platforms. Furthermore, it utilizes software-defined networking to quickly disconnect a failed automation controller and preserve its state for forensics. The VAC gives system operators time to replace the failed controller and prevents dangerous and costly damage to power systems. The VAC is compared against the SEL 3505-3 RTAC and shown to have the necessary features to act as a failover controller.

Johnson, Jordan↗
DOE OSTI2022

An automated workflow that generates atom mappings for large‐scale metabolic models and its application to Arabidopsis thaliana

SUMMARY Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determines cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA), which relies on the patterns of isotope labeling of metabolites in the network. The application of MFA also requires a stoichiometric model with atom mappings that are currently not available for the majority of large‐scale metabolic network models, particularly of plants. While automated approaches such as the Reaction Decoder Toolkit (RDT) can produce atom mappings for individual reactions, tracing the flow of individual atoms of the entire reactions across a metabolic model remains challenging. Here we establish an automated workflow to obtain reliable atom mappings for large‐scale metabolic models by refining the outcome of RDT, and apply the workflow to metabolic models of Arabidopsis thaliana . We demonstrate the accuracy of RDT through a comparative analysis with atom mappings from a large database of biochemical reactions, MetaCyc. We further show the utility of our automated workflow by simulating 15 N isotope enrichment and identifying nitrogen (N)‐containing metabolites which show enrichment patterns that are informative for flux estimation in future 15 N‐MFA studies of A. thaliana . The automated workflow established in this study can be readily expanded to other species for which metabolic models have been established and the resulting atom mappings will facilitate MFA and graph‐theoretic structural analyses with large‐scale metabolic networks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Design of a Novel Information System for Semi-Automated Management of Cybersecurity in Industrial Control Systems

There is an urgent need in many critical infrastructure sectors, including the energy sector, for attaining detailed insights into cybersecurity features and compliance with cybersecurity requirements related to their Operational Technology (OT) deployments. Frequent feature changes of OT devices interfere with this need, posing a great risk to customers. One effective way to address this challenge is via a semi-automated cyber-physical security assurance approach, which enables verification and validation of the OT device cybersecurity claims against actual capabilities, both pre- and post-deployment. To realize this approach, this paper presents new methodology and algorithms to automatically identify cybersecurity-related claims expressed in natural language form in ICS device documents. Here, we developed an identification process that employs natural language processing (NLP) techniques with the goal of semi-automated vetting of detected claims against their device implementation. We also present our novel NLP components for verifying feature claims against relevant cybersecurity requirements. The verification pipeline includes components such as automated vendor identification, device document curation, feature claim identification utilizing sentiment analysis for conflict resolution, and reporting of features that are claimed to be supported or indicated as unsupported. Our novel matching engine represents the first automated information system available in the cybersecurity domain that directly aids the generation of ICS compliance reports.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Trace Elemental Analysis of Bulk Thorium Using an Automated Separation–Inductively Coupled Plasma Optical Emission Spectroscopy Methodology

Presented here is a novel automated method for determining the trace element composition of bulk thorium by inductively coupled plasma–optical emission spectroscopy (ICP-OES). ICP-OES is a universal approach for measuring the trace elemental impurities present in actinide-rich materials; however, due to the emission rich spectrum of the actinide, a separation from the trace elements is warranted for spectrochemical analysis. Here, AG MP-1 ion exchange resin was utilized for retention of the Th matrix, while allowing the trace element impurities to be separated prior to subsequent analysis using ICP-OES. After demonstrating the separation on traditional gravity-driven columns, the methodology was transitioned to an automated platform for comparison. This automated platform utilizes syringe-driven sample and solvent flow and can collect the trace element and thorium fractions in separate locations. Finally, while reducing the sample size (500 µL, 1.5 mg of Th), maintaining the overall separation efficiency (recoveries >95%), and illustrating the sample throughput ability (n = 10+), this automated methodology could be readily adopted to nuclear facilities in which the determination of trace elemental impurities in Th samples is warranted.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Vision-Guided Automation and Assistance

Robotic automation and assistance is an excellent way to increase efficiency and safety when working in a potentially hazardous workspace. However, many traditional automation approaches rely on the precise placement of items to be manipulated. The scope of such automated tasks is also limited to the manipulation of one type of object since there is no way to distinguish between different objects. The addition of a vision pipeline, where robot vision is used to localize and recognize objects, can allow the robot to perform more complex tasks in a variable workspace. In my vision pipeline, a depth camera is used to generate a 3D point cloud of the workspace. Objects to be manipulated are isolated in the point cloud by filtering out shared surfaces and using Euclidean cluster extraction to group clusters of points. The locations of the objects are then estimated from the point cloud of the isolated objects. The localization of objects with robot vision allows for variable workspaces, reducing the overhead associated with requiring all objects to be precisely placed in the workspace. For object recognition, deep learning is used to train a neural network that classifies objects from the raw point clouds. More complex tasks that require multiple objects to be manipulated differently can be achieved through the vision pipeline. Through its ability to visualize the workspace, robot vision greatly improves efficiency and safety of automated and assistive tasks.

42 ENGINEERING↗