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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 667 records · Page 37

All sources NASA NTRS DOE OSTI

NASA NTRS1997

RIACS

Topics considered include: high-performance computing; cognitive and perceptual prostheses (computational aids designed to leverage human abilities); autonomous systems. Also included: development of a 3D unstructured grid code based on a finite volume formulation and applied to the Navier-stokes equations; Cartesian grid methods for complex geometry; multigrid methods for solving elliptic problems on unstructured grids; algebraic non-overlapping domain decomposition methods for compressible fluid flow problems on unstructured meshes; numerical methods for the compressible navier-stokes equations with application to aerodynamic flows; research in aerodynamic shape optimization; S-HARP: a parallel dynamic spectral partitioner; numerical schemes for the Hamilton-Jacobi and level set equations on triangulated domains; application of high-order shock capturing schemes to direct simulation of turbulence; multicast technology; network testbeds; supercomputer consolidation project.

Oliger, Joseph↗

NASA NTRS2024

Enhancing Metal Additive Manufacturing Training with the Advanced Vision Language Model: A Pathway to Immersive Augmented Reality Training for Non-Experts

This paper introduces an innovative training system for the Renishaw AM400 metal printer, leveraging the synergy of the advanced Vision Language Model (VLM) with Augmented Reality (AR) within the Digital Twins (DT) framework. Aimed at overcoming the limitations of conventional training methods in metal additive manufacturing (AM), our system integrates AR to provide an immersive learning environment, enhancing the real-world experience with interactive digital overlays. The core of the system lies in its use of VLM, which, pre-trained on diverse datasets, excels in processing multi-modal data, thereby offering nuanced and contextually relevant guidance for trainees. Key experiments demonstrate the system’s effectiveness, particularly highlighting the usage of VLM as an Artificial Intelligence (AI) agent to integrate external tools like YOLO-v7 for valve state classification and CRAFT for control panel text recognition. This approach significantly improves recognition accuracy, operational understanding, and human–machine interaction, especially for non-expert users, making complex metal AM operations more accessible. The research not only showcases the potential of AR and VLM in industrial training but also sets a new standard for smart manufacturing practices, indicating broader applications in various industrial domains.

Metal additive manufacturing↗

DOE OSTI2023

Copper Reductase Activity and Free Radical Chemistry by Cataract-Associated Human Lens γ-Crystallins

Cataracts are caused by high-molecular weight aggregates of human eye lens proteins that scatter light, causing lens opacity. Metal ions have emerged as important potential players in the etiology of cataract disease, as human lens γ-crystallins are susceptible to metal-induced aggregation. Here, the interaction of Cu 2+ ions with γD-, γC-, and γS- crystallins, the three most abundant γ-crystallins in the lens, has been evaluated. Cu 2+ ions induced non-amyloid aggregation in all three proteins. Solution turbidimetry, SDS-PAGE, circular dichroism and differential scanning calorimetry showed that the mechanism for Cu-induced aggregation involves: i) loss of beta-sheet structure in the N-terminal domain; ii) decreased thermal and kinetic stability; iii) formation of metal-bridged species; and iv) formation of disulfide-bridged dimers. Electron paramagnetic resonance (EPR) revealed two distinct Cu 2+ binding sites in each protein. Spin quantitation demonstrated reduction of γ-crystallin-bound Cu 2+ ions to Cu + under aerobic conditions, while X-ray absorption spectroscopy (XAS) confirmed the presence of linear or trigonal Cu + binding sites in γ-crystallins. Our EPR and XAS studies revealed that γ-crystallins’ Cu 2+ reductase activity yields a protein-based free radical that is likely a Tyr-based species in human γD-crystallin. This unique free radical chemistry carried out by distinct redox-active Cu sites in human lens γ-crystallins likely contributes to the mechanism of copper-induced aggregation. Finally, in the context of an aging human lens, γ-crystallins could be acting, not only as structural proteins, but also as key players for metal and redox homeostasis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Disruption of Z-Disc Function Promotes Mechanical Dysfunction in Human Myocardium: Evidence for a Dual Myofilament Modulatory Role by Alpha-Actinin 2

The ACTN2 gene encodes α-actinin 2, located in the Z-disc of the sarcomeres in striated muscle. In this study, we sought to investigate the effects of an ACTN2 missense variant of unknown significance (p.A868T) on cardiac muscle structure and function. Left ventricular free wall samples were obtained at the time of cardiac transplantation from a heart failure patient with the ACTN2 A868T heterozygous variant. This variant is in the EF 3–4 domain known to interact with titin and α-actinin. At the ultrastructural level, ACTN2 A868T cardiac samples presented small structural changes in cardiomyocytes when compared to healthy donor samples. However, contractile mechanics of permeabilized ACTN2 A868T variant cardiac tissue displayed higher myofilament Ca 2+ sensitivity of isometric force, reduced sinusoidal stiffness, and faster rates of tension redevelopment at all Ca 2+ levels. Small-angle X-ray diffraction indicated increased separation between thick and thin filaments, possibly contributing to changes in muscle kinetics. Molecular dynamics simulations indicated that while the mutation does not significantly impact the structure of α-actinin on its own, it likely alters the conformation associated with titin binding. Our results can be explained by two Z-disc mediated communication pathways: one pathway that involves α-actinin’s interaction with actin, affecting thin filament regulation, and the other pathway that involves α-actinin’s interaction with titin, affecting thick filament activation. This work establishes the role of α-actinin 2 in modulating cross-bridge kinetics and force development in the human myocardium as well as how it can be involved in the development of cardiac disease.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Potential pathogenicity determinants identified from structural proteomics of SARS-CoV and SARS-CoV-2

Despite SARS-CoV and SARS-CoV-2 being equipped with highly similar protein arsenals, the corresponding zoonoses have spread among humans at extremely different rates. The specific characteristics of these viruses that led to such distinct outcomes remain unclear. Here, we apply proteome-wide comparative structural analysis aiming to identify the unique molecular elements in the SARS-CoV-2 proteome that may explain the differing consequences. By combining protein modeling and molecular dynamics simulations, we suggest non-conservative substitutions in functional regions of the spike glycoprotein (S), nsp1, and nsp3 that are contributing to differences in virulence. Particularly, we explain why the substitutions at the receptor-binding domain of S affect the structure-dynamics behavior in complexes with putative host receptors. Conservation of functional protein regions within the two taxa is also noteworthy. We suggest that the highly conserved main protease, nsp5, of SARS-CoV and SARS-CoV-2 is part of their mechanism of circumventing the host interferon antiviral response. Overall, most substitutions occur on the protein surfaces and may be modulating their antigenic properties and interactions with other macromolecules. Our results imply that the striking difference in the pervasiveness of SARS-CoV-2 and SARS-CoV among humans seems to significantly derive from molecular features that modulate the efficiency of viral particles in entering the host cells and blocking the host immune response.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Structural analysis of carbohydrate binding by the macrophage mannose receptor CD206

The human mannose receptor expressed on macrophages and hepatic endothelial cells scavenges released lysosomal enzymes, glycopeptide fragments of collagen, and pathogenic microorganisms and thus reduces damage following tissue injury. The receptor binds mannose, fucose, or N-acetylglucosamine (GlcNAc) residues on these targets. C-type carbohydrate recognition domain 4 (CRD4) of the receptor contains the site for Ca 2+ -dependent interaction with sugars. To investigate the details of CRD4 binding, glycan array screening was used to identify oligosaccharide ligands. The strongest signals were for glycans that contain either Manα1-2Man constituents or fucosein various linkages. The mechanisms of binding to monosaccharides and oligosaccharide substructures present in many of these ligands were examined in multiple crystal structures of CRD4. Binding of mannose residues to CRD4 results primarily from interaction of the equatorial 3- and 4-OH groups with a conserved principal Ca 2+ common to almost all sugar-binding C-type CRDs. In the Manα1-2Man complex, supplementary interactions with the reducing mannose residue explain the enhanced affinity for this disaccharide. Bound GlcNAc also interacts with the principal Ca 2+ through equatorial 3- and 4-OH groups, whereas fucose residues can bind in several orientations, through either the 2- and 3-OH groups or the 3- and 4-OH groups. Secondary contacts with additional sugars in fucose-containing oligosaccharides, such as the Lewis-a trisaccharide, provide enhanced affinity for these glycans. These results explain many of the biologically important interactions of the mannose receptor with both mammalian glycoproteins and microbes such as yeast and suggest additional classes of ligands that have not been previously identified

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Federated benchmarking of medical artificial intelligence with MedPerf

Medical artificial intelligence (AI) has tremendous potential to advance healthcare by supporting and contributing to the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving both healthcare provider and patient experience. Unlocking this potential requires systematic, quantitative evaluation of the performance of medical AI models on large-scale, heterogeneous data capturing diverse patient populations. Here, to meet this need, we introduce MedPerf, an open platform for benchmarking AI models in the medical domain. MedPerf focuses on enabling federated evaluation of AI models, by securely distributing them to different facilities, such as healthcare organizations. This process of bringing the model to the data empowers each facility to assess and verify the performance of AI models in an efficient and human-supervised process, while prioritizing privacy. We describe the current challenges healthcare and AI communities face, the need for an open platform, the design philosophy of MedPerf, its current implementation status and real-world deployment, our roadmap and, importantly, the use of MedPerf with multiple international institutions within cloud-based technology and on-premises scenarios. Finally, we welcome new contributions by researchers and organizations to further strengthen MedPerf as an open benchmarking platform.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Spread Spectrum Time Domain Reflectometry (SSTDR) and Frequency Domain Reflectometry (FDR) for Detection of Cable Anomalies Using Machine Learning

Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation Inc. that is designed to operate on live cables up to 1000 volts. One of the main conclusions of a previous effort was that cable reflectometry plots can be difficult for humans to analyze due to baseline noise, low or noisy anomaly response peaks, or large responses from cable ends. Detection of cable anomalies for many of these frequencies and test conditions was challenging for manual analysis. This presented an ideal opportunity for ML analysis to distinguish undamaged cable indications from anomalous cable indications. This research discusses application of machine learning (ML) to reflectometry cable test methods. The goal was to assess feasibility to distinguish undamaged cable reflectometry responses from damaged or anomalous cable reflectometry responses. The assessment considered the 3 instruments, multiple frequency bandwidths from each instrument, multiple cable anomalies and test conditions, and both supervised and unsupervised ML approaches. Although approaches and analysis methods were not identical or directly comparable, both outputs were encouraging. The unsupervised prediction weighted accuracy was assessed by instrument and by frequency. It performed better at high frequencies with the highest prediction accuracy of 0.84 for the higher frequency FDR, 0.79 for the 48-MHz LiveWire SSTDR, and 0.77 for 300-MHz PNNL SSTDR. The initial weighted accuracy average across all frequencies for using supervised ML was 0.56 to 0.68. The supervised analysis was repeated with noisier training data removed resulting in weighted accuracies of 0.69 to 0.87. These weighted accuracies are not directly comparable due to differences in the supervised and unsupervised analysis details but do indicate an encouraging trend. Even with limited and unbalanced data, strong prediction accuracies seem encouraging for further work including more data under a wider range of conditions.

42 ENGINEERING↗

DOE OSTI2023

Analysis of Tasks in Autonomous Systems Using the EMRALD Dynamic Risk Assessment Tool

An autonomous system refers to the system that has the power and ability for self-governance in the performance of system functions. Autonomous systems have been actively pursued in a variety of domains such as automotive, aviation, maritime, medicine, and nuclear fields. As an unmanned concept employing the highest automation level, the autonomous system basically performs most of the work in normal operations or emergency situations. However, despite advances in technology, many researchers have noted these systems still require human actions. The nature of human actions on autonomous systems is different than the human actions that are considered in existing systems. Nevertheless, only a few studies have been conducted on 1) characterizing the different types of errors and risks associated with human actions interacting with autonomous systems and 2) how to evaluate human actions in the autonomous operations. As a starting point, this study aims to investigate differences of tasks in autonomous operation compared to those in existing nuclear power plant operation using the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) software. In this paper, insights aspect of human error and time are derived out and discussed based on the output of the EMRALD models.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1988

Computer simulation of multiple pilots flying a modern high performance helicopter

A computer simulation of a human response pilot mechanism within the flight control loop of a high-performance modern helicopter is presented. A human response mechanism, implemented by a low order, linear transfer function, is used in a decoupled single variable configuration that exploits the dominant vehicle characteristics by associating cockpit controls and instrumentation with specific vehicle dynamics. Low order helicopter models obtained from evaluations of the time and frequency domain responses of a nonlinear simulation model, provided by NASA Lewis Research Center, are presented and considered in the discussion of the pilot development. Pilot responses and reactions to test maneuvers are presented and discussed. Higher level implementation, using the pilot mechanisms, are discussed and considered for their use in a comprehensive control structure.

Zipf, Mark E.↗

NASA NTRS1989

Learning in tele-autonomous systems using Soar

Robo-Soar is a high-level robot arm control system implemented in Soar. Robo-Soar learns to perform simple block manipulation tasks using advice from a human. Following learning, the system is able to perform similar tasks without external guidance. It can also learn to correct its knowledge, using its own problem solving in addition to outside guidance. Robo-Soar corrects its knowledge by accepting advice about relevance of features in its domain, using a unique integration of analytic and empirical learning techniques.

Laird, John E.↗

DOE OSTI2022

Demonstration and Evaluation of the Human-Technology Integration Guidance for Plant Modernization

The significance of nuclear power in its role producing carbon-free electricity to the U.S. cannot be overstated. However, with changes in the energy market coupled with changes in incentives given to certain resources like solar and wind, the operating and maintenance costs for these sources have seen a significant reduction, which has consequently negatively impacted the economic viability of the existing U.S. nuclear power plant fleet. Digital instrumentation and control (I&C) and control room modernization is a major critical work domain to reduce operating and maintenance costs. Existing nuclear power plants are commonly configured with mostly legacy analog I&C as well as isolated pockets of digital I&C (a plant process computer, digital recorders, etc.). One challenge with this analog I&C is that replacement parts are becoming prohibitively more expensive and difficult to obtain. Moreover, a significant challenge with the existing analog I&C is that the way in which plants are currently operated and maintained is no longer competitive with other electricity generating sources, like natural gas, where advanced digital I&C technologies are commonplace. This gap between the waynuclear power plants are operated compared to other electricity generating sources significantly challenges the economic viability of the nuclear industry. Indeed, digital I&C systems can fundamentally change the way the plant is operated (i.e., the concept of operation). The introduction of digital I&C technologies offers a wealth of benefits to the nuclear industry. However, it is important to emphasize that, to realize these benefits, a careful understanding of how to integrate technology in a collaborative way that leverages the capabilities of people and technologies is necessary. Human-technology integration applies human factors engineering methods and tools to ensure the safe and reliable use of these technologies while ensuring that the inherent features of the technologies that provide economic value are not missed. The scope of this work documents the demonstration of the recently developed human and technology integration methodology, as applied to developing a new vision and concept of operations for a major U.S. nuclear power plant fleet. This report focuses on the methodological aspects of developing a vision and concept of operations. This report shares the tools, activities, and lessons learned during a modernization currently underway for industry as a whole to consider when planning any significant digital modification and developing a new vision and concept of operations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Crystal Structure and Characterization of Human Heavy-Chain Only Antibodies Reveals a Novel, Stable Dimeric Structure Similar to Monoclonal Antibodies

We report the novel crystal structure and characterization of symmetrical, homodimeric humanized heavy-chain-only antibodies or dimers (HC2s). HC2s were found to be significantly coexpressed and secreted along with mAbs from transient CHO HC/LC cotransfection, resulting in an unacceptable mAb developability attribute. Expression of full-length HC2s in the absence of LC followed by purification resulted in HC2s with high purity and thermal stability similar to conventional mAbs. The V H and C H 1 portion of the heavy chain (or Fd) was also efficiently expressed and yielded a stable, covalent, and reducible dimer (Fd2). Mutagenesis of all heavy chain cysteines involved in disulfide bond formation revealed that Fd2 intermolecular disulfide formation was similar to Fabs and elucidated requirements for Fd2 folding and expression. For one HC2, we solved the crystal structure of the Fd2 domain to 2.9 Å, revealing a highly symmetrical homodimer that is structurally similar to Fabs and is mediated by conserved (C H 1) and variable (V H ) contacts with all CDRs positioned outward for target binding. Interfacial dimer contacts revealed by the crystal structure were mutated for two HC2s and were found to dramatically affect HC2 formation while maintaining mAb bioactivity, offering a potential means to modulate novel HC2 formation through engineering. These findings indicate that human heavy-chain dimers can be secreted efficiently in the absence of light chains, may show good physicochemical properties and stability, are structurally similar to Fabs, offer insights into their mechanism of formation, and may be amenable as a novel therapeutic modality.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2013

Evidence Report: Risk of Inadequate Human-Computer Interaction

Human-computer interaction (HCI) encompasses all the methods by which humans and computer-based systems communicate, share information, and accomplish tasks. When HCI is poorly designed, crews have difficulty entering, navigating, accessing, and understanding information. HCI has rarely been studied in an operational spaceflight context, and detailed performance data that would support evaluation of HCI have not been collected; thus, we draw much of our evidence from post-spaceflight crew comments, and from other safety-critical domains like ground-based power plants, and aviation. Additionally, there is a concern that any potential or real issues to date may have been masked by the fact that crews have near constant access to ground controllers, who monitor for errors, correct mistakes, and provide additional information needed to complete tasks. We do not know what types of HCI issues might arise without this "safety net". Exploration missions will test this concern, as crews may be operating autonomously due to communication delays and blackouts. Crew survival will be heavily dependent on available electronic information for just-in-time training, procedure execution, and vehicle or system maintenance; hence, the criticality of the Risk of Inadequate HCI. Future work must focus on identifying the most important contributing risk factors, evaluating their contribution to the overall risk, and developing appropriate mitigations. The Risk of Inadequate HCI includes eight core contributing factors based on the Human Factors Analysis and Classification System (HFACS): (1) Requirements, policies, and design processes, (2) Information resources and support, (3) Allocation of attention, (4) Cognitive overload, (5) Environmentally induced perceptual changes, (6) Misperception and misinterpretation of displayed information, (7) Spatial disorientation, and (8) Displays and controls.

Kritina Holden↗

DOE OSTI2020

Thermal coupling-decoupling mechanism of heat transfer across van der Waals interfaces in n-eicosane

Progress toward improving thermal transport properties of n-eicosane, a promising phase change material for thermal energy storage near human body temperature, is hindered by lack of a general theoretical framework to model thermal interfacial conductance (TIC) of the van der Waals (vdW) force bonded molecular interfaces, which have little compositional/structural mismatch. Combining molecular dynamics simulations at temperatures up to the melting point and a time-domain analysis of interfacial heat currents in individual molecules, we unveil that (1) the heat flux across a molecular vdW interface has an alternating coupling-decoupling pattern at the single molecule level due to thermal fluctuations, and (2) the net heat transfer during the thermally coupled periods is orders of magnitude larger than that during the thermally decoupled periods. Furthermore, we demonstrate that a vdW interface's TIC correlates almost linearly with two atomistic-scale coupling-decoupling parameters: αc and σc, that represent the duration and strength of the thermal coupling, respectively. This thermal coupling-decoupling mechanism proposes a new paradigm that explicitly accounts for the effects of structural flexibility and dynamical fluctuation on heat transfer across molecular interfaces, and will likely provide new insights into modeling thermal transport properties in a wide-ranging soft materials, including self-assembled monolayers, paraffins or lipids.

42 ENGINEERING↗

DOE OSTI2020

Structure based virtual screening identifies small molecule effectors for the sialoglycan binding protein Hsa

Infective endocarditis (IE) is a cardiovascular disease often caused by bacteria of the viridans group of streptococci, which includes Streptococcus gordonii and Streptococcus sanguinis. Previous research has found that serine-rich repeat (SRR) proteins on the S. gordonii bacterial surface play a critical role in pathogenesis by facilitating bacterial attachment to sialylated glycans displayed on human platelets. Despite their important role in disease progression, there are currently no anti-adhesive drugs available on the market. Here, we performed structure-based virtual screening using an ensemble docking approach followed by consensus scoring to identify novel small molecule effectors against the sialoglycan binding domain of the SRR adhesin protein Hsa from the S. gordonii strain DL1. The screening successfully predicted nine compounds which were able to displace the native ligand (sialyl-T antigen) in an in vitro assay and bind competitively to Hsa. Furthermore, hierarchical clustering based on the MACCS fingerprints showed that eight of these small molecules do not share a common scaffold with the native ligand. This study indicates that SRR family of adhesin proteins can be inhibited by diverse small molecules and thus prevent the interaction of the protein with the sialoglycans. This opens new avenues for discovering potential drugs against IE.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

De novo design and Rosetta-based assessment of high-affinity antibody variable regions (Fv) against the SARS-CoV -2 spike receptor binding domain ( RBD )

The continued emergence of new SARS-CoV-2 variants has accentuated the growing need for fast and reliable methods for the design of potentially neutralizing antibodies (Abs) to counter immune evasion by the virus. Here, we report on the de novo computational design of high-affinity Ab variable regions (Fv) through the recombination of VDJ genes targeting the most solvent-exposed hACE2-binding residues of the SARS-CoV-2 spike receptor binding domain (RBD) protein using the software tool OptMAVEn-2.0. Subsequently, we carried out computational affinity maturation of the designed variable regions through amino acid substitutions for improved binding with the target epitope. Immunogenicity of designs was restricted by preferring designs that match sequences from a 9-mer library of “human Abs” based on a human string content score. We generated 106 different antibody designs and reported in detail on the top five that trade-off the greatest computational binding affinity for the RBD with human string content scores. We further describe computational evaluation of the top five designs produced by OptMAVEn-2.0 using a Rosetta-based approach. We used Rosetta SnugDock for local docking of the designs to evaluate their potential to bind the spike RBD and performed “forward folding” with DeepAb to assess their potential to fold into the designed structures. Ultimately, our results identified one designed Ab variable region, P1.D1, as a particularly promising candidate for experimental testing. This effort puts forth a computational workflow for the de novo design and evaluation of Abs that can quickly be adapted to target spike epitopes of emerging SARS-CoV-2 variants or other antigenic targets.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1994

Pilot interaction with cockpit automation 2: An experimental study of pilots' model and awareness of the Flight Management System

Technological developments have made it possible to automate more and more functions on the commercial aviation flight deck and in other dynamic high-consequence domains. This increase in the degrees of freedom in design has shifted questions away from narrow technological feasibility. Many concerned groups, from designers and operators to regulators and researchers, have begun to ask questions about how we should use the possibilities afforded by technology skillfully to support and expand human performance. In this article, we report on an experimental study that addressed these questions by examining pilot interaction with the current generation of flight deck automation. Previous results on pilot-automation interaction derived from pilot surveys, incident reports, and training observations have produced a corpus of features and contexts in which human-machine coordination is likely to break down (e.g., automation surprises). We used these data to design a simulated flight scenario that contained a variety of probes designed to reveal pilots' mental model of one major component of flight deck automation: the Flight Management System (FMS). The events within the scenario were also designed to probe pilots' ability to apply their knowledge and understanding in specific flight contexts and to examine their ability to track the status and behavior of the automated system (mode awareness). Although pilots were able to 'make the system work' in standard situations, the results reveal a variety of latent problems in pilot-FMS interaction that can affect pilot performance in nonnormal time critical situations.

Sarter, Nadine B.↗