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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

An Evaluation of Controller and Pilot Performance, Workload and Acceptability under a NextGen Concept for Dynamic Weather Adapted Arrival Routing

In todays terminal operations, controller workload increases and throughput decreases when fixed standard terminal arrival routes (STARs) are impacted by storms. To circumvent this operational constraint, Prete, Krozel, Mitchell, Kim and Zou (2008) proposed to use automation to dynamically adapt arrival and departure routing based on weather predictions. The present study examined this proposal in the context of a NextGen trajectory-based operation concept, focusing on the acceptability and its effect on the controllers ability to manage traffic flows. Six controllers and twelve transport pilots participated in a human-in-the-loop simulation of arrival operations into Louisville International Airport with interval management requirements. Three types of routing structures were used: Static STARs (similar to current routing, which require the trajectories of individual aircraft to be modified to avoid the weather), Dynamic routing (automated adaptive routing around weather), and Dynamic Adjusted routing (automated adaptive routing around weather with aircraft entry time adjusted to account for differences in route length). Spacing Responsibility, whether responsibility for interval management resided with the controllers (as today), or resided with the pilot (who used a flight deck based automated spacing algorithm), was also manipulated. Dynamic routing as a whole was rated superior to static routing, especially by pilots, both in terms of workload reduction and flight path safety. A downside of using dynamic routing was that the paths flown in the dynamic conditions tended to be somewhat longer than the paths flown in the static condition.

Johnson, Walter W.↗
NASA NTRS2011

Optimizing Decision Preparedness by Adapting Scenario Complexity and Automating Scenario Generation

Klein's recognition-primed decision (RPD) framework proposes that experts make decisions by recognizing similarities between current decision situations and previous decision experiences. Unfortunately, military personnel arQ often presented with situations that they have not experienced before. Scenario-based training (S8T) can help mitigate this gap. However, SBT remains a challenging and inefficient training approach. To address these limitations, the authors present an innovative formulation of scenario complexity that contributes to the larger research goal of developing an automated scenario generation system. This system will enable trainees to effectively advance through a variety of increasingly complex decision situations and experiences. By adapting scenario complexities and automating generation, trainees will be provided with a greater variety of appropriately calibrated training events, thus broadening their repositories of experience. Preliminary results from empirical testing (N=24) of the proof-of-concept formula are presented, and future avenues of scenario complexity research are also discussed.

Dunne, Rob↗
NASA NTRSDate not supplied

Biocybernetic Closed-Loop System for Mitigating Hazardous States of Awareness

The past century of passenger flight has seen continuous improvement in aviation safety by the aerospace industry. However, while commercial aviation accident rates have continued to decline, human error-related incident and accident rates remain remarkably constant across all types of aviation (Shappell, et al., 2007). Unfortunately, this level of human error is unacceptable when considering projections for increased traffic volume (FAA, 2009), and is likely to yield more incidents and accidents unless a more complete understanding of operator error is achieved and remediations are implemented. One area of interest highlighted by researchers is Hazardous States of Awareness (HSAs) that can result from deficiencies in the design and inappropriate use of human-machine interfaces. Identifying and mitigating HSAs is critical for reducing operator errors. One promising approach uses psychophysiological measures which enable automated systems to adapt to the operator?s state and modify modes of operation to support optimal human performance (Scerbo, 2007). This paper will survey previous research and describe future directions for the application of psychophysiological measures of operators derived from cortical and autonomic assessment to perform real-time adaptive modulation of human-automation task mode mixes. The authors will present a summary of previous work done at NASA LaRC and Old Dominion University using a Psychophysiologically Adaptive System (PAS) in which the level of automation of the NASA Multi-Attribute Task Battery was modulated based on Engagement Indices derived from the users? electroencephalogram (Pope, Bogart, & Bartolome, 1995; for review see, Scerbo, Freeman, & Mikulka, 2003). Future theoretical and methodological directions for this type of closed-loop research will be discussed. Specifically, the capacity for this type of PAS to maintain effective operator state and to enable validation of candidate physiological indices will be described. Consideration will also be given to critical system characteristics (e.g., engagement indices, methods for invoking changes among system states, individual differences among users, etc.) that have been or still need to be studied. The potential of the PAS approach for interactive system design and prototyping will also be described. Examples of adaptive automation flight deck concepts in recent experiments will be highlighted and discussed.

Chad L Stephens↗
DOE OSTI2022

Automated and efficient local adaptive regression for principal component-based reduced-order modeling of turbulent reacting flows

Principal Component Analysis can be used to reduce the cost of Computational Fluid Dynamics simulations of turbulent reacting flows by reducing the dimensionality of the transported variables through projection of the thermochemical state onto a lower-dimensional manifold. However, because of the nonlinearity of the principal component source terms, nonlinear regression techniques must be utilized for the source terms in terms of the principal components. Unfortunately, widely available and utilized nonlinear regression techniques can have prohibitive computational requirements and/or accuracy that is highly dependent on user experience in ad hoc tuning of model architecture and hyperparameters. Here, in this work, a new nonlinear regression approach is proposed that is both computationally efficient and automated so does not require any user input. The approach is evaluated through a priori prediction of principal component source terms using data from a Direct Numerical Simulation of a turbulent nonpremixed n-heptane/air jet flame. In particular, the proposed framework consists of local regressions whose complexity is adapted according to the local nonlinearity of the data: local linear regression when accurate enough and local Artificial Neural Networks when nonlinear regression is required. The number of local clusters for local regression is determined automatically using the Davies-Bouldin index. In addition, Bayesian optimization is utilized for model training (i.e., to select the best architectures and hyperparameters of the nonlinear regressions in an unsupervised fashion), eliminating ad hoc hand-tuning and/or expensive grid searches. Overall, compared to a single, global neural network, the new local adaptive regression approach is shown to have comparable accuracy but 69% less training time due to the utilization of local linear regression and faster training of local neural networks.

42 ENGINEERING↗
NASA NTRS1985

Automation of assertion testing - Grid and adaptive techniques

Assertions can be used to automate the process of testing software. Two methods for automating the generation of input test data are described in this paper. One method selects the input values of variables at regular intervals in a 'grid'. The other, adaptive testing, uses assertion violations as a measure of errors detected and generates new test cases based on test results. The important features of assertion testing are that: it can be used throughout the entire testing cycle; it provides automatic notification of error conditions; and it can be used with automatic input generation techniques which eliminate the subjectivity in choosing test data.

Andrews, D. M.↗
NASA NTRS1984

An approach for automated analysis of particle holograms

A simple method for analyzing droplet holograms is proposed that is readily adaptable to automation using modern image digitizers and analyzers for determination of the number, location, and size distributions of spherical or nearly spherical droplets. The method determines these parameters by finding the spatial location of best focus of the droplet images. With this location known, the particle size may be determined by direct measurement of image area in the focal plane. Particle velocity and trajectory may be determined by comparison of image locations at different instants in time. The method is tested by analyzing digitized images from a reconstructed in-line hologram, and the results show that the method is more accurate than a time-consuming plane-by-plane search for sharpest focus.

Stanton, A. C.↗
NASA NTRS2001

Effects of Selected Task Performance Criteria at Initiating Adaptive Task Real locations

In the current report various performance assessment methods used to initiate mode transfers between manual control and automation for adaptive task reallocation were tested. Participants monitored two secondary tasks for critical events while actively controlling a process in a fictional system. One of the secondary monitoring tasks could be automated whenever operators' performance was below acceptable levels. Automation of the secondary task and transfer of the secondary task back to manual control were either human- or machine-initiated. Human-initiated transfers were based on the operator's assessment of the current task demands while machine-initiated transfers were based on the operators' performance. Different performance assessment methods were tested in two separate experiments.

Montgomery, Demaris A.↗
NASA NTRS1986

Automated scanning of plastic nuclear track detectors using the Minnesota star scanner

The problems found in an attempt to adapt an automated scanner of astronomical plates, the Minnesota Automated Dual Plate Scanner (APS), to locating and measuring the etch pits produced by ionizing particles in plastic nuclear track detectors (CR-39) are described. A visual study of these pits was made to determine the errors introduced in determining positions and shapes. Measurements made under a low power microscope were compared with those from the APS.

Fink, P. J.↗
NASA NTRSDate not supplied

Improvements to the LAURA Mesh Adaptation Algorithm

This paper describes recent improvements to the LAURA code that removes the requirementof unbroken body-normal lines when using the automated mesh adaptation algorithm inLAURA responsible for mesh alignment with shock and adjusting near-wall mesh spacing. Fornon-simple geometry, restricting block topologies such that blocks span the domain from thesurface wall boundaries to domain inflow boundary can be difficult or impossible. Removing thisrequirement enables novel block topologies that simplify the meshing workflow for LAURA users.The new adaptation algorithm implementation in LAURA is described and several examples ofthe adaptation are presented to demonstrate the efficacy of the adaptation algorithm.

LAURA↗
NASA NTRSDate not supplied

Improvements to the LAURA Mesh Adaptation Algorithm

This paper describes recent improvements to the LAURA code that removes the requirementof unbroken body-normal lines when using the automated mesh adaptation algorithm inLAURA responsible for mesh alignment with shock and adjusting near-wall mesh spacing. Fornon-simple geometry, restricting block topologies such that blocks span the domain from thesurface wall boundaries to domain inflow boundary can be difficult or impossible. Removing thisrequirement enables novel block topologies that simplify the meshing workflow for LAURA users.The new adaptation algorithm implementation in LAURA is described and several examples ofthe adaptation are presented to demonstrate the efficacy of the adaptation algorithm.

LAURA↗
DOE OSTI2025

Novel PV Array System Design to Accelerate Solar Deployment, Reduce LCOE, Reduce Land Use Competition, and Increase Siting Flexibility

The increasing demand for solar energy faces significant barriers, including inefficient construction processes, high project costs limiting LCOE reductions, and diminishing availability of "good" sites with favorable interconnection. Conventional solar installations are often constrained by long construction timelines and the need for flat, large plots. Furthermore, the industry struggles with a shortage of skilled labor. Planted Solar aims to address these challenges by fundamentally transforming solar deployment from a construction project into a streamlined manufacturing process. Our novel approach combines high-density racking, integrated terrain-following design software, and installation automation. Unlike competing solutions that either assist with standard array assembly or offer dense packing without terrain adaptability or automation, Planted's technology uniquely brings together a new array product with in-place automated manufacturing to achieve the lowest possible cost, greater site flexibility, and accelerated deployment.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Automating the Study of Microbial Adaptation Dynamics on and off the ISS

The International Space Station (ISS) not only serves as a unique environment for humans, but also the microorganisms that join alongside. Many microbes present on the spacecraft arrive via humans, and as they interact with different surfaces they begin to inhabit those locations. Much like how human health has shown to be impacted by these extreme environments, microbial viability and response to stress also changes. Experimental evolution (EE) can aid in studying how microbes’ growth and activity changes within the ISS environments by applying controlled stressors to microbial cultures and monitoring their response over generations. EE studies are commonly done manually in laboratories, but, with multiple environmental variables to measure and adjust, it becomes highly labor-intensive, prone to human error, and challenging to scale. A multipurpose automated EE system named the AADEC has been developed to address these problems. This system integrates multiple sensors into a single fluidic chamber using UV-C flux, temperature, and media composition as stressors. AADEC contains five sensors: oxidation-reduction potential, electrical conductivity, pH, dissolved oxygen, and optical density. On their own, each is able to provide certain information on growth rate or metabolism; together, they show in detail how stressors affect life. AADEC studies can be conducted on Earth and repeated aboard the ISS to see how behavior changes when exposed to space mission stressors such as microgravity and radiation. AADEC’s auxiliary systems include peristaltic pumps for media exchange, magnetic rods for agitation, and a Raspberry Pi microprocessor to monitor, store, and adjust stressor levels real-time. This allows researchers to gather information within rapid generations, data and accuracy which is challenging to achieve through manual studies. With further miniaturization and automation, such as a more robust single-piece fluidics card, AADEC has the potential to be developed as a spacecraft payload. Support: NASA Ames CIF Award

Automating↗
NASA NTRS2014

Controller Inhibition of Automated Conflict Resolutions in a Maximum NextGen Condition

With the continued projection of increases in air traffic density, operations in the National Airspace System are expected to exceed human capabilities in the near future. In order to address the bottleneck of human workload capacity, highly automated safety-critical systems are under development to support air traffic controllers. A human-in-the-loop experiment examined controllers transition through four NextGen automation stages: Current-Day, Minimum, Moderate, and Maximum. Maximum NextGen simulated a fully automated environment where the automation was responsible for detecting and resolving conflicts within simulation parameters in high-density airspace. By allocating these tasks to the automation, the controllers task changed. The human moved to primarily a supervisory position- typically only regaining control over separation assurance tasks during conflict situations deferred by the automation. While tasks were allocated a-priori between the controller and automated agent, controllers maintained authority to inhibit the automation from interacting with particular aircraft. Preliminary work is complete, where significant differences were found in inhibition frequency between simulation participants. However, the contexts in which the controllers inhibited the automation, and their reasons for doing so, remain unclear. This analysis attempts to identity factors contributing to human controllers inhibition of the automation in the Maximum NextGen condition.

adaptable automation↗
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↗
DOE OSTI2025

Adaptive Interface-PINNs (AdaI-PINNs) for transient diffusion: Applications to forward and inverse problems in heterogeneous media

We model transient diffusion in heterogeneous materials using a novel physics-informed neural networks framework (PINNs) termed Adaptive interface physics-informed neural networks or AdaI-PINNs (Roy et al. arXiv preprint arXiv:2406.04626, 2024). AdaI-PINNs utilize different activation functions with trainable slopes tailored to each material region within the computational domain, allowing for a fully automated and adaptive PINNs approach to model interface problems with strongly and weakly discontinuous solutions. To enhance its performance in highly heterogeneous transient diffusion systems, we prescribe a suite of robust practices, including appropriate non-dimensionalization of equations, a biased sampling method, Glorot initialization, and the hard enforcement of boundary and initial conditions. Here we evaluate the efficacy of the proposed method on several benchmark forward and inverse problems. Comparative studies on one-dimensional and two-dimensional benchmark problems reveal that the modified AdaI-PINNs outperform its unmodified counterpart, achieving root-mean-square errors that are at least two orders of magnitude better in forward problems. For inverse problems, the maximum errors in the approximated diffusion coefficients by modified AdaI-PINNs are four orders of magnitude better than those of the unmodified version. Additionally, modified AdaI-PINNs demonstrate improved stability in problems with large material mismatches.

42 ENGINEERING↗
NASA NTRS2015

Detection of Operator Performance Breakdown as an Automation Triggering Mechanism

Performance breakdown (PB) has been anecdotally described as a state where the human operator "loses control of context" and "cannot maintain required task performance." Preventing such a decline in performance is critical to assure the safety and reliability of human-integrated systems, and therefore PB could be useful as a point at which automation can be applied to support human performance. However, PB has never been scientifically defined or empirically demonstrated. Moreover, there is no validated objective way of detecting such a state or the transition to that state. The purpose of this work is: 1) to empirically demonstrate a PB state, and 2) to develop an objective way of detecting such a state. This paper defines PB and proposes an objective method for its detection. A human-in-the-loop study was conducted: 1) to demonstrate PB by increasing workload until the subject reported being in a state of PB, and 2) to identify possible parameters of a detection method for objectively identifying the subjectively-reported PB point, and 3) to determine if the parameters are idiosyncratic to an individual/context or are more generally applicable. In the experiment, fifteen participants were asked to manage three concurrent tasks (one primary and two secondary) for 18 minutes. The difficulty of the primary task was manipulated over time to induce PB while the difficulty of the secondary tasks remained static. The participants' task performance data was collected. Three hypotheses were constructed: 1) increasing workload will induce subjectively-identified PB, 2) there exists criteria that identifies the threshold parameters that best matches the subjectively-identified PB point, and 3) the criteria for choosing the threshold parameters is consistent across individuals. The results show that increasing workload can induce subjectively-identified PB, although it might not be generalizable-only 12 out of 15 participants declared PB. The PB detection method based on signal detection analysis was applied to the performance data and the results showed that PB can be identified using the method, particularly when the values of the parameters for the detection method were calibrated individually.

multi-task environment↗