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Results for “hierarchical task analysis”

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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

User and Task Analysis of the Flight Surgeon Console at the Mission Control Center of the NASA Johnson Space Center

Astronauts in a space station are to some extent like patients in an intensive care unit (ICU). Medical support of a mission crew will require acquisition, transmission, distribution, integration, and archiving of significant amounts of data. These data are acquired by disparate systems and will require timely, reliable, and secure distribution to different communities for the execution of various tasks of space missions. The goal of the Comprehensive Medical Information System (CMIS) Project at Johnson Space Center Flight Medical Clinic is to integrate data from all Medical Operations sources, including the reference information sources and the electronic medical records of astronauts. A first step toward the full CMIS implementation is to integrate and organize the reference information sources and the electronic medical record with the Flight Surgeons console. In order to investigate this integration, we need to understand the usability problems of the Flight Surgeon's console in particular and medical information systems in general. One way to achieve this understanding is through the use of user and task analyses whose general purpose is to ensure that only the necessary and sufficient task features that match users capacities will be included in system implementations. The goal of this summer project was to conduct user and task analyses employing cognitive engineering techniques to analyze the task of the Flight Surgeons and Biomedical Engineers (BMEs) while they worked on Console. The techniques employed were user interviews, observations and a questionnaire to collect data for which a hierarchical task analysis and an information resource assessment were performed. They are described in more detail below. Finally, based on our analyses, we make recommendations for improvements to the support structure.

Johnson, Kathy A.↗
NASA NTRSDate not supplied

Advancements in Remote Ground Control Station Operator Pilot in Command Training Program for Beyond Visual Line of Sight Flight Operations

The training program for a Remote Ground Control Station Operator Pilot in Command (R-GCSO PIC) at NASA Langley Research Center marks a pivotal evolution in preparing operators for Beyond Visual Line of Sight (BVLOS) operations. This program, developed within the Advanced Air Mobility (AAM) project High Density Vertiplex (HDV) subproject, was crafted to bridge the gap between traditional Ground Control Station Operators (GCSO) and R-GCSO PICs, focusing on uncrewed aircraft systems (UAS). It encompassed extensive theoretical and practical training, including hands-on experience with advanced simulators and live flight operations, while ensuring a deep understanding of BVLOS complexities. The training leveraged NASA technologies like the MPATH (Measuring Performance for Autonomy Teaming with Humans) ground control station software and incorporated human factors principles to enhance operational readiness. This paper details the program's development, execution, and the critical insights gained, emphasizing the necessity of continuous adaptation in training methodologies to meet the evolving demands of UAS operations in the National Airspace System.

Ground control station operator↗
NASA NTRS1995

Inductive Approaches to Improving Diagnosis and Design for Diagnosability

The first research area under this grant addresses the problem of classifying time series according to their morphological features in the time domain. A supervised learning system called CALCHAS, which induces a classification procedure for signatures from preclassified examples, was developed. For each of several signature classes, the system infers a model that captures the class's morphological features using Bayesian model induction and the minimum message length approach to assign priors. After induction, a time series (signature) is classified in one of the classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. A second area of research assumes two sources of information about a system: a model or domain theory that encodes aspects of the system under study and data from actual system operations over time. A model, when it exists, represents strong prior expectations about how a system will perform. Our work with a diagnostic model of the RCS (Reaction Control System) of the Space Shuttle motivated the development of SIG, a system which combines information from a model (or domain theory) and data. As it tracks RCS behavior, the model computes quantitative and qualitative values. Induction is then performed over the data represented by both the 'raw' features and the model-computed high-level features. Finally, work on clustering for operating mode discovery motivated some important extensions to the clustering strategy we had used. One modification appends an iterative optimization technique onto the clustering system; this optimization strategy appears to be novel in the clustering literature. A second modification improves the noise tolerance of the clustering system. In particular, we adapt resampling-based pruning strategies used by supervised learning systems to the task of simplifying hierarchical clusterings, thus making post-clustering analysis easier.

Fisher, Douglas H.↗
NASA NTRS1993

TARGET: Rapid Capture of Process Knowledge

TARGET (Task Analysis/Rule Generation Tool) represents a new breed of tool that blends graphical process flow modeling capabilities with the function of a top-down reporting facility. Since NASA personnel frequently perform tasks that are primarily procedural in nature, TARGET models mission or task procedures and generates hierarchical reports as part of the process capture and analysis effort. Historically, capturing knowledge has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent the expert's knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some types of knowledge, procedural knowledge has received relatively little attention. In essence, TARGET is one of the first tools of its kind, commercial or institutional, that is designed to support this type of knowledge capture undertaking. This paper will describe the design and development of TARGET for the acquisition and representation of procedural knowledge. The strategies employed by TARGET to support use by knowledge engineers, subject matter experts, programmers and managers will be discussed. This discussion includes the method by which the tool employs its graphical user interface to generate a task hierarchy report. Next, the approach to generate production rules for incorporation in and development of a CLIPS based expert system will be elaborated. TARGET also permits experts to visually describe procedural tasks as a common medium for knowledge refinement by the expert community and knowledge engineer making knowledge consensus possible. The paper briefly touches on the verification and validation issues facing the CLIPS rule generation aspects of TARGET. A description of efforts to support TARGET's interoperability issues on PCs, Macintoshes and UNIX workstations concludes the paper.

Ortiz, C. J.↗
DOE OSTI2025

El Agente: An autonomous agent for quantum chemistry

Computational chemistry tools are widely used to study the behavior of chemical phenomena. Yet, the complexity of these tools can make them inaccessible to non-specialists and challenging even for experts. In this work, we introduce El Agente Q, an LLM-based multi-agent system that dynamically generates and executes quantum chemistry workflows from natural language user prompts. The system is built on a novel cognitive architecture featuring a hierarchical memory framework that enables flexible task decomposition, adaptive tool selection, post-analysis, and autonomous file handling and submission. El Agente Q is benchmarked on six university-level course exercises and two case studies, demonstrating robust problem-solving performance (averaging >87% task success) and adaptive error handling through in situ debugging. It also supports longer-term, multi-step task execution for more complex workflows, while maintaining transparency through detailed action trace logs. Together, these capabilities lay the foundation for increasingly autonomous and accessible quantum chemistry.

agentic systems↗
DOE OSTI2025

Extremely Scalable Distributed Computation of Contour Trees via Pre-Simplification

Contour trees offer an abstract representation of the level set topology in scalar fields and are widely used in topological data analysis and visualization. However, applying contour trees to large-scale scientific datasets remains challenging due to scalability limitations. Recent developments in distributed hierarchical contour trees have addressed these challenges by enabling scalable computation across distributed systems. Building on these structures, advanced analytical tasks—such as volumetric branch decomposition and contour extraction—have been introduced to facilitate large-scale scientific analysis. Despite these advancements, such analytical tasks substantially increase memory usage, which hampers scalability. In this paper, we propose a pre-simplification strategy to significantly reduce the memory overhead associated with analytical tasks on distributed hierarchical contour trees. We demonstrate enhanced scalability through strong scaling experiments, constructing the largest known contour tree—comprising over half a trillion nodes with complex topology—in under 15 minutes on a dataset containing 550 billion elements.

Li, Mingzhe [University of Utah]↗
NASA NTRS1994

Program For Systematic Documentation Of Tasks

Task Analysis Report Generation Tool (TARGET) computer program is graphical-interface software tool used to capture procedural knowledge and translate knowledge into hierarchical report. Designed to help programmer document expert's task, enabling programmer to build expert-system computer program that helps others perform task. Flexibility key element of design and of knowledge-acquisition session. Easy to use and tailored to accommodate users ranging from novice to experienced builder of expert systems. Written in C language.

Ortiz, Christopher John↗
NASA NTRSDate not supplied

A Partitioned -Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing

The NASA Multiscale Analysis Tool (NASMAT) is a “plug and play” software package that allows users to conduct massively multiscale modeling of hierarchical and nonlinear materials. This work extends the scalability and improves the High Performance Computing friendliness of NASMAT by adopting a Partitioned Task-Parallel approach. Interoperability of NASMAT with external software is enhanced through preCICE, a open source library for multiphysics coupling in a partitioned manner. Enhancement through preCICE allows for easy integration of NASMAT to other macro solvers and dissociates the parallelization strategy adopted within NASMAT from the macro solver. The task-parallel framework based on Master-Worker approach is implemented as the parallelization scheme. The scheme accounts for hierarchy of multiple scales (task-dependence) and heterogeneous nature (dynamic load balancing) of computations. The applicability and scalability of the framework will be evaluated by analyzing large scale engineering problems through massively multiscale methods.

NASMAT↗
NASA NTRS1991

Using GOMS models and hypertext to create representations of medical procedures for online display

This study investigated two methods to improve organization and presentation of computer-based medical procedures. A literature review suggested that the GOMS (goals, operators, methods, and selecton rules) model can assist in rigorous task analysis, which can then help generate initial design ideas for the human-computer interface. GOMS model are hierarchical in nature, so this study also investigated the effect of hierarchical, hypertext interfaces. We used a 2 x 2 between subjects design, including the following independent variables: procedure organization - GOMS model based vs. medical-textbook based; navigation type - hierarchical vs. linear (booklike). After naive subjects studies the online procedures, measures were taken of their memory for the content and the organization of the procedures. This design was repeated for two medical procedures. For one procedure, subjects who studied GOMS-based and hierarchical procedures remembered more about the procedures than other subjects. The results for the other procedure were less clear. However, data for both procedures showed a 'GOMSification effect'. That is, when asked to do a free recall of a procedure, subjects who had studies a textbook procedure often recalled key information in a location inconsistent with the procedure they actually studied, but consistent with the GOMS-based procedure.

Gugerty, Leo↗
NASA NTRS1984

Aerospace engineering design by systematic decomposition and multilevel optimization

A method for systematic analysis and optimization of large engineering systems, by decomposition of a large task into a set of smaller subtasks that is solved concurrently is described. The subtasks may be arranged in hierarchical levels. Analyses are carried out in each subtask using inputs received from other subtasks, and are followed by optimizations carried out from the bottom up. Each optimization at the lower levels is augmented by analysis of its sensitivity to the inputs received from other subtasks to account for the couplings among the subtasks in a formal manner. The analysis and optimization operations alternate iteratively until they converge to a system design whose performance is maximized with all constraints satisfied. The method, which is still under development, is tentatively validated by test cases in structural applications and an aircraft configuration optimization.

Sobieszczanski-Sobieski, J.↗
NASA NTRS1994

Planning applications in image analysis

We describe two interim results from an ongoing effort to automate the acquisition, analysis, archiving, and distribution of satellite earth science data. Both results are applications of Artificial Intelligence planning research to the automatic generation of processing steps for image analysis tasks. First, we have constructed a linear conditional planner (CPed), used to generate conditional processing plans. Second, we have extended an existing hierarchical planning system to make use of durations, resources, and deadlines, thus supporting the automatic generation of processing steps in time and resource-constrained environments.

Boddy, Mark↗
NASA NTRS1984

Aerospace engineering design by systematic decomposition and multilevel optimization

This paper describes a method for systematic analysis and optimization of large engineering systems, e.g., aircraft, by decomposition of a large task into a set of smaller, self-contained subtasks that can be solved concurrently. The subtasks may be arranged in many hierarchical levels with the assembled system at the top level. Analyses are carried out in each subtask using inputs received from other subtasks, and are followed by optimizations carried out from the bottom up. Each optimization at the lower levels is augmented by analysis of its sensitivity to the inputs received from other subtasks to account for the couplings among the subtasks in a formal manner. The analysis and optimization operations alternate iteratively until they converge to a system design whose performance is maximized with all constraints satisfied. The method, which is still under development, is tentatively validated by test cases in structural applications and an aircraft configuration optimization. It is pointed out that the method is intended to be compatible with the typical engineering organization and the modern technology of distributed computing.

Sobieszczanski-Sobieski, J.↗
NASA NTRS2013

Application Agreement and Integration Services

Application agreement and integration services are required by distributed, fault-tolerant, safety critical systems to assure required performance. An analysis of distributed and hierarchical agreement strategies are developed against the backdrop of observed agreement failures in fielded systems. The documented work was performed under NASA Task Order NNL10AB32T, Validation And Verification of Safety-Critical Integrated Distributed Systems Area 2. This document is intended to satisfy the requirements for deliverable 5.2.11 under Task 4.2.2.3. This report discusses the challenges of maintaining application agreement and integration services. A literature search is presented that documents previous work in the area of replica determinism. Sources of non-deterministic behavior are identified and examples are presented where system level agreement failed to be achieved. We then explore how TTEthernet services can be extended to supply some interesting application agreement frameworks. This document assumes that the reader is familiar with the TTEthernet protocol. The reader is advised to read the TTEthernet protocol standard [1] before reading this document. This document does not re-iterate the content of the standard.

Driscoll, Kevin R.↗
DOE OSTI2024

A Method for Producing Hierarchical and Statistically Calibrated Predictions of Nuclear Material Properties from Existing Models

Computer vision-based analysis of micrographs of nuclear materials is an emerging technique for property prediction, synthetic route identification, and other material analysis tasks. These analysis tasks play a pivotal role in many material characterization applications such as signature development for treaty verification, process optimization, etc. The backbone in many of the recent computer vision-based techniques is a deep learning model, which takes a fixed-size set of pixels and provides a class prediction for that set of pixels. For example, previous work developed a deep convolutional neural network (CNN) to predict the synthetic route from a 256 px x 256 px patch taken from a larger image of uranium ore concentrates. In this work, we present several methods for first calibrating these models in a manner that they can provide accurate probabilities of their predictions’ veracity, and several methods of combining these probabilities. Overall, the combination of these two steps into a pipeline allows for full-image and even full-sample (where a sample has many images) predictions with associated confidence values. Finally, we show that one can also use the patch predictions and confidence to produce a visualization to map predicted constituents through the image. Results and examples for predicting and mapping uranium ore concentrates’ synthetic process from imagery will be presented.

artificial intelligence↗
NASA NTRS1992

File servers, networking, and supercomputers

One of the major tasks of a supercomputer center is managing the massive amount of data generated by application codes. A data flow analysis of the San Diego Supercomputer Center is presented that illustrates the hierarchical data buffering/caching capacity requirements and the associated I/O throughput requirements needed to sustain file service and archival storage. Usage paradigms are examined for both tightly-coupled and loosely-coupled file servers linked to the supercomputer by high-speed networks.

Moore, Reagan W.↗
NASA NTRS1991

File servers, networking, and supercomputers

One of the major tasks of a supercomputer center is managing the massive amount of data generated by application codes. A data flow analysis of the San Diego Supercomputer Center is presented that illustrates the hierarchical data buffering/caching capacity requirements and the associated I/O throughput requirements needed to sustain file service and archival storage. Usage paradigms are examined for both tightly-coupled and loosely-coupled file servers linked to the supercomputer by high-speed networks.

Moore, Reagan W.↗
NASA NTRS1982

Multilevel semantic analysis and problem-solving in the flight-domain

The use of knowledge-base architecture and planning control; mechanisms to perform an intelligent monitoring task in the flight domain is addressed. The route level, the trajectory level, and parts of the aerodynamics level are demonstrated. Hierarchical planning and monitoring conceptual levels, functional-directed mechanism rationalization, and using deep-level mechanism models for diagnoses of dependent failures are discussed.

Chien, R. T.↗