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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Constraint, Intelligence, and Control Hierarchy in Virtual Environments

This paper seeks to deal directly with the question of what makes virtual actors and objects that are experienced in virtual environments seem real. (The term virtual reality, while more common in public usage, is an oxymoron; therefore virtual environment is the preferred term in this paper). Reality is difficult topic, treated for centuries in those sub-fields of philosophy called ontology- "of or relating to being or existence" and epistemology- "the study of the method and grounds of knowledge, especially with reference to its limits and validity" (both from Webster s, 1965). Advances in recent decades in the technologies of computers, sensors and graphics software have permitted human users to feel present or experience immersion in computer-generated virtual environments. This has motivated a keen interest in probing this phenomenon of presence and immersion not only philosophically but also psychologically and physiologically in terms of the parameters of the senses and sensory stimulation that correlate with the experience (Ellis, 1991). The pages of the journal Presence: Teleoperators and Virtual Environments have seen much discussion of what makes virtual environments seem real (see, e.g., Slater, 1999; Slater et al. 1994; Sheridan, 1992, 2000). Stephen Ellis, when organizing the meeting that motivated this paper, suggested to invited authors that "We may adopt as an organizing principle for the meeting that the genesis of apparently intelligent interaction arises from an upwelling of constraints determined by a hierarchy of lower levels of behavioral interaction. "My first reaction was "huh?" and my second was "yeah, that seems to make sense." Accordingly the paper seeks to explain from the author s viewpoint, why Ellis s hypothesis makes sense. What is the connection of "presence" or "immersion" of an observer in a virtual environment, to "constraints" and what types of constraints. What of "intelligent interaction," and is it the intelligence of the observer or the intelligence of the environment (whatever the latter may mean) that is salient? And finally, what might be relevant about "upwelling" of constraints as determined by a hierarchy of levels of interaction?

Sheridan, Thomas B.↗
DOE OSTI2025

A compendium of human gene functions derived from evolutionary modelling

A comprehensive, computable representation of the functional repertoire of all macromolecules encoded within the human genome is a foundational resource for biology and biomedical research. The Gene Ontology Consortium has been working towards this goal by generating a structured body of information about gene functions, which now includes experimental findings reported in more than 175,000 publications for human genes and genes in experimentally tractable model organisms 1,2 . Here, we describe the results of a large, international effort to integrate all of these findings to create a representation of human gene functions that is as complete and accurate as possible. Specifically, we apply an expert-curated, explicit evolutionary modelling approach to all human protein-coding genes. This approach integrates available experimental information across families of related genes into models that reconstruct the gain and loss of functional characteristics over evolutionary time. The models and the resulting set of 68,667 integrated gene functions cover approximately 82% of human protein-coding genes. The functional repertoire reveals a marked preponderance of molecular regulatory functions, and the models provide insights into the evolutionary origins of human gene functions. We show that our set of descriptions of functions can improve the widely used genomic technique of Gene Ontology enrichment analysis. The experimental evidence for each functional characteristic is recorded, thereby enabling the scientific community to help review and improve the resource, which we have made publicly available.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1979

A survey of Applied Psychological Services' models of the human operator

A historical perspective is presented in terms of the major features and status of two families of computer simulation models in which the human operator plays the primary role. Both task oriented and message oriented models are included. Two other recent efforts are summarized which deal with visual information processing. They involve not whole model development but a family of subroutines customized to add the human aspects to existing models. A global diagram of the generalized model development/validation process is presented and related to 15 criteria for model evaluation.

Siegel, A. I.↗
NASA NTRS2012

Understanding the Impact of User Frustration Intensities on Task Performance Using the OCC Theory of Emotions

Have you heard the saying "frustration is written all over your falce"? Well this saying is true, but that is not the only place. Frustration is written all over your face and your body. The human body has various means to communicate an emotion without the utterance of a single word. The Media Equation says that people interact with computers as if they are human: this includes experiencing frustration. This research measures frustration by monitoring human body-based measures such as heart rate, posture, skin temperature. and respiration. The OCC Theory of Emotions is used to separate frustration into different levels or intensities. The results of this study showed that individual intensities of frustration exist, so that task performance is not degraded. Results from this study can be used by usability testers to model how much frustration is needed before task performance measures start to decrease.

Washington, Gloria↗
NASA NTRS1972

Speed in Information Processing with a Computer Driven Visual Display in a Real-time Digital Simulation

Information transfer between the operator and computer-generated display systems is an area where the human factors engineer discovers little useful design data relating human performance to system effectiveness. This study utilized a computer-driven, cathode-ray-tube graphic display to quantify human response speed in a sequential information processing task. The performance criteria was response time to sixteen cell elements of a square matrix display. A stimulus signal instruction specified selected cell locations by both row and column identification. An equal probable number code, from one to four, was assigned at random to the sixteen cells of the matrix and correspondingly required one of four, matched keyed-response alternatives. The display format corresponded to a sequence of diagnostic system maintenance events, that enable the operator to verify prime system status, engage backup redundancy for failed subsystem components, and exercise alternate decision-making judgements. The experimental task bypassed the skilled decision-making element and computer processing time, in order to determine a lower bound on the basic response speed for given stimulus/response hardware arrangement.

Kyle, R. G.↗
NASA NTRS1996

On the Visual Input Driving Human Smooth-Pursuit Eye Movements

Current computational models of smooth-pursuit eye movements assume that the primary visual input is local retinal-image motion (often referred to as retinal slip). However, we show that humans can pursue object motion with considerable accuracy, even in the presence of conflicting local image motion. This finding indicates that the visual cortical area(s) controlling pursuit must be able to perform a spatio-temporal integration of local image motion into a signal related to object motion. We also provide evidence that the object-motion signal that drives pursuit is related to the signal that supports perception. We conclude that current models of pursuit should be modified to include a visual input that encodes perceived object motion and not merely retinal image motion. Finally, our findings suggest that the measurement of eye movements can be used to monitor visual perception, with particular value in applied settings as this non-intrusive approach would not require interrupting ongoing work or training.

Stone, Leland S.↗
NASA NTRS1994

Unique life sciences research facilities at NASA Ames Research Center

The Life Science Division at NASA's Ames Research Center has a suite of specialized facilities that enable scientists to study the effects of gravity on living systems. This paper describes some of these facilities and their use in research. Seven centrifuges, each with its own unique abilities, allow testing of a variety of parameters on test subjects ranging from single cells through hardware to humans. The Vestibular Research Facility allows the study of both centrifugation and linear acceleration on animals and humans. The Biocomputation Center uses computers for 3D reconstruction of physiological systems, and interactive research tools for virtual reality modeling. Psycophysiological, cardiovascular, exercise physiology, and biomechanical studies are conducted in the 12 bed Human Research Facility and samples are analyzed in the certified Central Clinical Laboratory and other laboratories at Ames. Human bedrest, water immersion and lower body negative pressure equipment are also available to study physiological changes associated with weightlessness. These and other weightlessness models are used in specialized laboratories for the study of basic physiological mechanisms, metabolism and cell biology. Visual-motor performance, perception, and adaptation are studied using ground-based models as well as short term weightlessness experiments (parabolic flights). The unique combination of Life Science research facilities, laboratories, and equipment at Ames Research Center are described in detail in relation to their research contributions.

Mulenburg, G. M.↗
DOE OSTI2023

Human-Building Collaboration: Toward lighting enabled collaborative system design

The profession of lighting design is evolving as contemporary lighting systems increasingly rely on cutting-edge computational technologies, sensors, and IOT systems. This trend requires designers to incorporate ideas of automation, dynamic controls, and user-system interaction into their design logic. However, real-time lighting simulations are constrained by inherent limitations arising from the reductive assumptions inevitably introduced in simulated lighting environments. This raises the question of how can designers account for the discrepancies between simulated and real lighting environments, and how can collaboration between humans and autonomous lighting systems bridge this gap. To address this question, we propose a protocol for designing collaborative interactions between humans and systems. Furthermore, this protocol builds on the Human-Lighting System Interaction Framework and demonstrates how human and system intelligence can be combined to fine-tune lighting qualities in a given space. Our paper shows how interactive lighting systems can customize lighting based on user preferences in real-time and how global lighting configurations can be adjusted over time. Specifically, we demonstrate: a) Human-system collaboration assumptions and goals, as well as how the protocol can be integrated into digitally programmable lighting systems. b) Implementations of collaboration that reveal how system autonomy, performance, and user experience are improved over short and long-term timeframes. c) How lighting design can be enhanced beyond simulation-driven design optimization capacities. The associated affordances and limitations are discussed with respect to existing lighting simulation design frameworks.

autonomous systems↗
NASA NTRS1998

Virtual acoustics, aeronautics, and communications

An optimal approach to auditory display design for commercial aircraft would utilize both spatialized (3-D) audio techniques and active noise cancellation for safer operations. Results from several aircraft simulator studies conducted at NASA Ames Research Center are reviewed, including Traffic alert and Collision Avoidance System (TCAS) warnings, spoken orientation "beacons" for gate identification and collision avoidance on the ground, and hardware for improved speech intelligibility. The implications of hearing loss among pilots is also considered.

NASA Center ARC↗
DOE OSTI2022

Sequential Decision Making (SDM) for Mesh Refinement and Model Selection in Multiscale, Multi-Physics Applications

Intelligent automation and decision support are needed to enhance computational efficiency and robustness in multiscale and multi-physics problems, including materials science, manufacturing, and climate and weather modeling. Current scientific computing approaches for enabling decisions by scientists fail to explore the role of learning, reasoning, and probabilistic planning. Often these decisions are not performed in real-time during the computation but are made prior to the start of the computation, which must be interrupted in order to make changes to the prior choices. Such interruptions at different stages of the computation increase the total computing time and the need for a human expert to frequently monitor the results. State of art scientific computing methods consist of rule-based algorithms that cannot automatically adapt to a dynamically changing computing environment. The development of a Sequential Decision Making (SDM) framework will automate scientific computing by optimizing the policies for mesh refinement, time-stepping, model and algorithm selection, resource allocation, and pre and post-processing. Our agent SDM framework for scientific computing will consist of data-driven learning (Classifier), automated reasoning (contextual knowledge), and probabilistic planning (Reinforcement Learning). In this project, we focused on three problems to demonstrate our SDM framework on a set of ordinary and partial differential equations. Classification of Lorenz system regions using Feed-Forward Neural Networks examined learning in the SDM framework. On the other hand, reasoning and planning in the SDM framework were used in two problems: adaptive time-stepping for nonlinear ODEs using on-policy RL algorithms, and adaptive mesh refinement for 2-D PDEs using off-policy RL algorithms.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Virtual agents in a simulated virtual training environment

A drawback to live-action training simulations is the need to gather a large group of participants in order to train a few individuals. One solution to this difficulty is the use of computer-controlled agents in a virtual training environment. This allows a human participant to be replaced by a virtual, or simulated, agent when only limited responses are needed. Each agent possesses a specified set of behaviors and is capable of limited autonomous action in response to its environment or the direction of a human trainee. The paper describes these agents in the context of a simulated hostage rescue training session, involving two human rescuers assisted by three virtual (computer-controlled) agents and opposed by three other virtual agents.

Achorn, Brett↗
NASA NTRS1988

Pilot factors guidelines for the operational inspection of navigation systems

A computerized human engineered inspection technique is developed for use by FAA inspectors in evaluating the pilot factors aspects of aircraft navigation systems. The short title for this project is Nav Handbook. A menu-driven checklist, computer program and data base (Human Factors Design Criteria) were developed and merged to form a self-contained, portable, human factors inspection checklist tool for use in a laboratory or field setting. The automated checklist is tailored for general aviation navigation systems and can be expanded for use with other aircraft systems, transports or military aircraft. The Nav Handbook inspection concept was demonstrated using a lap-top computer and an Omega/VLF CDU. The program generates standardized inspection reports. Automated checklists for LORAN/C and R NAV were also developed. A Nav Handbook User's Guide is included.

Sadler, J. F.↗
NASA NTRS1975

An adaptive maneuvering logic computer program for the simulation of one-on-one air-to-air combat. Volume 1: General description

A technique for computer simulation of air combat is described. Volume 1 decribes the computer program and its development in general terms. Two versions of the program exist. Both incorporate a logic for selecting and executing air combat maneuvers with performance models of specific fighter aircraft. In the batch processing version the flight paths of two aircraft engaged in interactive aerial combat and controlled by the same logic are computed. The realtime version permits human pilots to fly air-to-air combat against the adaptive maneuvering logic (AML) in Langley Differential Maneuvering Simulator (DMS). Volume 2 consists of a detailed description of the computer programs.

Burgin, G. H.↗
NASA NTRS1981

Computer aided manual tracking

A scheme was developed to assist the human operator by augmenting an optic sight manual tracking loop with target rate estimates from a computer control algorithm which can either be a Kalman Filter or an alpha, beta, gamma filter. The idea is for the computer to provide rate tracking while the human operator is responsible for nullifying the tracking error. A simple schematic is shown to illustrate the implementation of this concept. A hybrid real-time man-in-loop simulation was used to compare the tracking performance of the same flight trajectory with or without this form of computer-aided track. Preliminary results show the advantage of computer-aided track against high speed aircraft at close range. However, good tracking before target state estimator maturity becomes more critical for aided track than without. Results are presented for a constant velocity flight trajectory.

Yin, Y. K.↗
DOE OSTI2022

Transforming Energy Through Computational Excellence: Artificial Intelligence and Machine Learning

The National Renewable Energy Laboratory's (NREL's) expertise accelerates a decarbonized energy economy through the most advanced computational techniques, including artificial intelligence (AI) and Machine Learning (ML). AI is the simulation of human intelligence processes by machines, while ML encompasses the study of computer algorithms to imitate the way humans learn.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Closed-Loop Simulations of Human-Scale Mars Lander Descent Trajectories on Frontier

A computational campaign was performed to run high-fidelity, free-flight simulations of a human-scale Mars lander concept vehicle decelerating under retropropulsion through the Martian atmosphere with closed-loop flight control. A novel approach is used to couple computational fluid dynamics (CFD) software with a mature flight mechanics package, where the two applications communicate in real-time across two geographically-dispersed computational facilities. The CFD is performed on the Frontier exascale system located at Oak Ridge National Laboratory, and the flight mechanics are executed on a system located at NASA Langley Research Center. In the current campaign, CFD is performed using finite-rate chemistry to account for the interactions between the LOXCH 4 engines and the CO 2 Martian atmosphere. A simulation of a closed-loop main engine throttling and RCS actuation is presented, demonstrating that the vehicle and model are able to maintain stability in a long-duration CFD-in-the-loop flight simulation. Comparisons are made to a reduced order model ignoring aero-propulsive interactions.

CFD↗
DOE OSTI2025

Exocortex Network for AI-Augmented Human-Led Scientific Expedition

AI advances in science can be viewed along two main directions with a fluid boundary: enhancing efficiency through automation and smart tools to accelerate tasks that humans can already perform; and enabling exploration into uncharted territories and potentially toward AGI. These advances manifest in the AI cognitive core through the development and explainability of foundation models; in the physical embodiment of instruments and facilities; and in the integrated agency of AI workflows exemplified by the science exocortex. To address the role of humans in this evolving landscape, in this Perspective, we suggest a third direction: the development of personalized agents that form human-centered networks, supporting both efficiency and exploration while ensuring that AI remains aligned with human vision.

97 MATHEMATICS AND COMPUTING↗