Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “virtual training”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Emergency Response Virtual Environment for Safe Schools

An intelligent emergency response virtual environment (ERVE) that provides emergency first responders, response planners, and managers with situational awareness as well as training and support for safe schools is presented. ERVE incorporates an intelligent agent facility for guiding and assisting the user in the context of the emergency response operations. Response information folders capture key information about the school. The system enables interactive 3D visualization of schools and academic campuses, including the terrain and the buildings' exteriors and interiors in an easy to use Web..based interface. ERVE incorporates live camera and sensors feeds and can be integrated with other simulations such as chemical plume simulation. The system is integrated with a Geographical Information System (GIS) to enable situational awareness of emergency events and assessment of their effect on schools in a geographic area. ERVE can also be integrated with emergency text messaging notification systems. Using ERVE, it is now possible to address safe schools' emergency management needs with a scaleable, seamlessly integrated and fully interactive intelligent and visually compelling solution.

Wasfy, Ayman↗
NASA NTRS2007

Exploring and Visualizing A-Train Instrument Data

The succession of US and international satellites that follow each other in close succession, known as the A-Train, affords an opportunity to atmospheric researchers that no single platform could provide: Increasing the number of observations at any given geographic location.. . a more complete "virtual science platform". However, vertically and horizontally, co-registering and regridding datasets from independently developed missions, Aqua, Calipso, Cloudsat, Parasol, and Aura, so that they can be inter-compared can be daunting to some, and may be repeated by many. Scientists will individually spend much of their time and resources acquiring A-Train datasets of interest residing at various locations, developing algorithms to match up and graph datasets along the A-Train track, and search through large amounts of data for areas and/or phenomena of interest. The aggregate amount of effort that can be expended on repeating pre-science tasks could climb into the tens of millions of dollars. The goal of the A-Train Data Depot (ATDD) is to enable free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) is accomplished by through the ATDDs Giovanni data analysis and visualization tool. Giovanni brings together data from Aqua (MODIS, AIRS, AMSR-E), Cloudsat (cloud profiling radar) and Calipso (CALIOP, IIR), as well as the Aura (OMI, MLS, HIRDLS, TES) to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. This easy to learn and use exploration tool will allow users to create vertical profiles of any desired A-Train dataset, for any given time of choice. This presentation shows the power of Giovanni by describing and illustrating how this tool facilitates and aids A-Train science and research. A web based display system Giovanni provides users with the capability of creating co-located profile images of temperature and humidity data from the MODIS, MLS and AIRS instruments for a user specified time and spatial area. In addition, Cloud and Aerosol profiles may also be displayed for the Cloudsat and Caliop instruments. The ability to modify horizontal and vertical axis range, data range and dynamic color range is also provided. Two dimensional strip plots of MODIS, AIRS, OM1 and POLDER parameters, co-located along the Cloudsat reference track, can also be plotted along with the Cloudsat cloud profiling data. Center swath pixels for the same parameters can also be shown as line plots overlaying the Cloudsat or Calipso profile images. Images and subsetted data produced in each analysis run may be downloaded. Users truly can explore and discover data specific to their needs prior to ever transferring data to their analysis tools.

Kempler, S.↗
DOE OSTI2024

Enhancing Docking Accuracy with PECAN2, a 3D Atomic Neural Network Trained without Co-Complex Crystal Structures

Decades of drug development research have explored a vast chemical space for highly active compounds. The exponential growth of virtual libraries enables easy access to billions of synthesizable molecules. Computational modeling, particularly molecular docking, utilizes physics-based calculations to prioritize molecules for synthesis and testing. Nevertheless, the molecular docking process often yields docking poses with favorable scores that prove to be inaccurate with experimental testing. To address these issues, several approaches using machine learning (ML) have been proposed to filter incorrect poses based on the crystal structures. However, most of the methods are limited by the availability of structure data. Here, we propose a new pose classification approach, PECAN2 (Pose Classification with 3D Atomic Network 2), without the need for crystal structures, based on a 3D atomic neural network with Point Cloud Network (PCN). The new approach uses the correlation between docking scores and experimental data to assign labels, instead of relying on the crystal structures. We validate the proposed classifier on multiple datasets including human mu, delta, and kappa opioid receptors and SARS-CoV-2 Mpro. Our results demonstrate that leveraging the correlation between docking scores and experimental data alone enhances molecular docking performance by filtering out false positives and false negatives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1998

Integrated Data Visualization and Virtual Reality Tool

The Integrated Data Visualization and Virtual Reality Tool (IDVVRT) Phase II effort was for the design and development of an innovative Data Visualization Environment Tool (DVET) for NASA engineers and scientists, enabling them to visualize complex multidimensional and multivariate data in a virtual environment. The objectives of the project were to: (1) demonstrate the transfer and manipulation of standard engineering data in a virtual world; (2) demonstrate the effects of design and changes using finite element analysis tools; and (3) determine the training and engineering design and analysis effectiveness of the visualization system.

Dryer, David A.↗
NASA NTRS2003

Expedition 7 Crew Training Clip

This video shows the Expedition 7 crew of the International Space Station (ISS) during various training activities prior to launch. The crew consisted of Commander Yuri Malenchenko and Flight Engineer Ed Lu. At the virtual reality lab, the two astronauts work at a control panel, with Lu operating a joystick and speaking on earphones. Another section of the video shows Lu and Malenchenko inputting data into laptop computers, Lu testing an intercom and a video camera, and Lu using a machine to analyze blood samples from the crew. At the neutral buoyancy lab, the astronauts are helped in suit-up. The attachment of their gloves is shown. The video ends with Lu and Malenchenko lowered into a pool on a platform.

Source record↗
NASA NTRS1998

Wrap-Around Worlds

Flogiston Corporation was included in Spinoff 1992 for its stress reducing chair based on data from NASA's Anthropometric Source Book. Now, under a NASA SBIR (Small Business Innovative Research), Flogiston developed a new form of immersion in virtual and video spaces called Neutral Immersion. The technology is called Flostation and is the commercial spinoff from the astronaut training system. Motorola purchased the first Flostation for testing and demonstrating a new warping chip it is developing.

Source record↗
NASA NTRS2002

Visual Inference Programming

The goal of visual inference programming is to develop a software framework data analysis and to provide machine learning algorithms for inter-active data exploration and visualization. The topics include: 1) Intelligent Data Understanding (IDU) framework; 2) Challenge problems; 3) What's new here; 4) Framework features; 5) Wiring diagram; 6) Generated script; 7) Results of script; 8) Initial algorithms; 9) Independent Component Analysis for instrument diagnosis; 10) Output sensory mapping virtual joystick; 11) Output sensory mapping typing; 12) Closed-loop feedback mu-rhythm control; 13) Closed-loop training; 14) Data sources; and 15) Algorithms. This paper is in viewgraph form.

Wheeler, Kevin↗
DOE OSTI2023

Prediction on X-ray output of free electron laser based on artificial neural networks

Abstract Knowledge of x-ray free electron lasers’ (XFELs) pulse characteristics delivered to a sample is crucial for ensuring high-quality x-rays for scientific experiments. XFELs’ self-amplified spontaneous emission process causes spatial and spectral variations in x-ray pulses entering a sample, which leads to measurement uncertainties for experiments relying on multiple XFEL pulses. Accurate in-situ measurements of x-ray wavefront and energy spectrum incident upon a sample poses challenges. Here we address this by developing a virtual diagnostics framework using an artificial neural network (ANN) to predict x-ray photon beam properties from electron beam properties. We recorded XFEL electron parameters while adjusting the accelerator’s configurations and measured the resulting x-ray wavefront and energy spectrum shot-to-shot. Training the ANN with this data enables effective prediction of single-shot or average x-ray beam output based on XFEL undulator and electron parameters. This demonstrates the potential of utilizing ANNs for virtual diagnostics linking XFEL electron and photon beam properties.

47 OTHER INSTRUMENTATION↗
NASA NTRS2000

A Flight Training Simulator for Instructing the Helicopter Autorotation Maneuver (Enhanced Version)

Autorotation is a maneuver that permits a safe helicopter landing when the engine loses power. A catastrophe may occur if the pilot's control inputs are incorrect, insufficient, excessive, or poorly timed. Due to the danger involved, full-touchdown autorotations are very rarely practiced. Because in-flight autorotation training is risky, time-consuming, and expensive, the objective of the project was to develop the first helicopter flight simulator expressly designed to train students in this critical maneuver. A central feature of the project was the inclusion of an enhanced version of the Pilot-Rotorcraft Intelligent Symbology Management Simulator (PRISMS), a virtual-reality system developed by Anacapa Sciences and Thought Wave. A task analysis was performed to identify the procedural steps in the autorotation, to inventory the information needed to support student task performance, to identify typical errors, and to structure the simulator's practice environment. The system provides immediate knowledge of results, extensive practice of perceptual-motor skills, part-task training, and augmented cueing in a realistic cockpit environment. Additional work, described in this report, extended the capabilities of the simulator in three areas: 1. Incorporation of visual training aids to assist the student in learning the proper appearance of the visual scene when the maneuver is being properly performed; 2. Introduction of the requirement to land at a particular spot, as opposed to the wide, flat open field initially used, and development of appropriate metrics of success; and 3. Inclusion of wind speed and wind direction settings (and random variability settings) to add a more realistic challenge in "hitting the spot."

Rogers, Steven P.↗
NASA NTRS1994

Virtual reality as a human factors design analysis tool: Macro-ergonomic application validation and assessment of the Space Station Freedom payload control area

A virtual reality (VR) Applications Program has been under development at MSFC since 1989. Its objectives are to develop, assess, validate, and utilize VR in hardware development, operations development and support, missions operations training, and science training. A variety of activities are under way within many of these areas. One ongoing macro-ergonomic application of VR relates to the design of the Space Station Freedom Payload Control Area (PCA), the control room from which onboard payload operations are managed. Several preliminary conceptual PCA layouts have been developed and modeled in VR. Various managers and potential end users have virtually 'entered' these rooms and provided valuable feedback. Before VR can be used with confidence in a particular application, it must be validated, or calibrated, for that class of applications. Two associated validation studies for macro-ergonomic applications are under way to help characterize possible distortions of filtering of relevant perceptions in a virtual world. In both studies, existing control rooms and their 'virtual counterparts will be empirically compared using distance and heading estimations to objects and subjective assessments. Approaches and findings of the PCA activities and details of the studies are presented.

Hale, Joseph P.↗
DOE OSTI2023

Adaptively Learned Modeling for a Digital Twin of Hydropower Turbines with Application to a Pilot Testing System

In the development of a digital twin (DT) for hydropower turbines, dynamic modeling of the system (e.g., penstock, turbine, speed control) is crucial, along with all the necessary data interface, virtualization, and dashboard designs. Since the DT must mimic the actual dynamics of the hydropower turbine accurately, adaptive learning is required to train these dynamic models online so that the models in the DT can effectively follow the representation of the actual hydropower turbine dynamics accurately and reliably. This study presents an adaptive learning method for obtaining the hydropower turbine models for DT development of hydropower systems using the recursive least squares algorithm. To simplify the formulation, the hydropower turbine under consideration was assumed to operate near a fixed operating point, where the system dynamics can be well represented by a set of linear differential equations with constant parameters. In this context, the well-known six-coefficient model for the Francis turbine was formulated as the starting point to obtain input and output models for the turbine. Then, an adaptive learning mechanism was developed to learn model parameters using real-time data from a hydropower turbine testing system. This led to semi-physical modeling, in which first principles and data-driven modeling are integrated to produce dynamic models for DT development. Applications to a pilot system at the Norwegian University of Science and Technology (NTNU) were made, and the models learned adaptively using the data collected from the university’s pilot system. Desired modeling and validation results were obtained.

13 HYDRO ENERGY↗
NASA NTRS2001

Virtual reality robotic telesurgery simulations using MEMICA haptic system

The authors conceived a haptic mechanism called MEMICA (Remote Mechanical Mirroring using Controlled stiffness and Actuators) that can enable the design of high dexterity, rapid response, and large workspace haptic system. The development of a novel MEMICA gloves and virtual reality models are being explored to allow simulation of telesurgery and other applications. The MEMICA gloves are being designed to provide intuitive mirroring of the conditions at a virtual site where a robot simulates the presence of a human operator. The key components of MEMICA are miniature electrically controlled stiffness (ECS) elements and electrically controlled force and stiffness (ECFS) actuators that are based on the use of Electro-Rheological Fluids (ERF. In this paper the design of the MEMICA system and initial experimental results are presented.

Haptic interfaces↗
NASA NTRS2001

Space Station Human Factors: Designing a Human-Robot Interface

The experiments described in this paper are part of a larger joint MIT/NASA research effort and focus on the development of a methodology for designing and evaluating integrated interfaces for highly dexterous and multifunctional telerobot. Specifically, a telerobotic workstation is being designed for an Extravehicular Activity (EVA) anthropomorphic space station telerobot called Robonaut. Previous researchers have designed telerobotic workstations based upon performance of discrete subsets of tasks (for example, peg-in-hole, tracking, etc.) without regard for transitions that operators go through between tasks performed sequentially in the context of larger integrated tasks. The experiments presented here took an integrated approach to describing teleoperator performance and assessed how subjects operating a full-immersion telerobot perform during fine position and gross position tasks. In addition, a Robonaut simulation was also developed as part of this research effort, and experimentally tested against Robonaut itself to determine its utility. Results show that subject performance of teleoperated tasks using both Robonaut and the simulation are virtually identical, with no significant difference between the two. These results indicate that the simulation can be utilized as both a Robonaut training tool, and as a powerful design platform for telepresence displays and aids.

Rochlis, Jennifer L.↗
NASA NTRS2010

Frequency Stabilization of DFB Laser Diodes at 1572 nm for Spaceborne Lidar Measurements of CO2

We report a fiber-based, pulsed laser seeder system that rapidly switches among 6 wavelengths across atmospheric carbon dioxide (CO2) absorption line near 1572.3 nm for measurements of global CO2 mixing ratios to 1-ppmv precision. One master DFB laser diode has been frequency-locked to the CO2 line center using a frequency modulation technique, suppressing its peak-to-peak frequency drifts to 0.3 MHz at 0.8 sec averaging time over 72 hours. Four online DFB laser diodes have been offset-locked to the master laser using phase locked loops, with virtually the same sub-MHz absolute accuracy. The 6 lasers were externally modulated and then combined to produce the measurement pulse train.

Numata, Kenji↗
DOE OSTI2025

Exploring the Use of Large Immersive Display Systems in the Nuclear Industry

Large immersive display systems play a critical role in the nuclear industry by enabling advanced training, design reviews, scientific visualization, and safety simulations. These systems, such as CAVE and powerwalls, allow engineers and operators to interact with virtual nuclear environments in real-time, providing a deeper understanding of complex systems. Their ability to simulate real-world scenarios for testing and optimization in a safe, controlled environment ensures that operators and engineers can refine process, enhance safety protocols, and troubleshoot complex challenges. This article outlines key lessons learned from deploying these systems, practical insights into their applications, and considerations for future improvements, aiming to guide their broader adoption and effective use in the nuclear industry.

99 - GENERAL AND MISCELLANEOUS↗
NASA NTRS1995

Applied Virtual Reality Research and Applications at NASA/Marshall Space Flight Center

A Virtual Reality (VR) applications program has been under development at NASA/Marshall Space Flight Center (MSFC) since 1989. The objectives of the MSFC VR Applications Program are to develop, assess, validate, and utilize VR in hardware development, operations development and support, mission operations training and science training. Before this technology can be utilized with confidence in these applications, it must be validated for each particular class of application. That is, the precision and reliability with which it maps onto real settings and scenarios, representative of a class, must be calculated and assessed. The approach of the MSFC VR Applications Program is to develop and validate appropriate virtual environments and associated object kinematic and behavior attributes for specific classes of applications. These application-specific environments and associated simulations will be validated, where possible, through empirical comparisons with existing, accepted tools and methodologies. These validated VR analytical tools will then be available for use in the design and development of space systems and operations and in training and mission support systems. Specific validation studies for selected classes of applications have been completed or are currently underway. These include macro-ergonomic "control-room class" design analysis, Spacelab stowage reconfiguration training, a full-body micro-gravity functional reach simulator, and a gross anatomy teaching simulator. This paper describes the MSFC VR Applications Program and the validation studies.

Hale, Joseph P.↗
NASA NTRS1991

Human factors issues for interstellar spacecraft

Developments in research on space human factors are reviewed in the context of a self-sustaining interstellar spacecraft based on the notion of traveling space settlements. Assumptions about interstellar travel are set forth addressing costs, mission durations, and the need for multigenerational space colonies. The model of human motivation by Maslow (1970) is examined and directly related to the design of space habitat architecture. Human-factors technology issues encompass the human-machine interface, crew selection and training, and the development of spaceship infrastructure during transtellar flight. A scenario for feasible instellar travel is based on a speed of 0.5c, a timeframe of about 100 yr, and an expandable multigenerational crew of about 100 members. Crew training is identified as a critical human-factors issue requiring the development of perceptual and cognitive aids such as expert systems and virtual reality.

Cohen, Marc M.↗
NASA NTRS2017

The NASA Augmented/Virtual Reality Lab: The State of the Art at KSC

The NASA Augmented Virtual Reality (AVR) Lab at Kennedy Space Center is dedicated to the investigation of Augmented Reality (AR) and Virtual Reality (VR) technologies, with the goal of determining potential uses of these technologies as human-computer interaction (HCI) devices in an aerospace engineering context. Begun in 2012, the AVR Lab has concentrated on commercially available AR and VR devices that are gaining in popularity and use in a number of fields such as gaming, training, and telepresence. We are working with such devices as the Microsoft Kinect, the Oculus Rift, the Leap Motion, the HTC Vive, motion capture systems, and the Microsoft Hololens. The focus of our work has been on human interaction with the virtual environment, which in turn acts as a communications bridge to remote physical devices and environments which the operator cannot or should not control or experience directly. Particularly in reference to dealing with spacecraft and the oftentimes hazardous environments they inhabit, it is our hope that AR and VR technologies can be utilized to increase human safety and mission success by physically removing humans from those hazardous environments while virtually putting them right in the middle of those environments.

Little, William↗