Search NASA⌕ Search

SEARCH · Search NASA

Results for “operator 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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

CloudSat Anomaly and Return to the A-Train: Lessons Learned for Satellite Constellations

In April 2011, CloudSat suffered a severe battery anomaly, leaving the space-craft in emergency mode without the ability to command or maneuver the spacecraft. Before the team was able to recover spacecraft operability, CloudSat passed close to the Aqua satellite in the A-Train and then exited the A-Train. A new mode of operations, termed Daylight Only Operations (DO-Op) mode was developed to enable CloudSat to resume science operations in an orbit under the A-Train by November 2011, and in July 2012 CloudSat re-entered the A-Train. This paper describes challenges and lessons-learned during the anomaly, the exit from the A-Train and the return to the A-Train. These lessons-learned may ap-ply to other current and future satellite constellations in Earth orbit.

formation-flying↗
NASA NTRSDate not supplied

Sensorimotor Countermeasures

Exploration class missions will include multiple transitions between gravitational environments, sometimes after long periods in microgravity, which will impact the neurovestibular system and sensorimotor capabilities. New countermeasures and assessment tools are needed to enhance preflight disorientation training, maintain inflight physical performance, and accelerate recovery following transitions between gravity environments so that crew are enabled to perform critical exploration mission tasks. The Sensorimotor Countermeasures capability area encompasses three projects. 1) The Upright Proprioception Retention via Inflight Training and Evaluation (UPRITE) system is being developed as an in-flight countermeasure that will mitigate the degradation of balance control mechanisms, which will improve post-flight postural stability. The development of such a countermeasure is not simply a matter of adapting a ground-based training program for spaceflight. The way that we control balance in a gravitational environment cannot be duplicated in 0g. Therefore, the UPRITE system challenges proprioception and tactile function using a 0g configuration. The steps to develop the countermeasure have been broken into seven phases: training type, controllable board factors, protocol development, 0g hardware test, training efficacy, ISS hardware demonstration, and countermeasure verification. 2) Unobtrusive Monitoring Tools and Operational Assessments (aka Head/Body Assessments) are being developed to quantify crew member sensorimotor adaptation following gravitational transitions. Three areas are needed in this development 1) explore, develop, and validate unobtrusive monitoring tools, 2) define sensorimotor performance metrics, and 3) explore capabilities to enhance sensorimotor assessment tasks for operational use and validate assessment tasks via high-fidelity analogs. 3) The Spatial Disorientation Trainer is being developed as a portable training capability to simulate the performance of landing and recovery type tasks while experiencing vertigo due to post-flight vestibular alterations. These simulations can be used 1) across research studies investigating the impacts of vestibular disruption on operational performance/assessments, 2) to train astronauts for upcoming spaceflight missions, and 3) to educate space medicine and operational personnel prior to providing post-flight support.

Scott Jonathan Wood↗
DOE OSTI2025

RLGBS: Reinforcement Learning-Guided Beam Search for process optimization in a paper machine dryer section

Paper drying is responsible for over two-thirds of energy consumption in the U.S. pulp and paper industry, presenting significant potential for energy savings through optimization of process parameters. Current approaches often assume fixed operating conditions, neglecting dynamic ambient and process variations that limit achievable savings and real-world applicability. To this end, we develop a physics-based simulation environment for a paper machine dryer section and propose a reinforcement learning (RL) framework to minimize overall energy consumption by optimizing drying process parameters under diverse operating conditions. To mitigate overdrying and numerical instabilities caused by suboptimal local RL actions, we introduce Reinforcement Learning-Guided Beam Search (RLGBS), which explores multiple action sequences in parallel using beam search. Instead of making step-by-step decisions, RLGBS prioritizes solutions based on cumulative probability, reducing the impact of individual suboptimal actions. Experiments demonstrate that RLGBS achieves consistent energy savings under unseen operating conditions not encountered during training, outperforming conventional RL methods. While validated in drying optimization, this framework is broadly applicable to other RL-based industrial process control problems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

One-shot learning for solution operators of partial differential equations

Learning and solving governing equations of a physical system, represented by partial differential equations (PDEs), from data is a central challenge in many areas of science and engineering. Traditional numerical methods can be computationally expensive for complex systems and require complete governing equations. Existing data-driven machine learning methods require large datasets to learn a surrogate solution operator, which could be impractical. Here, we propose a solution operator learning method that requires only one PDE solution, i.e., one-shot learning, along with suitable initial and boundary conditions. Leveraging the locality of derivatives, we define a local solution operator in small local domains, train it using a neural network, and use it to predict solutions of new input functions via mesh-based fixed-point iteration or meshfree neural-network based approaches. We test our method on various PDEs, complex geometries, and a practical spatial infection spread application, demonstrating its effectiveness and generalization capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Tokamak edge localized mode onset prediction with deep neural network and pedestal turbulence

Abstract A neural network, BES-ELMnet, predicting a quasi-periodic disruptive eruption of the plasma energy and particles known as edge localized mode (ELM) onset is developed with observed pedestal turbulence from the beam emission spectroscopy system in DIII-D. BES-ELMnet has convolutional and fully-connected layers, taking two-dimensional plasma fluctuations with a temporal window of size 128 µ s and generating a scalar output which can be interpreted as a probability of the upcoming ELM onset. As approximately labeled inter-ELM broadband ( 15 kHz ⩽ f ⩽ 150 kHz ) fluctuations are given to the network, BES-ELMnet learns by itself ELM-related precursors arising before the onsets through supervised learning scheme. BES-ELMnet achieves the gradually increasing ELM onset probabilities between two consecutive ELMs during the inter-ELM phases and can forecast the first ELM onsets which occur after the high confinement mode transition. We further investigate the network generality in terms of the selected frequency band to ensure the use of BES-ELMnet for various operation regimes without changing the trained architecture. Therefore, our novel prediction method will enhance a proactive high confinement mode control of fusion-grade plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Spatiotemporal forecasting of the edge localized modes in tokamak plasmas using neural networks

Artificial intelligence techniques have been increasingly adopted by the plasma and fusion science to address problems like plasma reconstruction, surrogate modeling, and tokamak/stellarator optimization. A key focus in sustained fusion research is the prediction and mitigation of edge-localized-modes (ELMs), instabilities that occur in short, periodic bursts and can cause erosion to the tokamak vessel wall. Recent research has demonstrated the power of neural networks in approximating continuous functions. In this work, we build spatiotemporal forecasting models that can predict the onset of ELMs and their evolution at early stages. We leverage recent advances in generative modeling, sequence-to-sequence modeling, and Fourier neural operators to propose architectures and training strategies that can learn to forecast short to long term dynamics of the noisy signals due to ELMs. We benchmark the developed model against a state-of-the-art foundation model using the beam emission spectroscopy (BES) data that captures the plasma fluctuations due to ELMs over a 8 x 8 spatial grid. Our models demonstrate high accuracy, outperforming the baselines, in predicting the evolution of BES signals during ELM events. Furthermore, the developed models exhibit high accuracy in predicting the rapid rise and relaxation of the signals due to ELMs within 30–80 µs.

edge localized modes↗
DOE OSTI2023

Neutron (and other Particle) Transport at LANL: An Overview [Presentation]

For decades, Los Alamos National Laboratory has been at the forefront of neutron transport methods research and code development. One such code is PARTISN, the LANL parallel time-dependent discrete ordinate neutron transport code. In this presentation, we describe the various research efforts currently underway by the PARTISN and other code teams. Some examples of current research are a block automated mesh refinement scheme, the application of tensor trains to the discretized neutron transport equation, and GPU code porting. The block automated mesh refinement scheme uses cross section information to refine and coarsen the solution mesh to improve time to solution and reduce memory. The tensor train approach expresses discretized transport operators as tensor products of vectors and matrices to compress the size of linear systems being solved by transport codes. Rather than relying on matrix-free methods such as the transport sweep, we have access to an operator that can be inverted, reshaped, or manipulated algebraically. Finally, we describe how PARTISN is used, what problems we are looking to solve, and what the future holds for neutron transport at LANL. In addition to this, we briefly describe the various research efforts in other particle transport teams using both deterministic and Monte Carlo methods. In the presentation, we list possible opportunities for collaboration between the laboratory and faculty and students.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Resistive Wall Simulations with LAMDA

The prospect for a new downstream transport (DST) beam line for multipulse target testing (MPTL) has raised questions about the resistive-wall instability, which has been theoretically shown to couple between the multiple pulses in a pulse train. Recent upgrades to computer operating systems and the LAMDA beam dynamics code mandate that the code be revalidated before using to explore MPTL parameters. This note is a brief account of the revalidation of LAMDA for resistive wall problems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

PFAS Waste Management for Industrial, Water, and Wastewater Treatment Facilities

Per- and polyfluoroalkyl substances (PFAS), including perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), are widely used in industrial and consumer products due to their unique water and oil repelling properties. These slow-degrading and bio-accumulating compounds, often called "forever chemicals," are not typically removed by conventional industrial and municipal water/wastewater (W/WW) treatment. This tip of the month provides comprehensive strategies for managing PFAS-contaminated waste streams. Understanding the various types of PFAS waste streams is the first step in managing them. Primary PFAS waste includes contaminated process W/WW and solid materials directly from the production and processing of PFAS-containing materials. These might come from manufacturing facilities, firefighting training areas, or other industrial operations where PFAS compounds are used or were historically present. Secondary PFAS waste results from treatment and disposal mechanisms of primary PFAS waste streams, including spent activated carbon, used ion exchange resins, membrane reject streams, PFAS-laden backwash water, landfill leachate, incineration residuals, etc. TABLE 1 lists examples of the most common PFAS waste streams in different industrial facilities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1970

Flight control in the Apollo Program

Apollo Program flight control operations personnel premission planning and training, discussing presolution of launch problems and emergencies

Covington, J. O.↗
NASA NTRS1977

Assess 2: Spacelab simulation. Executive summary

An Airborne Science/Spacelab Experiments System Simulation (ASSESS II) mission, was conducted with the CV-990 airborne laboratory in May 1977. The project studied the full range of Spacelab-type activities including management interactions, experiment selection and funding, hardware development, payload integration and checkout, mission specialist and payload specialist selection and training, mission control center payload operations control center arrangements and interactions, real time interaction during flight between principal investigators and the flight crew, and retrieval of scientific flight data. ESA established an integration and coordination center for the ESA portion of the payload as planned for Spacelab. A strongly realistic Spacelab mission was conducted on the CV-990 aircraft. U.S. and ESA scientific experiments were integrated into a payload and flown over a 10 day period, with the payload flight crew fully-confined to represent a Spacelab mission. Specific conclusions for Spacelab planning are presented along with a brief explanation of each.

Source record↗
NASA NTRS1979

Automatic Data Processing Equipment (ADPE) acquisition plan for the medical sciences

An effective mechanism for meeting the SLSD/MSD data handling/processing requirements for Shuttle is discussed. The ability to meet these requirements depends upon the availability of a general purpose high speed digital computer system. This system is expected to implement those data base management and processing functions required across all SLSD/MSD programs during training, laboratory operations/analysis, simulations, mission operations, and post mission analysis/reporting.

Source record↗
NASA NTRS1981

Demonstration Advanced Avionics System (DAAS). Phase 1 report

An integrated avionics system which provides expanded functional capabilities that significantly enhance the utility and safety of general aviation at a cost commensurate with the general aviation market is discussed. Displays and control were designed so that the pilot can use the system after minimum training. Functional and hardware descriptions, operational evaluation and failure modes effects analysis are included.

Source record↗
NASA NTRS1986

Design and dynamic simulation of a fixed pitch 56 kW wind turbine drive train with a continuously variable transmission

The dynamic analysis of a horizontal axis fixed pitch wind turbine generator (WTG) rated at 56 kW is discussed. A mechanical Continuously Variable Transmission (CVT) was incorporated in the drive train to provide variable speed operation capability. One goal of the dynamic analysis was to determine if variable speed operation, by means of a mechanical CVT, is capable of capturing the transient power in the WTG/wind environment. Another goal was to determine the extent of power regulation possible with CVT operation.

Gallo, C.↗
NASA NTRS1987

Application of data to piloted simulators

The application of a further developed analytical model and JAWS data to a piloted simulator is addressed. The Ames simulator provides a facility for the development of piloting procedures, and for the selection of training scenarios. The system is operational with the new wind shear models and comprehensive data output. The use of these models with the simulator is dicussed in detail.

Bray, Richard S.↗
NASA NTRS1991

Neutral Buoyancy Portable Life Support System performance study

The Neutral Buoyancy Portable Life Support System (NBPSS) has been designed to support astronaut underwater training activities associated with EVA operations. The performance of competing NBPSS configurations has been analyzed on the basis of a modified 'Metabolic Man' program. NBPSS success is dependent on the development of novel cryogen supply tank and liquid-cooling garment vaporizer. Attention is given to mass and thermal balances and the evaluation results for the vent-loop ejector and heat-exchanger designs.

Chang, Chi-Min↗
NASA NTRS1992

Introduction to Space Station Freedom

NASA field centers and contractors are organized to develop 'work packages' for Space Station Freedom. Marshall Space Flight Center and Boeing are building the U.S. laboratory and habitation modules, nodes, and environmental control and life support system; Johnson Space Center and McDonnell Douglas are responsible for truss structure, data management, propulsion systems, thermal control, and communications and guidance; Lewis Research Center and Rocketdyne are developing the power system. The Canadian Space Agency (CSA) is contributing a Mobile Servicing Center, Special Dextrous Manipulator, and Mobile Servicing Center Maintenance Depot. The National Space Development Agency of Japan (NASDA) is contributing a Japanese Experiment Module (JEM), which includes a pressurized module, logistics module, and exposed experiment facility. The European Space Agency (ESA) is contributing the Columbus laboratory module. NASA ground facilities, now in various stages of development to support Space Station Freedom, include: Marshall Space Flight Center's Payload Operations Integration Center and Payload Training Complex (Alabama), Johnson Space Center's Space Station Control Center and Space Station Training Facility (Texas), Lewis Research Center's Power System Facility (Ohio), and Kennedy Space Center's Space Station Processing Facility (Florida). Budget appropriations impact the development of the Space Station. In Fiscal Year 1988, Congress appropriated only half of the funds that NASA requested for the space station program ($393 million vs. $767 million). In FY 89, NASA sought $967 million for the program, and Congress appropriated $900 million. NASA's FY 90 request was $2.05 billion compared to an appropriation of $1.75 billion; the FY 91 request was $2.45 billion, and the appropriation was $1.9 billion. After NASA restructured the Space Station Freedom program in response to directions from Congress, the agency's full budget request of $2.029 billion for Space Station Freedom in FY 92 was appropriated. For FY 93, NASA is seeking $2.25 billion for the program; the planned budget for FY 94 is $2.5 billion. Further alterations to the hardware configuration for Freedom would be a serious setback; NASA intends 'to stick with the current baseline' and continue planning for utilization.

Kohrs, Richard↗
NASA NTRS1994

Neural Network Classifies Teleoperation Data

Prototype artificial neural network, implemented in software, identifies phases of telemanipulator tasks in real time by analyzing feedback signals from force sensors on manipulator hand. Prototype is early, subsystem-level product of continuing effort to develop automated system that assists in training and supervising human control operator: provides symbolic feedback (e.g., warnings of impending collisions or evaluations of performance) to operator in real time during successive executions of same task. Also simplifies transition between teleoperation and autonomous modes of telerobotic system.

Fiorini, Paolo↗