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Results for “Predictive control”

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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Demonstrating electromagnetic control of free-surface, liquid-metal flows relevant to fusion reactors

Plasma-facing components (PFC's) made from solid materials may not be able to withstand the large heat and particle fluxes that will be produced within next-generation fusion reactors. To address the shortcomings of solid PFC's, a variety of liquid-metal (LM) PFC concepts have been proposed. Many of the suggested LM-PFC designs rely on electromagnetic restraint (Lorentz force) to keep free-surface, liquid-metal flows adhered to the interior surfaces of a fusion reactor. However, there is very little, if any, experimental data demonstrating that free-surface, LM-PFC's can actually be electromagnetically controlled. Therefore, in this study, electrical currents were injected into a free-surface liquid-metal that was flowing through a uniform magnetic field. The resultant Lorentz force generated within the liquid-metal affected the velocity and depth of the flow in a controllable manner that closely matched theoretical predictions. These results show the promise of electromagnetic control for LM-PFC's and suggest that electromagnetic control could be further developed to adjust liquid-metal nozzle output, prevent splashing within a tokamak, and alter heat transfer properties for a wide-range of liquid-metal systems.

Plasma-Facing Component↗
NASA NTRS1982

Shuttle entry performance and stability and control derivatives extraction from flight measurement data

Flight data taken from three Shuttle Space Transportation System flights (STS-1, 2, and 3) during entry are analyzed to determine the shuttle performance and aerodynamic characteristics. Correlations of the performance coefficients and the stability and control derivatives with preflight predictions are presented over the hypersonic speed range from Mach 2 to 25. In addition, an evaluation of the effectiveness of the onboard Reaction Control System (RCS) is given and an effort is made to independently quantify the combined impingement and flow-field interaction effects on the spacecraft rolling moment. Comparisons of stability and control derivatives extracted for the same flight conditions, but using data from different onboard sensors are also made. Results obtained using the same flight data, but different computer software are also shown.

Compton, H. R.↗
DOE OSTI2024

PIP-II Beam Current Monitor Fault Case & Beam Position Monitor Linearity Studies in CST Studio

The use of non-invasive sensors & systems to measure particle beam characteristics is a crucial part of modern accelerator control systems. As such, simulations predicting the behavior of these sensors are essential for guiding beamline control system design. This poster details the results returned by two beam sensor models created using CST Studio software: the signal linearity of an elliptical beam position monitor (BPM), and the fault cases of an AC current transformer (ACCT) beam current monitor (BCM).

Rouzky, Adam↗
NASA NTRS1987

Recent developments in the experimental identification of the dynamics of a highly flexible grid

Control effectiveness tests of reaction wheel actuators attached to a highly flexible grid are reported. Analytic determination of actuator control effectiveness is accomplished with finite-element modeling. Experimental determination is done with a least-square parameter identification algorithm that identifies the control coefficients of the second-order difference equation model of each vibration mode. The algorithm assumes a model with frequency and damping predetermined from free-decay tests for each mode. Accounting for the difference in forced and resonant frequency was necessary to produce control effectiveness estimates that are in reasonable agreement with the analytic predictions. The average error for control effectiveness coefficients greater than 5/sq sec was 6.384 percent.

Montgomery, Raymond C.↗
NASA NTRS2002

Flywheel Magnetic Suspension Developments

The paper provides an overview of many areas of the flywheel magnetic suspension (MS) R&D being performed at the Texas A&M Vibration Control and Electromechanics Lab (TAMU-VCEL). This includes system response prediction, actuator optimization and redundancy, controller realizations and stages, sensor enhancements and backup bearing reliability.

Palazzolo, Alan↗
NASA NTRS1995

Sensor Fusion in Telerobotic Task Controls

Model-based telerobotic task control and automation is typically limited to motion control of robot arms in free space, and contact events under predictable conditions. A display and control method- ology is described for combining different multidimensional sensor data to guide the performance of telerobotic contact or near-contact tasks successfully in manual or supervised automatic modes of control.

telerobotics robotic task controllers sensor fusio↗
DOE OSTI2023

Physics Basis, Optimization, and Control for Integrated 3D Edge Long-pulse Tokamak Scenarios

The aim of this project with international collaborations (PI: J.-K. Park of Princeton Plasma Physics Laboratory) is to develop a unified physics basis and predictive capability for the control of edge-localized modes (ELMs) with optimized non-axisymmetric (3D) fields, by leveraging the unique research capabilities of international KSTAR tokamak in Korea. At the University of California, Irvine, we use a fusion simulation code GTC to study the effects of the 3D magnetic fields (including both magnetic islands and stochastic magnetic field lines) on microturbulence. We focus on the effects of 3D equilibrium on turbulent and neoclassical transport that leads to ELM suppression. During the project period, the UCI team of this collaboration has made significant progress in understanding turbulent transport in 3D geometry including both tokamaks with RMP and stellarators. Four UCI postdoctoral researchers, Drs. Javier Nicolau, Gyungjin Choi, Pengfei Liu, and Xishuo Wei were partially supported by this project and collaborating with the entire project team. We have published 4 journal papers and gave several invited talks. This project advance physics understand of 3D effects on microturbulence, specially effects of magnetic islands. It will contribute to the DOE SciDAC ISEP project in the area of GTC development for general 3D geometry capability, rigorous verification and validation, and readiness for the emerging exascale computing. Through collaborations with computational scientists, the project helps to advance high performance computing in the area of GPU acceleration, linear solver, and data management.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRSDate not supplied

Normative Baseline Oculomotor Performance

Future missions to the moon or Mars will require the crew to monitor and assess their health and performance more autonomously, necessitating approaches that are easily useable and interpretable by non-clinicians. The eye-movement-based performance metrics (oculometrics) obtained from NASA-patented technology developed at the Visuomotor Control Laboratory can reliably detect and discriminate the source of mild neural impairment relative to an individual’s baseline visual and sensorimotor performance and can predict performance in manual control tasks. This study aims to develop a database of normative performance that can be used to enable the detection of impairment without a within-subject baseline and to facilitate power analyses for the design of future studies.

eye movements↗
NASA NTRS1997

Dynamic analysis of heart rate may predict subsequent ventricular tachycardia after myocardial infarction

Dynamics analysis of RR interval behavior and traditional measures of heart rate variability were compared between postinfarction patients with and without vulnerability to ventricular tachyarrhythmias in a case-control study. Short-term fractal correlation of heart rate dynamics was better than traditional measures of heart rate variability in differentiating patients with and without life-threatening arrhythmias.

NASA Discipline Cardiopulmonary↗
DOE OSTI2023

Effects of Substance Use and Antisocial Personality on Neuroimaging-Based Machine Learning Prediction of Schizophrenia

Abstract Background and hypothesis Neuroimaging-based machine learning (ML) algorithms have the potential to aid the clinical diagnosis of schizophrenia. However, literature on the effect of prevalent comorbidities such as substance use disorder (SUD) and antisocial personality (ASPD) on these models’ performance has remained unexplored. We investigated whether the presence of SUD or ASPD affects the performance of neuroimaging-based ML models trained to discern patients with schizophrenia (SCH) from controls. Study design We trained an ML model on structural MRI data from public datasets to distinguish between SCH and controls (SCH = 347, controls = 341). We then investigated the model’s performance in two independent samples of individuals undergoing forensic psychiatric examination: sample 1 was used for sensitivity analysis to discern ASPD (N = 52) from SCH (N = 66), and sample 2 was used for specificity analysis to discern ASPD (N = 26) from controls (N = 25). Both samples included individuals with SUD. Study results In sample 1, 94.4% of SCH with comorbid ASPD and SUD were classified as SCH, followed by patients with SCH + SUD (78.8% classified as SCH) and patients with SCH (60.0% classified as SCH). The model failed to discern SCH without comorbidities from ASPD + SUD (AUC = 0.562, 95%CI = 0.400–0.723). In sample 2, the model’s specificity to predict controls was 84.0%. In both samples, about half of the ASPD + SUD were misclassified as SCH. Data-driven functional characterization revealed associations between the classification as SCH and cognition-related brain regions. Conclusion Altogether, ASPD and SUD appear to have effects on ML prediction performance, which potentially results from converging cognition-related brain abnormalities between SCH, ASPD, and SUD.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1998

Flight Stability and Control and Performance Results from the Linear Aerospike SR-71 Experiment (LASRE)

The Linear Aerospike SR-71 Experiment (LASRE) is presently being conducted to test a 20-percent-scale version of the Linear Aerospike rocket engine. This rocket engine has been chosen to power the X-33 Single Stage to Orbit Technology Demonstrator Vehicle. The rocket engine was integrated into a lifting body configuration and mounted to the upper surface of an SR-71 aircraft. This paper presents stability and control results and performance results from the envelope expansion flight tests of the LASRE configuration up to Mach 1.8 and compares the results with wind tunnel predictions. Longitudinal stability and elevator control effectiveness were well-predicted from wind tunnel tests. Zero-lift pitching moment was mispredicted transonically. Directional stability, dihedral stability, and rudder effectiveness were overpredicted. The SR-71 handling qualities were never significantly impacted as a result of the missed predictions. Performance results confirmed the large amount of wind-tunnel-predicted transonic drag for the LASRE configuration. This drag increase made the performance of the vehicle so poor that acceleration through transonic Mach numbers could not be achieved on a hot day without depleting the available fuel.

Moes, Timothy R.↗
NASA NTRSDate not supplied

Application of the Concepts of Load State, Load Space, and Output Space to Strain-Gage Balances

The concepts of load state, load space, and output space are used to describe elements of the development of a load prediction process for a six–component strain–gage balance. The use of these terms adds clarity during the selection of the independent and dependent variables for the development of the load prediction process. First, the control volume model of a strain–gage balance is reviewed as it helps better understand the role of loads, outputs, and state variables during the load prediction. Then, the description of the absolute load datum in both the load space and the output space is discussed. It is concluded that the use of the difference between a raw output and the natural zero of a balance gage has a key advantage for the definition of the output space. In that case, the origin of the output space will also describe the absolute load datum of the balance. Finally, details of the application of the concepts of load state, load space, and output space to two commonly used balance load prediction methods are discussed.

strain-gage balance↗
DOE OSTI2020

Advancing Fusion with Machine Learning Research Needs Workshop Report

Abstract Machine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and prediction, and autonomous vehicle control. Data-driven machine learning methods have also been applied to fusion energy research for over 2 decades, including significant advances in the areas of disruption prediction, surrogate model generation, and experimental planning. The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these computational approaches to extract scientific knowledge and bridge gaps between theoretical models and practical implementations. Large-scale commercial success of various ML/AI applications in recent years, including robotics, industrial processes, online image recognition, financial system prediction, and autonomous vehicles, have further demonstrated the potential for data-driven methods to produce dramatic transformations in many fields. These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government and around the world. The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies and approaches for applying ML/AI methods to fusion energy research. This paper describes the results of a joint FES/ASCR DOE-sponsored Research Needs Workshop on Advancing Fusion with Machine Learning, held April 30–May 2, 2019, in Gaithersburg, MD (full report available at https://science.osti.gov/-/media/fes/pdf/workshop-reports/FES_ASCR_Machine_Learning_Report.pdf ). The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO’s) with high potential for advancing fusion energy. In addition to the PRO topics themselves, the workshop identified research guidelines to maximize the effectiveness of ML/AI methods in fusion energy science, which include focusing on uncertainty quantification, methods for quantifying regions of validity of models and algorithms, and applying highly integrated teams of ML/AI mathematicians, computer scientists, and fusion energy scientists with domain expertise in the relevant areas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Effects of input gradient regularization on neural networks time-series forecasting of thermal power systems

This study proposes using neural networks, specifically gated recurrent unit (GRU), long-short-term memory (LSTM), and transformer networks, to improve control strategies in a 450 MW coal-fired power plant. However, neural networks face issues of becoming overly dependent on just a few variables to make predictions, which negatively impacts control decisions that rely on the model to determine the value of all manipulated variables. The paper introduces regularization techniques, including noise injection and input gradient regularization, during the training phase. Here, the work presents novel contributions in adapting neural networks to control industrial systems and applying regularization techniques from computer vision to industrial process control. Results demonstrate the effectiveness of input gradient regularization in reducing model dependence on subsets of variables, emphasizing the balance between fidelity and controllability. Further exploration is recommended, including the development of recurrent transformers, closed-loop control testing, and a sensitivity analysis on computer models to provide further insight.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2013

Comparison of Mars Science Laboratory Reaction Control System Jet Computations With Flow Visualization and Velocimetry

Numerical predictions of the Mars Science Laboratory reaction control system jets interacting with a Mach 10 hypersonic flow are compared to experimental nitric oxide planar laser-induced fluorescence data. The steady Reynolds Averaged Navier Stokes equations using the Baldwin-Barth one-equation turbulence model were solved using the OVERFLOW code. The experimental fluorescence data used for comparison consists of qualitative two-dimensional visualization images, qualitative reconstructed three-dimensional flow structures, and quantitative two-dimensional distributions of streamwise velocity. Through modeling of the fluorescence signal equation, computational flow images were produced and directly compared to the qualitative fluorescence data.

Bathel, Brett F.↗
NASA NTRS1994

Temperature prediction of space flight experiments by computer thermal analysis

Life sciences experiments are especially sensitive to temperature. A small temperature difference between otherwise identical samples can cause various differences in biological reaction rates. Knowledge of experimental temperatures and temperature histories help to distinguish the effects of microgravity and temperature on spaceflight experiments compared to ground based studies, and allow appropriate controls and sensitivity tests. Up to the present time, the Orbiter (Space Shuttle) has not generally provided temperature measurement instrumentation inside ambient lockers located in the Mid-deck of the Orbiter, or inside similar facilities such as Spacehab and Spacelab, but many pieces of hardware do have temperature recording capability. Most of these temperatures, however, have only been roughly measured or estimated. Such reported experimental temperatures, while accurate within a range of several degrees Celsius, are of limited utility to biological researchers. The temperature controlled lockers used in spaceflight, such as Commerical-Refrigeration Incubation Modules (C-R/IMs), severely reduce the mass and volume available for test samples and do not necessarily provide uniform thermal environments. While these test carriers avoid some of the experimental temperature variations of the ambient lockers, the number of samples which can be accommodated in these temperature controlled units is limited. In the present work, improved models of thermal prediction and control were sought. Temperatures are predicted by thermal analysis software using empirical temperatures recorded during STS-57. These temperatures are compared to data recorded throughout the mission using Ambient Temperature Recorders (ATRs) located within several payload lockers. Additional test cases are undertaken using controlled ground experiments to more precisely determine the reliability of the thermal model. The approach presented should increase the utility of various spaceflight carriers in the support of biological and material science research and ground control studies done in preparation for flight.

Birdsong, M. B.↗
NASA NTRS1983

Stability and control over the supersonic and hypersonic speed range

The performance and aerodynamic characteristics of the Space Shuttle Columbia are analyzed over the speed range from Mach 2 to 26 using flight data taken from the first five Space Transportation System flights. These data are used to reconstruct the entry trajectory, calculate vehicle performance, and estimate lateral stability and control derivatives including those assocated with the onboard Reaction Control System. The trajectory reconstruction process is discussed in its relationship to the determination of the vehicle flight characteristics. Vehicle performance results are presented which show that lift and drag were generally overpredicted by 3 percent and that the life-to-drag ratio was underpredicted by 1 percent. Anomalies in pitching-moment trim characteristics are shown and noted to be due to real-gas and Mach-number effects. Lateral stability and control derivatives estimated using programmed test input maneuvers are corrected with preflight predictions and are usually within the uncertainties associated with the predictions. The lateral reaction-control system effectiveness is evaluated.

Compton, H. R.↗