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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A smart alarm for particle accelerator beamline operations

We present the initial results of a proof-of-concept 'smart alarm' for the Continuous Electron Beam Accelerator Facility injector beamline at Jefferson Lab. To minimize machine downtime and improve operational efficiency, an autonomous alarm system able to identify and diagnose unusual machine states is needed. Our approach leverages a trained neural network capable of alerting operators (a) when an anomalous condition exists in the beamline and (b) identifying the element setting that is the root cause. The tool is based on an inverse model that maps beamline readings (diagnostic readbacks) to settings (beamline attributes operators can modify). The model takes as input readings from the machine and computes machine settings which are compared to control setpoints. Instances where predictions differ from setpoints by a user-defined threshold are flagged as anomalous. Given data corresponding to 354 anomalous injector configurations, the model can narrow the root cause of an anomalous condition to three potential candidates with 94.6% accuracy. Furthermore, compared to the current method of identifying anomalous conditions which raises an alarm when machine parameters drift outside their normal tolerances, the data-driven model can identify 83% more anomalous conditions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

Ewald: an extended wide-angle Laue diffractometer for the second target station of the Spallation Neutron Source

Visualizing hydrogen atoms in biological materials is one of the biggest remaining challenges in biophysical analysis. While X-ray techniques have unrivaled capacity for high-throughput structure determination, neutron diffraction is uniquely sensitive to hydrogen atom positions in crystals of biological materials and can provide a more complete picture of the atomic and electronic structures of biological macromolecules. This information can be essential in providing predictive understanding and engineering control of key biological processes, for example, in catalysis, ligand binding and light harvesting, and to guide bioengineering of enzymes and drug design. One very common and large capability gap for all neutron atomic resolution single-crystal diffractometers is the weak flux of available neutron beams, which results in limited signal-to-noise ratios giving a requirement for sample volumes of at least 0.1 mm 3 . The ability to operate on crystals an order of magnitude smaller (0.01 mm 3 ) will open up new and more complex systems to studies with neutrons which will help in our understanding of enzyme mechanisms and enable us to improve drugs against multi resistant bacteria. With this is mind, an extended wide-angle Laue diffractometer, `Ewald', has been designed, which can collect data using crystal volumes below 0.01 mm 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2023

Vertical Structure and Ice Production Processes of Shallow Convective Postfrontal Clouds over the Southern Ocean in MARCUS. Part II: Modeling Study

Abstract Part I of this series presented a detailed overview of postfrontal mixed-phase clouds observed during the Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) field campaign. In Part II, we focus on a multiday (23–26 February 2018) case with the aim of understanding ice production as well as model sensitivity to ice process parameterizations using the Weather Research and Forecasting (WRF) Model. The control simulation with the Predicted Particle Properties (P3) microphysics scheme underestimates the ice content and overestimates the supercooled liquid water content, contrary to the bias common in global climate models. The simulations targeted at ice production processes show negligible sensitivity to cloud droplet number concentrations. Further, neither increasing ice nuclei particle (INP) concentrations to an unrealistic level nor adjusting it to MARCUS field estimations alone guarantees more ice production in the model. However, the simulated clouds are found to be highly sensitive to the implementation of immersion freezing, the thresholding of condensation/deposition freezing initiation, and the rime splintering process. By increasing immersion freezing of cloud droplets, relaxing thresholds for condensation/deposition freezing, or removing rime splintering thresholds, the model significantly improves its performance in producing ice. The relaxation of the immersion freezing temperature threshold to the observed cloud-top temperature suggests an in-cloud seeder–feeder mechanism. The results of this work call for an increase in observations of INP, especially over the remote Southern Ocean and at relatively high temperatures, and measurements of ice particle size distributions to better constrain ice nucleating processes in models.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems

The high complexity and multiscale nature of many engineered systems—such as those in nuclear power plants—make representing and forecasting their dynamic behavior challenging. Physics-based models can be overly complex and computationally intractable, whereas machine learning (ML) tools are often data-hungry and prone to unphysical solutions. This study proposes a knowledge-informed ML-aided hybrid residual modeling approach that offers accurate and efficient time series forecasting for the operation of dynamical engineered systems. Hybrid residual modeling entails a baseline solution from domain knowledge and known physics expressions about the system dynamics integrated with an ML model to capture undiscovered information from the mismatch (i.e., residuals) between true states from measurements and baseline-predicted outputs. This study further quantifies the ML model uncertainty to provide trustworthy solutions. Real-time operational data from thermal-hydraulic flow loops of the cryogenic moderator system in Oak Ridge National Laboratory’s Spallation Neutron Source facility were used to demonstrate the potential of knowledge-informed uncertainty-aware ML in real-world applications. The state variables of the cryogenic helium loop were modeled with (1) first principles–based system identification (sysID), (2) long short-term memory (LSTM) neural network, and (3) hybrid sysID (baseline) + LSTM (residual). The superior predictive capability of the sysID+LSTM model versus stand-alone sysID and LSTM is confirmed by average performance metrics and individual data points across different prediction horizons. By creating a robust representation of the underlying physical system, the widely applicable hybrid residual modeling approach will enable the future development of digital twins for performance prediction, prognostics, and operation control.

Zhao, Xingang↗
DOE OSTI2020

Boosting Energy Efficiency of Heterogeneous Connected Automated Vehicle (CAV) Fleets via Anticipative and Cooperative Vehicle Guidance

In 2017, the Department of Energy funded a team at Clemson University and Argonne National Laboratory to develop collaborative perception and anticipative/predictive vehicle guidance schemes for Connected and Automated Vehicles (CAVs) and to quantify the energy saving potential of this technology in large scale traffic microsimulations at different levels of technology penetration and also experimentally. The project goal was demonstrating up to a 10% energy saving potential from different aspects of the implementation with a focus on reducing unnecessary braking events by anticipatory speed and lane selection. This project introduced novel anticipative car following and lane selection schemes for Connected and Automated Vehicles (CAVs). Our control schemes benefited from prediction of human driver behavior, information exchange between CAVs, and sometimes from collaboration to save energy, reduce braking events, and harmonize traffic. The energy savings was first demonstrated by traffic micro-simulations and then via a novel Vehicle-In-the-Loop (VIL) experimental testbed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Advanced Materials & Manufacturing Technology (AMMT): Development of Additive Manufacturing Agnostic Process Parameter Procedure, 316H Stainless Steel Readiness Level Data Sets, and Machine Maintenance Plan

The University of California, Davis is involved in a project to deploy and enhance an artificial intelligence (AI) system for predicting and preventing plasma disruptions on the DIII D tokamak, under the funding from Department of Energy DE-SC0023500 (title: AI/Deep Learning FRNN Software for Prediction & Real-Time Control of DIII-D Plasma Control System (PCS)). The overarching goal is to demonstrate that real-time, AI-guided intervention can proactively modify the plasma state to avoid or mitigate disruptions—a critical challenge for the future of fusion energy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dust pollution in China affected by different spatial and temporal types of El Niño

Dust is an important aerosol affecting air quality in China in the winter and spring seasons. Dust in China is potentially influenced by the interannual climate variability associated with El Niño. Here, the impacts of El Niño with different temporal and spatial types on dust pollution in boreal winter and spring in China and the potential mechanisms are investigated using a state-of-the-art Earth system model (E3SMv1). We find that the eastern Pacific (EP) and central Pacific (CP) El Niño both increase wintertime dust concentrations by 5–50 µg m –3 over central-eastern China. Due to a stronger wind and lower relative humidity, which favor dust emissions near sources, and a strengthened northwesterly and reduced precipitation, which are conducive to dust transport, dust concentrations during the CP El Niño are 5–20 µg m –3 higher in northern China than during the EP El Niño, although the changes are mostly insignificant. El Niño with a short duration (SD) increases boreal winter dust concentrations by 20–100 µg m –3 over northern China relative to the climatological mean, while there is a decrease of 5–50 µg m –3 during the long-duration (LD) El Niño, which is also related to the El Niño-induced changes in atmospheric circulation, precipitation, and relative humidity. In the following spring season, all types of El Niño events enhance dust over northern China, but only the increase during the LD El Niño is statistically significant, suggesting that the weaker intensity but longer duration of the LD El Niño events can significantly affect spring dust in China. Our results contribute to the current knowledge of the influence of El Niño on dust pollution, which has profound implications for air pollution control and dust storm prediction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1972

Human factors aspects of air traffic control

An overview of human factors problems associated with the operation of present and future air traffic control systems is presented. A description is included of those activities and tasks performed by air traffic controllers at each operational position within the present system. Judgemental data obtained from controllers concerning psychological dimensions related to these tasks and activities are also presented. The analysis includes consideration of psychophysiological dimensions of human performance. The role of the human controller in present air traffic control systems and his predicted role in future systems is described, particularly as that role changes as the result of the system's evolution towards a more automated configuration. Special attention is directed towards problems of staffing, training, and system operation. A series of ten specific research and development projects are recommended and suggested work plans for their implementation are included.

Older, H. J.↗
NASA NTRS1972

The effect of alloy composition on the mechanism of stress-corrosion cracking of titanium alloys in aqueous environments

A detailed study was made of the relation between the size distribution of Ti3Al particles in a Ti-8Al alloy and the tensile properties measured in air and in saltwater. The size distribution of Ti3Al was varied by isothermal aging for various times at temperatures in the range 770 to 970 K (930 to 1290 F). The aging kinetics were found to be relatively slow. Quantitative measurements of the particle coarsening rate at 920 K (1200 F) showed good agreement with the predicted behavior for coarsening controlled by matrix diffusion, and suggested that the specific free energy of the Ti3Al alpha interface in negligible small. In all cases, the Ti3Al particles were sheared by the glide dislocations. It was concluded that there is a definite correlation between the presence of deformable Ti3Al particles and an alloy's susceptibility to aqueous stress corrosion cracking. Furthermore, the appearance of the surface slip lines and the dislocation substructure in deformed specimens suggest that the specific effect of the Ti3Al particles is to cause a nonhomogeneous planar slip character and an enhanced chemical potential of the slip bands.

Wood, R. A.↗
NASA NTRS1973

Structural technologies - Systems challenges and NASA thrusts.

Some significant areas of emphasis in the NASA airframes structures program are highlighted. The topics treated include automated analysis and design processes, building confidence in advanced composites, improving the technology base for future supersonic and hypersonic vehicles, validation of concepts for active control systems, development of predictive methods for aircraft loads and aeroelasticity, and generation of methodology to assure structural integrity as a part of the design process. An integrated long-range program for fatigue and fracture is recommended.

Brooks, G. W.↗
NASA NTRS1973

Developing structures technology for the day after tomorrow.

To prepare for new demands on aircraft structures, NASA has established a number of goals. These include automatic analysis and design, building confidence in advanced composites, improving the technology base for future supersonic and hypersonic vehicles, validating concepts for active controls, developing methods for predicting aircraft loads and aeroelasticity, and generating design methods for assuring structural integrity. Progress made in achieving these goals is discussed in detail.

Brooks, G. W.↗
NASA NTRS1974

A review of air transport noise

Flight vehicles are characterized according to their manner of operation and type of propulsion system, and their associated sources of noise are identified. Available noise reduction technology as it relates to engine cycle design and to power plant component design is summarized. Such components as exhaust jets, fans, propellers, rotors, airflow-surface interactions, and reciprocating engine exhausts are discussed, along with their noise reduction potentials. Significant aircraft noise reductions are noted to have been accomplished by the application of available technology in support of noise certification rules. Improved analytical prediction methods, and well controlled validation experiments supported by advanced design aeroacoustic facilities, are required as a basis for an effective integrated systems approach to aircraft noise control.

Hubbard, H. H.↗
NASA NTRS1978

Shuttle being tested at Marshall Center

Ground vibration tests of the space shuttle vehicle performed to evaluate the structural dynamics and their effect on the control system of the shuttle are described. Test results are used to verify the system design and mathematical models that predict how the shuttle's control system will react to the much more severe vibrations expected during launch and flight into orbit. The test configurations, the test facility, and the dynamic test suspension system are among the topics discussed.

Source record↗
NASA NTRS1980

Status of linear boundary-layer stability and the e to the nth method, with emphasis on swept-wing applications

The-state-of-the-art for the application of linear stability theory and the e to the nth power method for transition prediction and laminar flow control design are summarized, with analyses of previously published low disturbance, swept wing data presented. For any set of transition data with similar stream distrubance levels and spectra, the e to the nth power method for estimating the beginning of transition works reasonably well; however, the value of n can vary significantly, depending upon variations in disturbance field or receptivity. Where disturbance levels are high, the values of n are appreciably below the usual average value of 9 to 10 obtained for relatively low disturbance levels. It is recommended that the design of laminar flow control systems be based on conservative estimates of n and that, in considering the values of n obtained from different analytical approaches or investigations, the designer explore the various assumptions which entered into the analyses.

Hefner, J. N.↗