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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives

Smart buildings play a crucial role toward decarbonizing society, as globally buildings emit about one-third of greenhouse gases. In the last few years, machine learning has achieved a notable momentum that, if properly harnessed, may unleash its potential for advanced analytics and control of smart buildings, enabling the technique to scale up for supporting the decarbonization of the building sector. In this perspective, transfer learning aims to improve the performance of a target learner exploiting knowledge in related environments. The present work provides a comprehensive overview of transfer learning applications in smart buildings, classifying and analyzing 77 papers according to their applications, algorithms, and adopted metrics. The study identified four main application areas of transfer learning: (1) building load prediction, (2) occupancy detection and activity recognition, (3) building dynamics modeling, and (4) energy systems control. Furthermore, the review highlighted the role of deep learning in transfer learning applications that has been used in more than half of the analyzed studies. The paper also discusses how to integrate transfer learning in a smart building's ecosystem, identifying, for each application area, the research gaps and guidelines for future research directions.

Pinto, G↗
NASA NTRS1997

Robust Feedback Control of Flow Induced Structural Radiation of Sound

A significant component of the interior noise of aircraft and automobiles is a result of turbulent boundary layer excitation of the vehicular structure. In this work, active robust feedback control of the noise due to this non-predictable excitation is investigated. Both an analytical model and experimental investigations are used to determine the characteristics of the flow induced structural sound radiation problem. The problem is shown to be broadband in nature with large system uncertainties associated with the various operating conditions. Furthermore the delay associated with sound propagation is shown to restrict the use of microphone feedback. The state of the art control methodologies, IL synthesis and adaptive feedback control, are evaluated and shown to have limited success for solving this problem. A robust frequency domain controller design methodology is developed for the problem of sound radiated from turbulent flow driven plates. The control design methodology uses frequency domain sequential loop shaping techniques. System uncertainty, sound pressure level reduction performance, and actuator constraints are included in the design process. Using this design method, phase lag was added using non-minimum phase zeros such that the beneficial plant dynamics could be used. This general control approach has application to lightly damped vibration and sound radiation problems where there are high bandwidth control objectives requiring a low controller DC gain and controller order.

Heatwole, Craig M.↗
DOE OSTI2023

Environmental controls on observed spatial variability of soil pore water geochemistry in small headwater catchments underlain with permafrost

Abstract. Soil pore water (SPW) chemistry can vary substantially across multiple scales in Arctic permafrost landscapes. The magnitude of these variations and their relationship to scale are critical considerations for understanding current controls on geochemical cycling and for predicting future changes. These aspects are especially important for Arctic change modeling where accurate representation of sub-grid variability may be necessary to predict watershed-scale behaviors. Our research goal is to characterize intra- and inter-watershed soil water geochemical variations at two contrasting locations in the Seward Peninsula of Alaska, USA. We then attempt to identify the key factors controlling concentrations of important pore water solutes in these systems. The SPW geochemistry of 18 locations spanning two small Arctic catchments was examined for spatial variability and its dominant environmental controls. The primary environmental controls considered were vegetation, soil moisture and/or redox condition, water–soil interactions and hydrologic transport, and mineral solubility. The sampling locations varied in terms of vegetation type and canopy height, presence or absence of near-surface permafrost, soil moisture, and hillslope position. Vegetation was found to have a significant impact on SPW NO3- concentrations, associated with the localized presence of nitrogen-fixing alders and mineralization and nitrification of leaf litter from tall willow shrubs. The elevated NO3- concentrations were, however, frequently equipoised by increased microbial denitrification in regions with sufficient moisture to support it. Vegetation also had an observable impact on soil-moisture-sensitive constituents, but the effect was less significant. The redox conditions in both catchments were generally limited by Fe reduction, seemingly well-buffered by a cache of amorphous Fe hydroxides, with the most reducing conditions found at sampling locations with the highest soil moisture content. Non-redox-sensitive cations were affected by a wide variety of water–soil interactions that affect mineral solubility and transport. Identification of the dominant controls on current SPW hydrogeochemistry allows for qualitative prediction of future geochemical trends in small Arctic catchments that are likely to experience warming and permafrost thaw. As source areas for geochemical fluxes to the broader Arctic hydrologic system, geochemical processes occurring in these environments are particularly important to understand and predict with regards to such environmental changes.

Conroy, Nathan Alec (ORCID:0000000305973373)↗
DOE OSTI2025

Reinforcement Learning for In-Spill Optimization of the Mu2e Resonant Extraction: Compensating Non-Stationarity

We present design considerations and challenges for the fast machine learning component of a third-order resonant beam extraction regulation system being commissioned to deliver steady beam rates to the mu2e experiment at Fermilab. Dedicated quadrupoles drive the tune toward the 29/3 resonance each spill, extracting beam at kV multiwire septa. The overall Spill Regulation System consists of (1) a “slow” process using ~100-spill averages to adjust the base quad ramp infrequently, (2) a feedforward harmonic content compensator, and (3) the “fast” ML agent reacting during each ongoing spill with on-the-fly additive corrections to the sum of (1) and (2). We have demonstrated improved beam-rate steadying for a fast ML agent compared to a PID controller using a quasi-physical spill simulation, and demonstrated distillation of that simulation into a predictive surrogate model. Current work includes a data-and-training pipeline to generate data-aware surrogates with real-world dynamics, even as the dynamics shift unpredictably. The surrogates are to act as RL environments against which to train our fast ML control agents before deploying them on FPGA in the live system. Further current efforts focus on modeling and controlling beam loss around the storage ring, understanding additional available hardware inputs to the model, and the interplay of these with beam-steadying performance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1981

Investigations of stability and dynamic performances of switching regulators employing current-injected control

The stability and dynamic performances of a buck/boost regulator employing a current-injected control are examined. Small-signal models for the power state, the multi-loop error processor and the duty-cycle pulse-modulator are developed. The error-processor model which incorporates the current-injected loop, the dc loop and the compensation network permits evaluation of the effects of each individual control loop and their combined efforts toward shaping the performance characteristics of the closed-loop system. Comparisons are made between this modeling approach and earlier approaches. Some important yet subtle dissimilarities are discussed. This model predicts the constant-frequency 50 percent duty-cycle instability which is inherent to the current-injected control.

Lee, F. C.↗
NASA NTRS2024

Evaluation, Analysis, and Application of Internal Strain-Gage Balance Data

Experimental processes, analytical methods, and numerical algorithms are described that may be used to predict the forces and moments of an internal strain–gage balance during a wind tunnel test. First, the control volume model of a strain–gage balance and the concepts of load state, load space, and output space are introduced. These important abstractions provide a better understanding of fundamental characteristics of different balance load prediction approaches. Then, the description of strain–gage balance data and the definition of the primary bridge sensitivity are discussed. Afterwards, basic elements of the calibration of a typical six–component balance are reviewed. Two fundamentally different balance load prediction methods, the processing of check loads, and related topics are also discussed. Three real–world balance data examples are reviewed in great detail to illustrate typical analysis results for a variety of strain–gage balance designs. Finally, important observations are summarized and recommendations are provided. – Additional information and detailed mathematical derivations can be found in the appendices of the document. They include the following topics: balance terminology, definitions of important statistical metrics, balance axis system conventions, balance load transformations, the combined load diagram, electrical output format options, bi–directional output characteristics, determination of the natural zeros, derivation of two balance load prediction methods, description of two tare load iteration algorithms, modeling of balance temperature effects, basics of three–component moment balances, definition of the percent contribution, detection of linear and near–linear dependencies in balance calibration data, a regression model search algorithm, balance interactions, and other related information.

strain-gage balance↗
DOE OSTI2022

Prediction of grain structure after thermomechanical processing of U-10Mo alloy using sensitivity analysis and machine learning surrogate model

Abstract Hot rolling and annealing are critical intermediate steps for controlling microstructures and thickness variations when fabricating uranium alloyed with 10% molybdenum (U-10Mo), which is highly relevant to worldwide nuclear non-proliferation efforts. This work proposes a machine-learning surrogate model combined with sensitivity analysis to identify and predict U-10Mo microstructure development during thermomechanical processing. Over 200 simulations were collected using physics-based microstructure models covering a wide range of thermomechanical processing routes and initial alloy grain features. Based on the sensitivity analysis, we determined that an increase in rolling reduction percentage at each processing pass has the strongest effect in reducing the grain size. Multi-pass rolling and annealing can significantly improve recrystallization regardless of the reduction percentage. With a volume fraction below 2%, uranium carbide particles were found to have marginal effects on the average grain size and distribution. The proposed stratified stacking ensemble surrogate predicts the U-10Mo grain size with a mean square error four times smaller than a standard single deep neural network. At the same time, with a significant speedup (1000×) compared to the physics-based model, the machine learning surrogate shows good potential for U-10Mo fabrication process optimization.

36 MATERIALS SCIENCE↗
NASA NTRS1985

Understanding climate: A strategy for climate modeling and predictability research, 1985-1995

The emphasis of the NASA strategy for climate modeling and predictability research is on the utilization of space technology to understand the processes which control the Earth's climate system and it's sensitivity to natural and man-induced changes and to assess the possibilities for climate prediction on time scales of from about two weeks to several decades. Because the climate is a complex multi-phenomena system, which interacts on a wide range of space and time scales, the diversity of scientific problems addressed requires a hierarchy of models along with the application of modern empirical and statistical techniques which exploit the extensive current and potential future global data sets afforded by space observations. Observing system simulation experiments, exploiting these models and data, will also provide the foundation for the future climate space observing system, e.g., Earth observing system (EOS), 1985; Tropical Rainfall Measuring Mission (TRMM) North, et al. NASA, 1984.

Thiele, O.↗
NASA NTRS1972

Microbial burden prediction model for unmanned planetary spacecraft

The technical development of a computer program for predicting microbial burden on unmanned planetary spacecraft is outlined. The discussion includes the derivation of the basic analytical equations, the selection of a method for handling several random variables, the macrologic of the computer programs and the validation and verification of the model. The prediction model was developed to (1) supplement the biological assays of a spacecraft by simulating the microbial accretion during periods when assays are not taken; (2) minimize the necessity for a large number of microbiological assays; and (3) predict the microbial loading on a lander immediately prior to sterilization and other non-lander equipment prior to launch. It is shown that these purposes not only were achieved but also that the prediction results compare favorably to the estimates derived from the direct assays. The computer program can be applied not only as a prediction instrument but also as a management and control tool. The basic logic of the model is shown to have possible applicability to other sequential flow processes, such as food processing.

Hoffman, A. R.↗
NASA NTRS1994

Predicting the effects of unmodeled dynamics on an aircraft flight control system design using eigenspace assignment

When using eigenspace assignment to design an aircraft flight control system, one must first develop a model of the plant. Certain questions arise when creating this model as to which dynamics of the plant need to be included in the model and which dynamics can be left out or approximated. The answers to these questions are important because a poor choice can lead to closed-loop dynamics that are unpredicted by the design model. To alleviate this problem, a method has been developed for predicting the effect of not including certain dynamics in the design model on the final closed-loop eigenspace. This development provides insight as to which characteristics of unmodeled dynamics will ultimately affect the closed-loop rigid-body dynamics. What results from this insight is a guide for eigenstructure control law designers to aid them in determining which dynamics need or do not need to be included and a new way to include these dynamics in the flight control system design model to achieve a required accuracy in the closed-loop rigid-body dynamics. The method is illustrated for a lateral-directional flight control system design using eigenspace assignment for the NASA High Alpha Research Vehicle (HARV).

Johnson, Eric N.↗
DOE OSTI2023

The physics of desiccation cracks 2: Modeling and prediction of the crack patterns

Here, this paper extends the experimental results of our companion paper by modeling and predicting the onset and pattern formation of desiccation cracks in geomaterials (Ruoyu et al., 2023). Thin-layer silt samples in controlled atmospheric conditions were tested to obtain the surface strain maps with the digital image correlation (DIC) method during dehydration. Support experiments, including consolidation and displacement-controlled triaxial tests, were conducted for the properties of geomaterials. These experimental results were used to validate a viscoplastic theoretical model by comparing cracks and singularities locations that distribute following the Cnoidal wave pattern. A critical value exists in the viscoplastic model that determines the number of singularities, which accurately predicts the number of cracks in the experiment. The critical values contain two crucial parameters: rate sensitivity and λ. Rate sensitivity describes the rate-dependent stress–strain relation, while λ shows the ability of pore pressure redistribution under the external mechanical loading rate. These results provide a new view to analyze the desiccation cracks considering the rate-dependent viscoplasticity.

42 ENGINEERING↗
NASA NTRS2014

High-fidelity Simulation of Jet Noise from Rectangular Nozzles

This Phase II project validated a state-of-the-art LES model, coupled with a Ffowcs Williams-Hawkings (FW-H) far-field acoustic solver, to support the development of advanced engine concepts. These concepts include innovative flow control strategies to attenuate jet noise emissions. The end-to-end LES/ FW-H noise prediction model was demonstrated and validated by applying it to rectangular nozzle designs with a high aspect ratio. The model also was validated against acoustic and flow-field data from a realistic jet-pylon experiment, thereby significantly advancing the state of the art for LES.

Sinha, Neeraj↗
NASA NTRS1986

Helicopter rotor noise due to ingestion of atmospheric turbulence

A theoretical study was conducted to develop an analytical prediction method for helicopter main rotor noise due to the ingestion of atmospheric turbulence. This study incorporates an atmospheric turbulence model, a rotor mean flow contraction model and a rapid distortion turbulence model which together determine the statistics of the non-isotropic turbulence at the rotor plane. Inputs to the combined mean inflow and turbulence models are controlled by atmospheric wind characteristics and helicopter operating conditions. A generalized acoustic source model was used to predict the far field noise generated by the non-isotropic flow incident on the rotor. Absolute levels for acoustic spectra and directivity patterns were calculated for full scale helicopters, without the use of empirical or adjustable constants. Comparisons between isotropic and non-isotropic turbulence at the rotor face demonstrated pronounced differences in acoustic spectra. Turning and contraction of the flow for hover and low speed vertical ascent cases result in a 3 dB increase in the acoustic spectrum energy and a 10 dB increase in tone levels. Compared to trailing edge noise, turbulence ingestion noise is the dominant noise mechanism below approximately 30 rotor harmonics, while above 100 harmonics, trailing edge noise levels exceed turbulence ingestion noise by 25 dB.

Simonich, J. C.↗
DOE OSTI2024

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak

Active feedback control in magnetic confinement fusion devices is desirable to mitigate plasma instabilities and enable robust operation. Optical high-speed cameras provide a powerful, non-invasive diagnostic and can be suitable for these applications. Here, in this study, we process high-speed camera data, at rates exceeding 100 kfps, on in situ field-programmable gate array (FPGA) hardware to track magnetohydrodynamic (MHD) mode evolution and generate control signals in real time. Our system utilizes a convolutional neural network (CNN) model, which predicts the n = 1 MHD mode amplitude and phase using camera images with better accuracy than other tested non-deep-learning-based methods. By implementing this model directly within the standard FPGA readout hardware of the high-speed camera diagnostic, our mode tracking system achieves a total trigger-to-output latency of 17.6 μs and a throughput of up to 120 kfps. This study at the High Beta Tokamak-Extended Pulse (HBT-EP) experiment demonstrates an FPGA-based high-speed camera data acquisition and processing system, enabling application in real-time machine-learning-based tokamak diagnostic and control as well as potential applications in other scientific domains.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2003

Computational Analysis of Cryogenic Flow Through a Control Valve

The initial efforts to develop the capability to model valves used in rocket engine component testing at Stennis Space Center are documented. An axisymmetric model of a control valve with LN2 as the working fluid was developed. The goal was to predict the effect of change in the plug/sear region of the valve prior to testing. The valve flow coefficient was predicted for a range of plug positions. Verification of the calculations was carried out to quantify the uncertainty in the numerical answer. The modeled results compared well qualitatively to experimental trends. Additionally, insights into the flow processes in the valve were obtained. Benefits from the verification process included the ability to use coarser grids and insight into ways to reduce computational time by using double precision accuracy and non-integer grid ratios. Future valve modeling activities will include shape optimization of the valve/seat region and dynamic grid modeling.

Danes, Russell↗
DOE OSTI2023

Nanoparticle Catalyst Formation and Subsequent Sintering: Size-Distribution Fundamental Understanding and Catalyst Control via Mechanism-Enabled Population Balance Modeling (Final Report)

The challenge of elucidating the chemical mechanisms by which nano- and other particles form, and then using those mechanisms to understand, analyze, and ideally predict particle-size and particle-size distributions, was undertaken. Thanks to multi-year, longer-term DOE support each of these challenges was successfully met. The community is now able to both predict, and control in cases where the underlying mechanism of particle formation has been determined, the key PS and PSD that are, in turn, critical properties that strongly influence the catalytic and other physical properties of nano- and larger particles across nature.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Longitudinal coherence and short-term wind speed prediction based on a nacelle-mounted Doppler lidar

The spatial structure of turbulence in atmospheric boundary layer flows is highly relevant to wind energy. In particular, wind turbine control strategies based on inflow preview measurements require knowledge of the longitudinal evolution of turbulent flow as it approaches the rotor. These upstream measurements are usually obtained with nacelle-mounted wind lidars. In contrast to traditional in situ anemometry, lidars collect measurements within a probe volume which varies in size depending on the technology of the commercial system being used. Here, we address two issues related to the use of wind lidar to measure the incoming flow to a wind turbine: (i) whether existing longitudinal coherence models can be used to predict flow at the rotor, based on measurements performed at a distance away from the rotor; and (ii) what effect probe-volume averaging has on the inflow predictions. These two questions are critical to the design and implementation of robust wind turbine control strategies. To address these questions, we perform field measurements and large-eddy simulations to determine which incoming flow structures can be readily predicted with existing coherence models, and which require additional corrections to account for lidar volumetric averaging effects. Results reveal that the wind turbine induction zone has a negligible impact on the longitudinal coherence and first-order turbulence quantities, such as the standard deviation of velocity fluctuations. However, the phase of the signal, from which advection time periods of the turbulent structures are derived, is affected by the rotor blockage effect.

17 WIND ENERGY↗
NASA NTRS1989

Predictive Attitude Maintenance For A Space Station

Paper provides mathematical basis for predictive management of angular momenta of control-moment gyroscopes (CMG's) to control attitude of orbiting space station. Numerical results presented for pitch control of proposed power-tower space station. Based on prior orbit history and mathematical model of density of atmosphere, predictions made of requirements on dumping and storage of angular momentum in relation to current loading state of CMG's and to acceptable attitude tolerances.

Hattis, Philip D.↗