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Results for “Variational data augmentation”

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 19 records

Variational data augmentation for a learning-based granular predictive model of power outages

As the trend in climate change continues, extreme weather events are expected to occur with increasing frequency and severity and pose a significant threat to the electric power infrastructure. Regardless of the efforts a utility puts towards hardening the grid, storm-induced damage to the utility assets such as cables and distributed energy resources (DERs) that are particularly vulnerable to such events is unavoidable. Access to a highly granular, in space and time, outage forecasting tool with long lead times (i.e., days ahead) will enhance the efficiency of service restoration efforts. Here, in this study, we propose to develop and implement a multi-model framework as an operational tool based on a granular and multi-day outage forecasting model using operational numerical weather prediction model forecasts and detailed component outage information. An innovative two-layered recurrent neural network, i.e., a long-short-term-memory (LSTM)-based variational autoencoder (VAE) framework and a sliding window are used to address the uneven distribution of different types of weather events and make better use of the time-series data. Case studies are performed to demonstrate the performance of the new framework.

54 ENVIRONMENTAL SCIENCES↗

An investigation on machine learning predictive accuracy improvement and uncertainty reduction using VAE-based data augmentation

The confluence of ultrafast computers with large memory, rapid progress in Machine Learning (ML) algorithms, and the availability of large datasets place multiple engineering fields at the threshold of dramatic progress. However, a unique challenge in nuclear engineering is data scarcity because experimentation on nuclear systems is usually more expensive and time-consuming than most other disciplines. One potential way to resolve the data scarcity issue is deep generative learning, which uses certain ML models to learn the underlying distribution of existing data and generate synthetic samples that resemble the real data. In this way, one can significantly expand the dataset to train more accurate predictive ML models. In this study, our objective is to evaluate the effectiveness of data augmentation using variational autoencoder (VAE)-based deep generative models. We investigated whether the data augmentation leads to improved accuracy in the predictions of a deep neural network (DNN) model trained using the augmented data. Additionally, the DNN prediction uncertainties are quantified using Bayesian Neural Networks (BNN) and conformal prediction (CP) to assess the impact on predictive uncertainty reduction. To test the proposed methodology, we used TRACE simulations of steady-state void fraction data based on the NUPEC Boiling Water Reactor Full-size Fine-mesh Bundle Test (BFBT) benchmark. Here, we found that augmenting the training dataset using VAEs has improved the DNN model’s predictive accuracy, improved the prediction confidence intervals, and reduced the prediction uncertainties.

Bayesian neural network↗

Predicting critical heat flux with uncertainty quantification and domain generalization using conditional variational autoencoders and deep neural networks

Deep generative models (DGMs) can generate synthetic data samples that closely resemble the original dataset, addressing data scarcity. In this work, we developed a conditional variational autoencoder (CVAE) to augment critical heat flux (CHF) data used for the 2006 Groeneveld lookup table. To compare with traditional methods, a fine-tuned deep neural network (DNN) regression model was evaluated on the same dataset. Both models achieved small mean absolute relative errors, with the CVAE showing more favorable results. Uncertainty quantification (UQ) was performed using repeated CVAE sampling and DNN ensembling. The DNN ensemble improved performance over the baseline, while the CVAE maintained consistent results with less variability and higher confidence. Both models achieved small errors inside and outside the training domain, with slightly larger errors outside. Altogether, the CVAE performed better than the DNN in predicting CHF and exhibited better uncertainty behavior.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Altitude test of several afterburner configurations on a turbofan engine with a hydrogen heater to simulate an elevated turbine discharge temperature

A performance test of several experimental afterburner configurations was conducted with a mixed-flow turbofan engine in an altitude facility. The simulated flight conditions were for Mach 1.4 at two altitudes, 12,190 and 14,630 meters. Turbine discharge temperatures of 889 and 1056 K were used. A production afterburner was tested for comparison. The research afterburners included partial forced mixers with V-gutter flameholders, a carburetted V-gutter flameholder, and a triple ring V-gutter flameholder with four swirl-can fuel mixers. Fuel injection variations were included. Performance data shown include augmented thrust ratio, thrust specific fuel consumption, combustion efficiency, and total pressure drop across the afterburner.

Johnsen, R. L.↗

Calibration of NASA Turbulent Air Motion Measurement System

A turbulent air motion measurement system (TAMMS) was integrated onboard the Lockheed 188 Electra airplane (designated NASA 429) based at the Wallops Flight Facility in support of the NASA role in global tropospheric research. The system provides air motion and turbulence measurements from an airborne platform which is capable of sampling tropospheric and planetary boundary-layer conditions. TAMMS consists of a gust probe with free-rotating vanes mounted on a 3.7-m epoxy-graphite composite nose boom, a high-resolution inertial navigation system (INS), and data acquisition system. A variation of the tower flyby method augmented with radar tracking was implemented for the calibration of static pressure position error and air temperature probe. Additional flight calibration maneuvers were performed remote from the tower in homogeneous atmospheric conditions. System hardware and instrumentation are described and the calibration procedures discussed. Calibration and flight results are presented to illustrate the overall ability of the system to determine the three-component ambient wind fields during straight and level flight conditions.

Barrick, John D. W.↗

Global Reference Atmospheric Model and Trace Constituents

Global Reference Atmospheric Model (GRAM-99) is an engineering-level model of the Earth's atmosphere. It provides both mean values and perturbations for density, temperature, pressure, and winds, as well as monthly- and geographically-varying trace constituent concentrations. From 0-27 km, thermodynamics and winds are based on National Oceanic and Atmospheric Administration Global Upper Air Climatic Atlas (GUACA) climatology. Above 120 km, GRAM is based on the NASA Marshall Engineering Thermosphere (MET) model. In the intervening altitude region, GRAM is based on Middle Atmosphere Program (MAP) climatology that also forms the basis of the 1986 COSPAR Intemationa1 Reference Atmosphere (CIRA). MAP data in GRAM are augmented by a specially-derived longitude variation climatology. Atmospheric composition is represented in GRAM by concentrations of both major and minor species. Above 120 km, MET provides concentration values for N2, O2, Ar, O, He, and H. Below 120 km, species represented also include H2O, O3, N2O, CO, CH, and CO2. Water vapor in GRAM is based on a combination of GUACA, Air Force Geophysics Laboratory (AFGL), and NASA Langley Research Center climatologies. Other constituents below 120 km are based on a combination of AFGL and h4AP/CIRA climatologies. This report presents results of comparisons between GRAM Constituent concentrations and those provided by the Naval Research Laboratory (NRL) climatology of Summers (NRL,/MR/7641-93-7416, 1993). GRAM and NRL concentrations were compared for seven species (CH4, CO, CO2, H2O, N2O, O2, and O3) for months January, April, July, and October, over height range 0-115 km, and latitudes -90deg to + 90deg at 10deg increments. Average GRAM-NRL correlations range from 0.878 (for CO) to 0.975 (for O3), with an average over all seven species of 0.936 (standard deviation 0.049).

Justus, C.↗

Investigation of control, display, and crew-loading requirements for helicopter instrument approach

A ground simulation experiment was conducted on a flight simulator for advanced aircraft to investigate the influence and interaction of flight-control system, flight-director display, and crew-loading situation on helicopter flying qualities during terminal-area operations in instrument conditions. Six levels of control complexity were implemented on a representative helicopter model. The six levels of augmentation were examined with display variations consisting of raw elevation and azimuth data only and of raw data plus one-, two-, and three-cue flight directors. Crew-loading situations simulated for the control-display combinations were dual-pilot operation and single-pilot operation. Four pilots performed a total of 150 evaluations of combinations of these parameters for a representative microwave landing system approach task. Pilot rating results indicated the existence of a control display trade-off for ratings of satisfactory, whereas ratings of adequate-but-unsatisfactory depended primarily on the control system; the control system required for ratings of adequate-but-unsatisfactory was clearly more complex for the single-pilot situation than that for the dual-pilot situation.

Lebacqz, J. V.↗

A piloted simulator investigation of stability and control, display and crew-loading requirements for helicopter instrument approach. Part 1: Technical discussion and results

A ground-simulation experiment was conducted to investigate the influence and interaction of flight-control system, fight-director display, and crew-loading situation on helicopter flying qualities during terminal area operations in instrument conditions. The experiment was conducted on the Flight Simulator for Advanced Aircraft at Ames Research Center. Six levels of control complexity, ranging from angular rate damping to velocity augmented longitudinal and vertical axes, were implemented on a representative helicopter model. The six levels of augmentation were examined with display variations consisting of raw elevation and azimuth data only, and of raw data plus one-, two-, and three-cue flight directors. Crew-loading situations simulated for the control-display combinations were dual-pilot operation (representative auxiliary tasks of navigation, communications, and decision-making). Four pilots performed a total of 150 evaluations of combinations of these parameters for a representative microwave landing system (MLS) approach task.

Lebacqz, J. V.↗

Dynamics of argon metastables in Ar–CH 4 radio frequency capacitively-coupled plasma: real-time monitoring with neural network-augmented broadband optical emission spectroscopy

In moderate-pressure radio frequency (RF) capacitively coupled plasmas generated in argon–methane mixtures, the density of argon metastable atoms (Ar 1 s 5 ) exhibits a non-monotonic dependence on methane (CH 4 ) concentration. Laser-induced fluorescence (LIF) was used to measure and compare local Ar 1 s 5 densities in Ar and Ar–CH 4 plasmas at 2.6 Torr and RF powers of 17–117 W. The addition of 1% CH 4 increases the metastable density, and 2% CH 4 triggers a strong depletion by an order of magnitude, compared to 1% CH 4 case. This non-monotonic behavior demonstrates the sensitivity of metastable populations to small gas admixtures, which is critical for processes where metastables drive precursor dissociation. For real-time monitoring of metastable population, broadband optical emission spectroscopy (OES) is augmented with a feedforward neural network (NN) to predict Ar s1 5 densities from spectral features. When trained on LIF data, the NN replicates the absolute densities and the dynamic trends of Ar 1 s 5 density variation. The NN-augmented broadband OES approach can be used as a simple and cost-effective tool for tracking Ar metastables in Ar-rich plasmas, facilitating industrial-scale optimization.

Yatom, Shurik [Princeton Plasma Physics Laboratory↗

Enhanced Mixing in a Rectangular Duct

An experimental investigation of the mixing of non-reacting opposed rows of jets injected normal to a confined rectangular crossflow has been conducted. Planar Mie-scattering was used to measure the time-average concentration distribution of the jet fluid in planes perpendicular to the duct axis. Particular emphasis was placed on the study of closely spaced orifice configurations applicable to the mixing zone of an RQL combustor. Baseline studies were performed of mixing under "ideal" conditions, i.e., plenum fed jets injecting into a crossflow uniform in velocity and turbulence intensity. In addition, more practical ("non-ideal") issues encountered during hardware design were also studied. As in other studies, mixing effectiveness, determined using a spatial unmixedness parameter based on the variance of mean jet concentration distributions, was found to be optimum when the spacing-to-duct-height ratio was inversely proportional to the square root of the jet-to-mainstream momentum-flux ratio. This relationship is suitable for design under ideal flow conditions. Inlet flow boundary conditions of the jet and approach flow (mainstream) were found to strongly influence mixing performance, but no attempt was made to determine optimum performance under non-ideal conditions. The tests performed do offer some guidance as to expected mixing behavior for several common variables likely to be imposed by hardware constraints. Additionally, in this study it was found that for rows of orifices with opposite centerlines inline, mixing was similar for blockages up to 89 percent (previous crossflow mixing studies concerned with dilution zone configurations, blockages were typically less than 50 percent). Lower levels of unmixedness were obtained as a function of downstream location when axial injection length was minimized. Mixing may be enhanced if orifice centerlines of opposed rows are staggered, but blockage must be =50 percent in this configuration. Round hole and "square" orifice shapes had similar performance. Other variations in orifice shape did not substantially augment overall mixing performance. Furthermore an isothermal mixing data set was generated and used by CFDRC as input to a NO(x) inference code.

Liscinsky, D. S.↗

Noise measurements for various configurations of a model of a mixer nozzle externally blown flap system

Noise data were taken for variations to a large scale model of an externally blown flap lift augmentation system. The variations included two different mixer nozzles (7 and 8 lobes), two different wing models (2 and 3 flaps), and different lateral distances between the wing chord line and the nozzle centerline. When the seven lobe was used with the trailing flap in the 60 deg position, increasing the wing to nozzle distance had no effect on the sound level. When the eight lobe nozzle was used there was a decrease in sound level. With the 20 deg flap setting the noise level decreased when the distance was increased using either nozzle.

Goodykoontz, J. H.↗

Constraints on the Within Season and Between Year Variability of the North Residual Cap from MGS-TES

There is a long history of telescopic and spacecraft observations of the polar regions of Mars. The finely laminated ice deposits and surrounding layered terrains are commonly thought to contain a record of past climate conditions and change. Understanding the basic nature of the deposits and their mineral and ice constituents is a continued focus of current and future orbited missions. Unresolved issues in Martian polar science include a) the unusual nature of the CO2 ice deposits ("Swiss Cheese", "slab ice" etc.) b) the relationship of the ice deposits to underlying layered units (which differs from the north to the south), c) understanding the seasonal variations and their connections to the finely laminated units observed in high-resolution images and d) the relationship of dark materials in the wind-swept lanes and reentrant valleys to the surrounding dark dune and surface materials. Our work focuses on understanding these issues in relationship to the north residual ice cap. Recent work using Mars Global Surveyor (MGS) data sets have described evolution of the seasonal CO2 frost deposits. In addition, the north polar residual ice cap exhibits albedo variations between Mars years and within the summer season. The Thermal Emission Spectrometer (TES) data set can augment these observations providing additional constraints such as temperature evolution and spectral properties associated with ice and rocky materials. Exploration of these properties is the subject of our current study.

Calvin, W. M.↗

A flight investigation of static stability, control augmentation, and flight director influences on helicopter IFR handling qualities

A flight experiment was conducted using the NASA-Army V/STOLAND UH-1H variable-stability helicopter to investigate the influence of several longitudinal-static-stability, control-augmentation, and flight-director parameters on helicopter flying qualities during terminal area operations in instrument conditions. This experiment, which was part of a joint NASA/FAA program pertaining to helicopter IFR airworthiness, was designed to corroborate and extend previous ground simulation results obtained in this program. Variations examined included stable and neutral longitudinal control position gradients, rate-damping and attitude-command augmentation, and raw data versus flight-director displays. Pilot rating results agreed excellently with the ground simulation data, indicating an adequate instrument capability with rate-damping augmentation and neutral statics and the need for pitch-roll attitude augmentation to achieve a satisfactory system.

Lebacqz, J. V.↗

Acoustic scattering by circular cylinders of various aspect ratios

The effects of acoustic scattering on the useful frequency range of pressure gradient microphones were investigated experimentally between ka values of 0.407 and 4.232 using two circular cylindrical models (L/D = 0.5 and 0.25) having a 25 cm outside diameter. Small condenser microphones, attached to preamplifiers by flexible connectors, were installed from inside the cylindrical bodies, and flush mounted on the exterior surface of the cylinders. A 38 cm diameter woofer in a large speaker enclosure was used as the sound source. Surface pressure augmentation and phase differences were computed from measured data for various sound wave incidence angles. Results are graphically compared with theoretical predictions supplied by NASA for ka = 0.407, 2.288, and 4.232. All other results are tabulated in the appendices. With minor exceptions, the experimentally determined pressure augmentations agreed within 0.75 dB with theoretical predictions. The agreement for relative phase angles was within 5 percent without any exceptions. Scattering parameter variations with ka and L/D ratio, as computed from experimental data, are also presented.

Maciulaitis, A.↗

Assessment and Improvement of RANS-based Transition Models based on Experimental Data of the Common Research Model with Natural Laminar Flow

Transition models based on auxiliary transport equations augmenting the Reynolds-averaged Navier-Stokes (RANS) framework often rely upon the correlations that were derived from a limited number of low-speed experiments and do not account for all of the transition mechanisms and/or their variation with the significant flow parameters. Available data from a recent experiment in the National Transonic Facility at the NASA Langley Research Center are used to assess the current transition modeling capability in NASA's OVERFLOW 2.2o code for a swept wing configuration at transonic cruise conditions. Specifically, the OVERFLOW solutions are used together with detailed stability analysis of the boundary layer flow over the new Common Research Model with Natural Laminar Flow (CRM-NLF) to evaluate the accuracy and the robustness of the transport-equation-based transition models, with the goal of proposing improvements that would help to strengthen the physical basis of these models for the important class of flows involving the combined effects of crossflow and flow compressibility. Results highlight the significant underprediction of the laminar flow extent within the inboard region of the wing, wherein the onset of transition may be attributed to a gradual amplification of Tollmien-Schlichting instabilities.

Boundary layer transition↗

Natural variations in the geomagnetically trapped electron population

Temporal variations in the trapped natural electron flux intensities and energy spectra are discussed and demonstrated using recent satellite data. These data are intended to acquaint the space systems engineer with the types of natural variations that may be encountered during a mission and to augment the models of the electron environment currently being used in space system design and orbit selection. An understanding of the temporal variations which may be encountered should prove helpful. Some of the variations demonstrated here which are not widely known include: (1) addition of very energetic electrons to the outer zone during moderate magnetic storms: (2) addition of energetic electrons to the inner zone during major magnetic storms; (3) inversions in the outer zone electron energy spectrum during the decay phase of a storm injection event and (4) occasional formation of multiple maxima in the flux vs altitude profile of moderately energetic electrons.

Vampola, A. L.↗

Improved Earth Sensor Performance Using a Sequentially Correlated Noise Model

Spacecraft attitude estimation by means of an extended Kalman filter requires a reasonably true model of the inherent noise of each sensor. For some sensors, the largest uncorrected noise comes not from the sensor itself, but from errors in the model for the predicted observations. This is certainly the case for Earth horizon sensors. The Earth horizon as seen from low Earth orbit is nearly a circle whose radius depends primarily on altitude. A straightforward latitude-dependent correction is added to this to account for the oblateness of the Earth. There also are both seasonal and stochastic variations in the horizon height. The seasonal variations can be predicted to some limited degree based on models de(ived from historical data. The stochastic component characteristically shows variations that are correlated both in time and space but which are unpredictable over long time spans. This work investigates whether Earth horizon sensor performance can be improved by solving for its systematic error as an augmentation of an attitude Kalman filter. It is found that using only Earth and Sun sensors, the augmented state is not fully observable. Even when magnetometer data is included, only the pitch axis component of the error can be improved; the roll component is unobservable.

Sedlak, Joseph↗

Improved Earth Sensor Performance Using a Sequentially Correlated Noise Model

Spacecraft attitude estimation by means of an extended Kalman filter requires a reasonably true model of the inherent noise of each sensor. For some sensors, the largest uncorrected noise comes not from the sensor itself, but from errors in the model for the predicted observations. This is certainly the case for Earth horizon sensors. The Earth horizon as seen from low Earth orbit is nearly a circle whose radius depends primarily on altitude. A straightforward latitude-dependent correction is added to this to account for the oblateness of the Earth. There also are both seasonal and stochastic variations in the horizon height. The seasonal variations can be predicted to some limited degree based on models derived from historical data. The stochastic component characteristically shows variations that are correlated both in time and space but which are unpredictable over long time spans. This work investigates whether Earth horizon sensor performance can be improved by solving for its systematic error as an augmentation of an attitude Kalman filter. It is found that using only Earth and Sun sensors, the augmented state is not fully observable. Even when magnetometer data is included, only the pitch axis component of the error can be improved; the roll component is unobservable.

Sedlak, J.↗