Search NASA⌕ Search

SEARCH · Search NASA

Results for “generative modeling”

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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Adaptive Disturbance Tracking Theory with State Estimation and State Feedback for Region II Control of Large Wind Turbines

A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.

Balas, Mark J.↗
NASA NTRS2014

Implementation and Validation of 3-D Ice Accretion Measurement Methodology

A research program has been implemented to develop and validate the use of a commercial 3-D laser scanning system to record ice accretion geometry in the NASA Icing Research Tunnel. A main component of the program was the geometric assessment of the 3-D laser scanning system on a 2-D (straight wing) and a 3-D (swept wing) airfoil geometries. This exercise consisted of comparison of scanned ice accretion to castings of the same ice accretion. The scan data were also used to create rapid prototype artificial ice shapes that were scanned and compared to the original ice accretion.The results from geometric comparisons on the straight wing showed that the ice shape models generated through the scanrapid prototype process compared reasonably well with the cast shapes. Similar results were obtained with the geometric comparisons on the swept wing. It was difficult to precisely compare the scans of the cast shapes to the original ice accretion scans because the cast shapes appear to have shrunk during the moldcasting process by as much as 0.10-inch. However the comparison of the local ice-shape features were possible and produced better results. The rapid prototype manufacturing process was shown to reproduce the original ice accretion scan normally within 0.01-inch.

Aerodynamics↗
NASA NTRS2014

Implementation and Validation of 3-D Ice Accretion Measurement Methodology

A research program has been implemented to develop and validate the use of a commercial 3-D laser scanning system to record ice accretion geometry in the NASA Icing Research Tunnel. A main component of the program was the geometric assessment of the 3- D laser scanning system on a 2-D (straight wing) and a 3-D (swept wing) airfoil geometries. This exercise consisted of comparison of scanned ice accretion to castings of the same ice accretion. The scan data were also used to create rapid prototype artificial ice shapes that were scanned and compared to the original ice accretion. The results from geometric comparisons on the straight wing showed that the ice shape models generated through the scan/rapid prototype process compared reasonably well with the cast shapes. Similar results were obtained with the geometric comparisons on the swept wing. It was difficult to precisely compare the scans of the cast shapes to the original ice accretion scans because the cast shapes appear to have shrunk during the mold/casting process by as much as 0.10-inch. However the comparison of the local ice-shape features were possible and produced better results. The rapid prototype manufacturing process was shown to reproduce the original ice accretion scan normally within 0.01-inch.

Icing↗
NASA NTRS2017

Vortex Generators in a Streamline-Traced, External-Compression Supersonic Inlet

Vortex generators within a streamline-traced, external-compression supersonic inlet for Mach 1.66 were investigated to determine their ability to increase total pressure recovery and reduce total pressure distortion. The vortex generators studied were rectangular vanes arranged in counter-rotating and co-rotating arrays. The vane geometric factors of interest included height, length, spacing, angle-of-incidence, and positions upstream and downstream of the inlet terminal shock. The flow through the inlet was simulated numerically through the solution of the steady-state, Reynolds-averaged Navier-Stokes equations on multi-block, structured grids using the Wind-US flow solver. The vanes were simulated using a vortex generator model. The inlet performance was characterized by the inlet total pressure recovery and the radial and circumferential total pressure distortion indices at the engine face. Design of experiments and statistical analysis methods were applied to quantify the effect of the geometric factors of the vanes and search for optimal vane arrays. Co-rotating vane arrays with negative angles-of-incidence positioned on the supersonic diffuser were effective in sweeping low-momentum flow from the top toward the sides of the subsonic diffuser. This distributed the low-momentum flow more evenly about the circumference of the subsonic diffuser and reduced distortion. Co-rotating vane arrays with negative angles-of-incidence or counter-rotating vane arrays positioned downstream of the terminal shock were effective in mixing higher-momentum flow with lower-momentum flow to increase recovery and decrease distortion. A strategy of combining a co-rotating vane array on the supersonic diffuser with a counter-rotating vane array on the subsonic diffuser was effective in increasing recovery and reducing distortion.

computational fluid dynamics↗
NASA NTRS2017

Aeroservoelastic Modeling of Body Freedom Flutter for Control System Design

The communication of this method is being used by NASA in the ongoing collaborations with groups interested in the X-56A flight test program. Model generation for body freedom flutter Addressing issues in: State Consistency, Low frequency dynamics, Unsteady aerodynamics. Applied approach to X-56A MUTT: Comparing to flight test data.

Degree of Freedom↗
NASA NTRS2017

Ice Crystal Icing Research at NASA

Ice crystals found at high altitude near convective clouds are known to cause jet engine power-loss events. These events occur due to ice crystals entering a propulsion systems core flowpath and accreting ice resulting in events such as uncommanded loss of thrust (rollback), engine stall, surge, and damage due to ice shedding. As part of a community with a growing need to understand the underlying physics of ice crystal icing, NASA has been performing experimental efforts aimed at providing datasets that can be used to generate models to predict the ice accretion inside current and future engine designs. Fundamental icing physics studies on particle impacts, accretion on a single airfoil, and ice accretions observed during a rollback event inside a full-scale engine in the Propulsion Systems Laboratory are summarized. Low fidelity code development using the results from the engine tests which identify key parameters for ice accretion risk and the development of high fidelity codes are described. These activities have been conducted internal to NASA and through collaboration efforts with industry, academia, and other government agencies. The details of the research activities and progress made to date in addressing ice crystal icing research challenges are discussed.

icing↗
NASA NTRS2017

Ice Crystal Icing Research at NASA

Ice crystals found at high altitude near convective clouds are known to cause jet engine power-loss events. These events occur due to ice crystals entering a propulsion systems core flowpath and accreting ice resulting in events such as uncommanded loss of thrust (rollback), engine stall, surge, and damage due to ice shedding. As part of a community with a growing need to understand the underlying physics of ice crystal icing, NASA has been performing experimental efforts aimed at providing datasets that can be used to generate models to predict the ice accretion inside current and future engine designs. Fundamental icing physics studies on particle impacts, accretion on a single airfoil, and ice accretions observed during a rollback event inside a full-scale engine in the Propulsion Systems Laboratory are summarized. Low fidelity code development using the results from the engine tests which identify key parameters for ice accretion risk and the development of high fidelity codes are described. These activities have been conducted internal to NASA and through collaboration efforts with industry, academia, and other government agencies. The details of the research activities and progress made to date in addressing ice crystal icing research challenges are discussed.

upwind schemes↗
NASA NTRS2017

Ice Crystal Icing Research at NASA

Ice crystals found at high altitude near convective clouds are known to cause jet engine power-loss events. These events occur due to ice crystals entering a propulsion system's core flowpath and accreting ice resulting in events such as uncommanded loss of thrust (rollback), engine stall, surge, and damage due to ice shedding. As part of a community with a growing need to understand the underlying physics of ice crystal icing, NASA has been performing experimental efforts aimed at providing datasets that can be used to generate models to predict the ice accretion inside current and future engine designs. Fundamental icing physics studies on particle impacts, accretion on a single airfoil, and ice accretions observed during a rollback event inside a full-scale engine in the Propulsion Systems Laboratory are summarized. Low fidelity code development using the results from the engine tests which identify key parameters for ice accretion risk and the development of high fidelity codes are described. These activities have been conducted internal to NASA and through collaboration efforts with industry, academia, and other government agencies. The details of the research activities and progress made to date in addressing ice crystal icing research challenges are discussed.

crysta↗
NASA NTRS2017

Online Multi-Modal Learning and Adaptive Information Trajectory Planning for Autonomous Exploration

In robotic information gathering missions, scientists are typically interested in understanding variables which require proxy measurements from specialized sensor suites to estimate. However, energy and time constraints limit how often these sensors can be used in a mission. Robots are also equipped with cheaper to use navigation sensors such as cameras. In this paper, we explore a challenging planning problem in which a robot is required to learn about a scientific variable of interest in an initially unknown environment by planning informative paths and deciding when and where to use its sensors. To tackle this we present two innovations: a Bayesian generative model framework to automatically learn correlations between expensive science sensors and cheaper to use navigation sensors online, and a sampling based approach to plan for multiple sensors while handling long horizons and budget constraints. Our approach does not grow in complexity with data and is anytime making it highly applicable to field robotics. We tested our approach extensively in simulation and validated it with real data collected during the 2014 Mojave Volatiles Prospector Mission. Our planning algorithm performs statistically significantly better than myopic approaches and at least as well as a coverage-based algorithm in an initially unknown environment while having added advantages of being able to exploit prior knowledge and handle other intricacies of the real world without further algorithmic modifications.

learning↗
NASA NTRS2016

A Quantum-Assisted Algorithm for Sampling Applications in Machine Learning

An increase in the efficiency of sampling from Boltzmann distributions would have a significant impact in deep learning and other machine learning applications. Recently, quantum annealers have been proposed as a potential candidate to speed up this task, but several limitations still bar these state-of-the-art technologies from being used effectively. One of the main limitations is that, while the device may indeed sample from a Boltzmann-like distribution, quantum dynamical arguments suggests it will do so with an instance-dependent effective temperature, different from the physical temperature of the device. Unless this unknown temperature can be unveiled, it might not be possible to effectively use a quantum annealer for Boltzmann sampling. In this talk, we present a strategy to overcome this challenge with a simple effective-temperature estimation algorithm. We provide a systematic study assessing the impact of the effective temperatures in the learning of a kind of restricted Boltzmann machine embedded on quantum hardware, which can serve as a building block for deep learning architectures. We also provide a comparison to k-step contrastive divergence (CD-k) with k up to 100. Although assuming a suitable fixed effective temperature also allows to outperform one step contrastive divergence (CD-1), only when using an instance-dependent effective temperature we find a performance close to that of CD-100 for the case studied here. We discuss generalizations of the algorithm to other more expressive generative models, beyond restricted Boltzmann machines.

Perdomo-Ortiz, Alejandro↗
NASA NTRS2019

Astrobiology Survey of a Lava Cave at Lava Beds National Monument by a Rover Carrying a Remote Sensing Instrument Payload

We report here on a survey of a lava tube cave by a rover that is instrumented for astrobiology missions. The NASA Ames testbed rover, CaveR, was deployed in Valentine Cave in Lava Beds National Monument (N. CA, USA) during August of 2018. The rover carried an instrument package consisting of Near Infrared and Visible Spectrometer System (NIRVSS) a point spectrometer operating in 1590-3400 nm range, sensitive to H2O and -OH bearing minerals, pyroxenes, and carbonates (Roush, et al 2018); the bore sighted Drill Operations Camera (DOC), a monochrome imager illuminated by LEDs at 410, 540, 640, 740, 905 and 940 nm; a Realsense ™ depth sensor system for 3D model generation; and a high resolution DSLR stereo camera. The payload was mounted on a tiltable instrument platform attached to the left side of the rover. The rover was driven manually in the cave by field operators, following instructions from a remote science operations team, and simulating a mission concept with science-guided autonomy. A simulated mission took place for 3 days with a team of 3 scientists selecting targets and interpreting data from the payload. To begin the mission, the rover drove along one wall of the cave imaging continuously with the Realsense in 20 m cave segments, three total. At the start of each day, the images from a 20m segment and a panorama stitched from them were provided to the science team to examine. The science team used these data to prioritize specific points along the cave wall for the collection of NIRVSS, DOC, and DSLR data. The objective of the data collection was to identify and study putative biological and mineralogical features in the cave. The data were delivered in xGDS, a customized mapping, planning, and data base management software developed at NASA Ames (Lee, et al 2013). Once the targets for further observations were selected, a plan for collecting the observations (positions in the cave and pointing for each requested observation) was constructed using xGDS and delivered to a rover team to execute the science data collection plan. Acquired data were delivered back to the science team for analysis. Preliminary results from the experiment illustrate the utility of the system (rover plus payload) to study the cave geology and mineralogy and its potential for identifying biomineral features.

Wong, Uland↗
NASA NTRS2019

Overview of Multi-Layer Metal Insulation Development for Small Stirling Convertors at NASA GRC

The small Stirling convertor currently under development at the NASA Glenn Research Center (GRC) is designed to produce one watt of electrical power from eight watts of heat. Previous radioisotope power systems (RPS) made use of the General-Purpose Heat Source (GPHS) which produces 250 watts of heat but is unsuitable for a one-watt Stirling convertor. The only heat source available is the Light-Weight Radioisotope Heating Unit (LWRHU) which produces one watt of heat and is primarily used to provide heat to electronics and instrumentation to maintain their appropriate operating temperature. Unfortunately, the LWRHU has a heat flux of 272 W/m-squared compared to the GPHS heat flux of 6000 W/m-squared which greatly increases the demands on the insulation to ensure that enough of the heat produced is available to the convertor and not lost to the environment. An analysis was performed that showed that the insulation must have a thermal conductivity of 0.005 W/m·K or better for the system to function. A multi-layer metal insulation package was designed and a prototype was fabricated and tested to investigate the feasibility of this design. The prototype did not meet the requirements; however, the improved thermal model generated using the test data will allow for a second iteration to be developed that has a much higher confidence and meets the performance requirements.

Goodell, Daniel D.↗
NASA NTRS2019

Overview of Multi-Layer Metal Insulation Development for Small Stirling Convertors at NASA GRC

The small Stirling convertor currently under development at the NASA Glenn Research Center (GRC) is designed to produce one watt of electrical power from eight watts of heat. Previous radioisotope power systems (RPS) made use of the General-Purpose Heat Source (GPHS) which produces 250 watts of heat but is unsuitable for a one-watt Stirling convertor. The only heat source available is the Light-Weight Radioisotope Heating Unit (LWRHU) which produces one watt of heat and is primarily used to provide heat to electronics and instrumentation to maintain their appropriate operating temperature. Unfortunately, the LWRHU has a heat flux of 272 W/m-squared (watts per square meter) compared to the GPHS heat flux of 6000 W/m-squared which greatly increases the demands on the insulation to ensure that enough of the heat produced is available to the convertor and not lost to the environment. An analysis was performed that showed that the insulation must have a thermal conductivity of 0.005 W/m squared -K (watts per square meter per Kelvin) or better for the system to function. A multi-layer metal insulation package was designed and a prototype was fabricated and tested to investigate the feasibility of this design. The prototype did not meet the requirements; however, the improved thermal model generated using the test data will allow for a second iteration to be developed that has a much higher confidence and meets the performance requirements.

Goodell, Daniel↗
NASA NTRS2019

Assessment of Ku- and Ka-Band Dual-Frequency Radar for Retrieval of Snow Properties

Current scattering look-up tables for snow assume a constant mass density along with a Gamma particle size distribution (PSD). The first assumption is tested against scattering parameters from simulated particle models generated by Dr. Kwo-Sen Kuo at GSFC and Dr. Guosheng Liu at FSU. Good agreement of the scattering parameters is found with the FSU results if the mass is taken to be the same as the mass of the simulated particle and the mass density is taken to be 0.2 g/cm cu. For the GSFC data base, good agreement is found if the mass density is taken to be between 0.1 and 0.2 g/cm cu. The second assumption of a Gamma PSD is tested against measured PSD's along with a m-d (mass-dimension) relationship. The degree of agreement depends on the value of, the 'shape' parameter in the Gamma distribution but to a lesser degree on the m-d relationship (of the three that were examined). A shortcoming of the simulated snow particle data bases is the lack of large particles. As a consequence, larger values of DFR (dual-frequency ratio) that are commonly seen in airborne and spaceborne measurements cannot be reproduced from the tables. This situation is expected to improve as scattering parameters from larger particles are included in the databases.

Liang Liao↗
NASA NTRS2020

Thoracic Pressure Does Not Impact CSF Pressure via Compartment Compliance

Space acquired neuro-ocular syndrome (SANS) remains a difficult risk to characterize due to the complex multi-factorial etiology related to physiological responses to the spaceflight environment. Fluid shift and the resultant change on the Cardiovascular (CV) and cerebral spinal fluid systems (CSF) in the absence of gravity continue to be considered a contributing factor to the progression of SANS. In this study, we utilize a computational model of the CSF and CV interface to establish the sensitivity that intracranial pressure, and subsequently the optic nerve sheath pressure, exhibits due to variations in thoracic pressure, assuming the cranial perfusion pressure, i.e. mean arterial pressure (MAP) to central venous pressure (CVP), is known. Methods: The GRC Cross cutting computational modeling project created as model of the CSF and CV interaction within the cranial vault by extending the work of Stevens et al. [1] by modifying the representative anatomy to include a separate venous sinus, jugular veins, secondary veins and extra jugular pathways [2-3] to more adequately represent the vascular drainage pathways from the cranial vault (Figure 1). Assuming the MAP, CVP and thoracic pressure are known, we initiated this enhanced computational model assuming a supine positon and utilized a linear ramp to vary the thoracic pressure from the assumed supine state to the target pressure corresponding to set MAP and CVP values. The model generates the time based CSF pressure values (Figure2). Results and Conclusions: Following this analysis, CSF pressure shows significant independence from thoracic pressure changes (16 mmHg in thoracic pressure produces < 1mmHg change in CSF pressure), being mostly dependent on perfusion pressure. Similarly fluid redistribution is not predicted to be impacted over a level of 1mL. We note that this simulation represents an acute changes (order of 10's of minutes) and does not represent the long term effects.

Munster, Drayton W.↗
NASA NTRS2019

Decomposing Shortwave Top-of-Atmosphere and Surface Radiative Flux Variations in Terms of Surface and Atmospheric Contributions

Adiagnostic tool for determining surface and atmospheric contributions to interannual variations in top-of-atmosphere (TOA) reflected shortwave (SW) and net downward SW surface radiative fluxes is introduced. The method requires only upward and downward radiative fluxes at the TOA and surface as input and therefore can readily be applied to both satellite-derived and model-generated adiative fluxes. Observations from the Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Edition 4.0 product show that 81% of the monthly variability in global mean reflected SW TOA flux anomalies is associated with atmospheric variations (mainly clouds),6%is from surface variations, and 13% is from atmosphere–surface covariability. Over the Arctic Ocean, most of the variability in both reflected SW TOA flux and net downward SW surface flux anomalies is explained by variations in sea ice and cloud fraction alone (r2 5 0.94). Compared to CERES, variability in two reanalyses—the ECMWF interim reanalysis (ERA-Interim) and NASA’s Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2)—show large differences in the regional distribution of variance for both the atmospheric and surface contributions to anomalies in net downward SW surface flux. For MERRA-2 the atmospheric contribution is 17% too large compared to CERES while ERA-Interim underestimates the variance by 15%. The difference is mainly due to how cloud variations are represented in the reanalyses. The overall surface contribution in both ERA-Interim and MERRA-2 is smaller than CERES EBAF by 15% for ERA-Interim and 58% for MERRA-2, highlighting limitations of the reanalyses in representing surface albedo variations and their influence on SW radiative fluxes.

Norman G. Loeb↗
NASA NTRSDate not supplied

Spectral Analysis of Integrated Pressures on Patches with Unsteady Pressure-Sensitive Paint Measurements

This paper describes the spectral analysis of integrated pressures on patches of the scale model of the Space Launch System (SLS) Block 1B crew vehicle with the Unsteady Pressure-Sensitive Paint (uPSP) measurements, which were collected in the ascent transient aerodynamics tests with the Unitary Plan Wind Tunnel 11-by-11-foot Transonic Wind Tunnel in September 2019 at NASA Ames Research Center. Recent research has demonstrated that uPSP can be an essential tool for the assessment of the unsteady, aerodynamic phenomena. The work described in this paper is a part of NASA’s development of a new state-of-the-art uPSP capability in production wind tunnels. In this paper, 108 patches are defined with x station values and azimuth angles of the scale model. For each patch, the polygons are determined from the surface cells of the grid of the model, clipped with the edges of the patch, and each of the polygons is divided into triangles. The inputs of the pressure integration algorithm are the time series of pressure coefficients on the vertices of the grid of the model, generated by the uPSP data processing program from the videos taken with 4 Phantom high-speed cameras during the wind tunnel tests. The integrated pressure of the patch is determined as the ratio of the sum of the forces on the triangles over the sum of the areas of the triangles. For each of the test cases, the Cross Power Spectral Density (CPSD) and Magnitude-Squared Coherence (msCohere) are computed for frequencies over 1/3 octave bands from the time series of the integrated pressures on the patches. The spectral analysis outputs of different cases of the wind tunnel tests are analyzed and the coherence of patches is investigated over frequencies, x station values, azimuth angles, Mach numbers and SLS vehicle attitudes. The pressure integration and spectral analysis described in this paper were executed on the NASA Pleiades supercomputer. Funding for this research was provided by the NASA Aeroscience Evaluation and Test Capabilities (AETC) Project.

Pressure-Sensitive Paint↗
NASA NTRS2020

Intelligent Contingency Management for Urban Air Mobility

The third aviation revolution is seeking to enable transportation where users have access to immediate and flexible air travel; the users dictate trip origin, destination and timing. One of the major components of this vision is urban air mobility (UAM) for the masses. UAM means a safe and efficient system for vehicles to move passengers and cargo within a city. In order to reach UAM’s full market potential the vehicle will have to be autonomous. One of the primary challenges of autonomous flight is dealing with off-nominal events, both common and unforeseen; thus, intelligent contingency management (ICM) is one of the enabling technologies. In this context, the vehicle has to be aware of its internal state and external environment at all times, ascertain its capability and make decisions about mission completion or modification. All of these functions require data to model and assess the environment and then take actions based on these models. Necessarily, there is uncertainty associated with the data and the models generated from it. Since we are dealing with safety-critical systems, one of the main challenges of ICM is to generate sufficient data and to minimize its uncertainty to enable practical and safe decision making. We propose an overall architecture that incorporates deterministic and learning algorithms together to assess vehicle capabilities, project these into the future and make decisions on mission management level. A layered approach allows for mature parts and technologies to be integrated into early highly automated vehicles before the final state of autonomy is reached.

data-driven systems↗