Search NASA⌕ Search

SEARCH · Search NASA

Results for “Generative model”

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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Dust and neutral gas modeling of the inner atmospheres of comets

This paper summarizes the present, preencounter understanding of the physical and chemical processes controlling the inner (r less than 1000 km) region of cometary atmospheres. Special emphasis was attached to compiling a self-consistent set of governing equations. This review is aimed at readers who want to understand the present status of the mantle and coma regions and/or who want to develop new, next generation models which will be needed as the large volume of new observational data will become available in the near future.

Gombosi, T. I.↗
NASA NTRS2013

Missing Peroxy Radical Sources Within a Rural Forest Canopy

Organic peroxy (RO2) and hydroperoxy (HO2) radicals are key intermediates in the photochemical processes that generate ozone, secondary organic aerosol and reactive nitrogen reservoirs throughout the troposphere. In regions with ample biogenic hydrocarbons, the richness and complexity of peroxy radical chemistry presents a significant challenge to current-generation models, especially given the scarcity of measurements in such environments. We present peroxy radical observations acquired within a Ponderosa pine forest during the summer 2010 Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen - Rocky Mountain Organic Carbon Study (BEACHON-ROCS). Total peroxy radical mixing ratios reach as high as 180 pptv and are among the highest yet recorded. Using the comprehensive measurement suite to constrain a near-explicit 0-D box model, we investigate the sources, sinks and distribution of peroxy radicals below the forest canopy. The base chemical mechanism underestimates total peroxy radicals by as much as a factor of 3. Since primary reaction partners for peroxy radicals are either measured (NO) or under-predicted (HO2 and RO2, i.e. self-reaction), missing sources are the most likely explanation for this result. A close comparison of model output with observations reveals at least two distinct source signatures. The first missing source, characterized by a sharp midday maximum and a strong dependence on solar radiation, is consistent with photolytic production of HO2. The diel profile of the second missing source peaks in the afternoon and suggests a process that generates RO2 independently of sun-driven photochemistry, such as ozonolysis of reactive hydrocarbons. The maximum magnitudes of these missing sources (approximately 120 and 50 pptv min−1, respectively) are consistent with previous observations alluding to unexpectedly intense oxidation within forests. We conclude that a similar mechanism may underlie many such observations.

atmosphere↗
NASA NTRSDate not supplied

Kamodo – An Adaptable Tool to Obtain and Compare Observations and Modeling Results

What is Kamodo? -Official NASA open-source project written in Python. -Building upon the functionalization of datasets. -It is a CCMC developed and maintained software tool for access, interpolation, and visualization of space weather models and data. -It allows model developers to represent simulation results as mathematical functions which may be manipulated directly by end users. -It handles unit conversion transparency and supports interactive science discovery through jupyter notebooks with minimal coding. -All Kamodo tools are accessible through Python, and all source code is publicly available on the Kamodo NASA GitHub repositories. -Kamodo does not generate model outputs. Users need to acquire the desired model outputs before they can be functionalized by Kamodo.

Kamodo↗
NASA NTRS2014

Gamma-Ray Emission in Dissipative Pulsar Magnetospheres: from Theory to Fermi Observations

We compute the patterns of gamma-ray emission due to curvature radiation in dissipative pulsar magnetospheres. Our ultimate goal is to construct macrophysical models that are able to reproduce the observed gamma-ray light curve phenomenology recently published in the Second Fermi Pulsar Catalog. We apply specific forms of Ohm's law on the open field lines using a broad range for the macroscopic conductivity values that result in solutions ranging, from near-vacuum to near-force-free. Using these solutions, we generate model gamma-ray light curves by calculating realistic trajectories and Lorentz factors of radiating particles under the influence of both the accelerating electric fields and curvature radiation reaction. We further constrain our models using the observed dependence of the phase lags between the radio and gamma-ray emission on the gamma-ray peak separation. We perform a statistical comparison of our model radio-lag versus peak-separation diagram and the one obtained for the Fermi standard pulsars. We find that for models of uniform conductivity over the entire open magnetic field line region, agreement with observations favors higher values of this parameter. We find, however, significant improvement in fitting the data with models that employ a hybrid form of conductivity, specifically, infinite conductivity interior to the light cylinder and high but finite conductivity on the outside. In these models the gamma-ray emission is produced in regions near the equatorial current sheet but modulated by the local physical properties. These models have radio lags near the observed values and statistically best reproduce the observed light curve phenomenology. Additionally, they also produce GeV photon cut-off energies.

stars↗
NASA NTRS2001

Medium Fidelity Simulation of Oxygen Tank Venting

The item to he cleared is a medium-fidelity software simulation model of a vented cryogenic tank. Such tanks are commonly used to transport cryogenic liquids such as liquid oxygen via truck, and have appeared on liquid-fueled rockets for decades. This simulation model works with the HCC simulation system that was developed by Xerox PARC and NASA Ames Research Center. HCC has been previously cleared for distribution. When used with the HCC software, the model generates simulated readings for the tank pressure and temperature as the simulated cryogenic liquid boils off and is vented. Failures (such as a broken vent valve) can be injected into the simulation to produce readings corresponding to the failure. Release of this simulation will allow researchers to test their software diagnosis systems by attempting to diagnose the simulated failure from the simulated readings. This model does not contain any encryption software nor can it perform any control tasks that might be export controlled.

Sweet, Adam↗
NASA NTRS2022

Microstructure Segmentation with Deep Learning Encoders Pre-Trained on a Large Microscopy Dataset

This study examined the improvement of microscopy segmentation accuracy by transfer learning from a large dataset of microscopy images called MicroNet. Many neural network encoder architectures, including VGG, Inception, and ResNet, were trained on over 100,000 labelled microscopy images from 54 classes. These pre-trained encoders were then embedded into multiple segmentation architectures including U-Net and DeepLabV3+ to evaluate segmentation performance on newly created benchmark microscopy datasets. Compared to ImageNet pre-training, models pre-trained on MicroNet generalized better to out-of-distribution micrographs taken under different imaging and sample conditions and were more accurate with less training data. When training with only a single Ni-superalloy image, pre-training on MicroNet produced a 72.2 percent reduction in relative segmentation error. These results suggest that transfer learning from large in-domain datasets generate models with learned feature representations that are more useful for downstream tasks and will likely improve any microscopy image analysis technique that can leverage pre-trained encoders.

machine learning↗
NASA NTRS2022

Microstructure Segmentation With Deep Learning Encoders Pre-Trained on a Large Microscopy Dataset

This study examined the improvement of microscopy segmentation intersection over union accuracy by transfer learning from a large dataset of microscopy images called MicroNet. Many neural network encoder architectures were trained on over 100,000 labeled microscopy images from 54 material classes. These pre-trained encoders were then embedded into multiple segmentation architectures including UNet and DeepLabV3+ to evaluate segmentation performance on created benchmark microscopy datasets. Compared to ImageNet pre-training, models pre-trained on MicroNet generalized better to out-of-distribution micrographs taken under different imaging and sample conditions and were more accurate with less training data. When training with only a single Ni-superalloy image, pre-training on MicroNet produced a 72.2% reduction in relative intersection over union error. These results suggest that transfer learning from large in-domain datasets generate models with learned feature representations that are more useful for downstream tasks and will likely improve any microscopy image analysis technique that can leverage pre-trained encoders.

machine learning↗
NASA NTRS1983

Using PAFEC as a preprocessor for COSMIC/NASTRAN

Programs for Automatic Finite Element Calculations (PAFEC) is a general purpose, three dimensional linear and nonlinear finite element program (ref. 1). PAFEC's features include free format input utilizing engineering keywords, powerful mesh generating facilities, sophisticated data base management procedures, and extensive data validation checks. Presented here is a description of a software interface that permits PAFEC to be used as a preprocessor for COSMIC/NASTRAN. This user friendly software, called PAFCOS, frees the stress analyst from the laborious and error prone procedure of creating and debugging a rigid format COSMIC/NASTRAN bulk data deck. By interactively creating and debugging a finite element model with PAFEC, thus taking full advantage of the free format engineering keyword oriented data structure of PAFEC, the amount of time spent during model generation can be drastically reduced. The PAFCOS software will automatically convert a PAFEC data structure into a COSMIC/NASTRAN bulk data deck. The capabilities and limitations of the PAFCOS software are fully discussed in the following report.

Gray, W. H.↗
NASA NTRS2023

Statistical Approach on Utilizing Ground-Based Experiments to Model Break-Up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office, the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples in the SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗
NASA NTRSDate not supplied

Statistical Approach on Utilizing Ground-based Experiments to Model Break-up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office; the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples as with as with the NASA SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗
NASA NTRS1986

A finite element approach for solution of the 3D Euler equations

Prediction of thermal deformations and stresses has prime importance in the design of the next generation of high speed flight vehicles. Aerothermal load computations for complex three-dimensional shapes necessitate development of procedures to solve the full Navier-Stokes equations. This paper details the development of a three-dimensional inviscid flow approach which can be extended for three-dimensional viscous flows. A finite element formulation, based on a Taylor series expansion in time, is employed to solve the compressible Euler equations. Model generation and results display are done using a commercially available program, PATRAN, and vectorizing strategies are incorporated to ensure computational efficiency. Sample problems are presented to demonstrate the validity of the approach for analyzing high speed compressible flows.

Thornton, E. A.↗
NASA NTRS1983

Numerical simulation of large-scale ocean-atmosphere coupling and the ocean's role in climate

The problem of reducing model generated sigma coordinate data to pressure levels is considered. A mass consistent scheme for performing budget analyses is proposed, wherein variables interpolated to a given pressure level are weighted according to the mass between a nominal pressure level above and either a nominal pressure level below or the Earth's surface, whichever is closer. The method is applied to the atmospheric energy cycle as simulated by the OSU two level atmospheric general circulation model. The results are more realistic than sigma coordinate analyses with respect to eddy decomposition, and are in agreement with the sigma coordinate evaluation of the numerical energy sink. Comparison with less sophisticated budget schemes indicates superiority locally, but not globally.

Gates, W. L.↗
NASA NTRS2011

Modeling Weather Impact on Ground Delay Programs

Scheduled arriving aircraft demand may exceed airport arrival capacity when there is abnormal weather at an airport. In such situations, Federal Aviation Administration (FAA) institutes ground-delay programs (GDP) to delay flights before they depart from their originating airports. Efficient GDP planning depends on the accuracy of prediction of airport capacity and demand in the presence of uncertainties in weather forecast. This paper presents a study of the impact of dynamic airport surface weather on GDPs. Using the National Traffic Management Log, effect of weather conditions on the characteristics of GDP events at selected busy airports is investigated. Two machine learning methods are used to generate models that map the airport operational conditions and weather information to issued GDP parameters and results of validation tests are described.

Wang, Yao↗
NASA NTRS1997

Quelling Cabin Noise in Turboprop Aircraft via Active Control

Cabin noise in turboprop aircraft causes passenger discomfort, airframe fatigue, and employee scheduling constraints due to OSHA standards for exposure to high levels of noise. The noise levels in the cabins of turboprop aircraft are typically 10 to 30 decibels louder than commercial jet noise levels. However. unlike jet noise the turboprop noise spectrum is dominated by a few low frequency tones. Active structural acoustic control is a method in which the control inputs (used to reduce interior noise) are applied directly to a vibrating structural acoustic system. The control concept modeled in this work is the application of in-plane force inputs to piezoceramic patches bonded to the wall of a vibrating cylinder. The goal is to determine the force inputs and locations for the piezoceramic actuators so that: (1) the interior noise is effectively damped; (2) the level of vibration of the cylinder shell is not increased; and (3) the power requirements needed to drive the actuators are not excessive. Computational experiments for data taken from a computer generated model and from a laboratory test article at NASA Langley Research Center are provided.

Kincaid, Rex K.↗
NASA NTRS1998

Stochastic feedback and the regulation of biological rhythms

We propose a general approach to the question of how biological rhythms spontaneously self-regulate, based on the concept of "stochastic feedback". We illustrate this approach by considering at a coarse-grained level the neuroautonomic regulation of the heart rate. The model generates complex dynamics and successfully acounts for key characteristics of cardiac variability, including the l/f power spectrum, the functional form and scaling of the distribution of variations, and correlations in the Fourier phases indicating nonlinear dynamics.

NASA Discipline Cardiopulmonary↗
NASA NTRS2017

A Comparison of Three Random Number Generators for Aircraft Dynamic Modeling Applications

Three random number generators, which produce Gaussian white noise sequences, were compared to assess their suitability in aircraft dynamic modeling applications. The first generator considered was the MATLAB (registered) implementation of the Mersenne-Twister algorithm. The second generator was a website called Random.org, which processes atmospheric noise measured using radios to create the random numbers. The third generator was based on synthesis of the Fourier series, where the random number sequences are constructed from prescribed amplitude and phase spectra. A total of 200 sequences, each having 601 random numbers, for each generator were collected and analyzed in terms of the mean, variance, normality, autocorrelation, and power spectral density. These sequences were then applied to two problems in aircraft dynamic modeling, namely estimating stability and control derivatives from simulated onboard sensor data, and simulating flight in atmospheric turbulence. In general, each random number generator had good performance and is well-suited for aircraft dynamic modeling applications. Specific strengths and weaknesses of each generator are discussed. For Monte Carlo simulation, the Fourier synthesis method is recommended because it most accurately and consistently approximated Gaussian white noise and can be implemented with reasonable computational effort.

Grauer, Jared A.↗
NASA NTRS2001

Three-dimensional tissue assemblies: novel models for the study of Salmonella enterica serovar Typhimurium pathogenesis

The lack of readily available experimental systems has limited knowledge pertaining to the development of Salmonella-induced gastroenteritis and diarrheal disease in humans. We used a novel low-shear stress cell culture system developed at the National Aeronautics and Space Administration in conjunction with cultivation of three-dimensional (3-D) aggregates of human intestinal tissue to study the infectivity of Salmonella enterica serovar Typhimurium for human intestinal epithelium. Immunohistochemical characterization and microscopic analysis of 3-D aggregates of the human intestinal epithelial cell line Int-407 revealed that the 3-D cells more accurately modeled human in vivo differentiated tissues than did conventional monolayer cultures of the same cells. Results from infectivity studies showed that Salmonella established infection of the 3-D cells in a much different manner than that observed for monolayers. Following the same time course of infection with Salmonella, 3-D Int-407 cells displayed minimal loss of structural integrity compared to that of Int-407 monolayers. Furthermore, Salmonella exhibited significantly lower abilities to adhere to, invade, and induce apoptosis of 3-D Int-407 cells than it did for infected Int-407 monolayers. Analysis of cytokine expression profiles of 3-D Int-407 cells and monolayers following infection with Salmonella revealed significant differences in expression of interleukin 1alpha (IL-1alpha), IL-1beta, IL-6, IL-1Ra, and tumor necrosis factor alpha mRNAs between the two cultures. In addition, uninfected 3-D Int-407 cells constitutively expressed higher levels of transforming growth factor beta1 mRNA and prostaglandin E2 than did uninfected Int-407 monolayers. By more accurately modeling many aspects of human in vivo tissues, the 3-D intestinal cell model generated in this study offers a novel approach for studying microbial infectivity from the perspective of the host-pathogen interaction.

NASA Discipline Environmental Health↗
NASA NTRS2018

Introduction to Big Earth Data Applications

Climate and weather modeling generate enormous volumes that make iterative analysis challenging, spurring the development of new ways to work with the data. A theme going across applications is the need to identify and highlight "interesting" data for the scientist to focus on. Operational applications often scale up from small, local studies to larger spatial scales with more analysis targets.

parallel processing (computers)↗