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Results for “conditional generative models”

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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

A LANDSAT study of ephemeral and perennial rangeland vegetation and soils

The author has identified the following significant results. Several methods of computer processing were applied to LANDSAT data for mapping vegetation characteristics of perennial rangeland in Montana and ephemeral rangeland in Arizona. The choice of optimal processing technique was dependent on prescribed mapping and site condition. Single channel level slicing and ratioing of channels were used for simple enhancement. Predictive models for mapping percent vegetation cover based on data from field spectra and LANDSAT data were generated by multiple linear regression of six unique LANDSAT spectral ratios. Ratio gating logic and maximum likelihood classification were applied successfully to recognize plant communities in Montana. Maximum likelihood classification did little to improve recognition of terrain features when compared to a single channel density slice in sparsely vegetated Arizona. LANDSAT was found to be more sensitive to differences between plant communities based on percentages of vigorous vegetation than to actual physical or spectral differences among plant species.

Bentley, R. G., Jr.↗
NASA NTRS1976

The interactions of solar arrays with electric thrusters

The generation of a charge-exchange plasma by a thruster, the transport of this plasma to the solar array, and the interaction of the solar array with the plasma after it arrives are all described. The generation of this plasma can be described accurately from thruster geometry and operating conditions. The transport of the charge-exchange plasma was studied experimentally with a 15 cm thruster. A model was developed for simple thruster-array configurations. A variety of experiments were surveyed for the interaction of the plasma at the solar array.

Kaufman, H. R.↗
NASA NTRS1986

On plasma disturbances caused by the motion of the Space Shuttle and small satellites - A comparison of in situ observations

Recent results regarding the interactions between a body and its environmental space plasma, made by charged particle probes mounted in the bay of the Space Shuttle Orbiter Columbia (STS 3 mission), are compared with earlier results, obtained from small ionospheric satellites, in an attempt to widen our scope of knowledge and understanding regarding such interactions. The objective is to work toward a unified model of body-space plasma interactions in the solar system covering a variety of plasma and body conditions. The comparisons focus mainly on (1) the (wake/ram) current ratio; (2) the generation of charged particle density fluctuations (indicative of plasma turbulence) around the body; and (3) the increase in electron temperature ahead and in the wake of the satellite. The main results of the comparison are that (1) the (wake/ram) current ratio (or current depletion in the wake) for the Orbiter is 1 to 2 orders of magnitude larger than the ratio for small ionospheric satellites; and (2) fluctuations in density (or turbulence) are observed for both 'large body' (Shuttle Orbiter) and 'smaller body' (standard ionospheric satellites). However, the cause of the turbulence may not be the same for both cases; (3) the results for the electronic temperature enhancement due to the Shuttle Orbiter are in contrast with measurements from smaller ionospheric satellites. A path to follow in future Shuttle experiments is suggested and caution that care be taken in interpreting local particle and field measurements.

Samir, U.↗
NASA NTRS1989

A further study of cumulus interactions and mergers - Three-dimensional simulations with trajectory analysis

Cumulus processes involved in the interaction and merging of clouds under the influence of different imposed conditions (including large-scale lifting forcing, environmental wind shear, and cloud microphysical processes) were studied using simulations with a three-dimensional model. The design of the study was to generate several convective clouds randomly inside the model domain, and then to observe and analyze the interactions and merging between the simulated clouds. Ten merged clouds were identified. Seven of these, each involving two previously separated clouds, generally lie along a line parallel to the initial environmental wind shear vector, while one (also a two-cloud system) lies along a line perpendicular to the wind shear vector prior to merging. The remaining two merging systems involve three parent clouds each; they are a combination of parallel and perpendicular cells. The merging mechanisms associated with three-cloud merging cases are studied by examining the temperature, pressure, and wind fields prior to, during, and following the merging.

Tao, Wei-Kuo↗
NASA NTRS1997

Interannual Fluctuations in Atmospheric Angular Momentum Simulated by the National Centers for Environmental Prediction Medium Range Forecast Model

An earlier study established the existence of globally coherent interannual fluctuations in atmospheric angular momentum (AAM), associated with the El Nino-Southern Oscillation (ENSO) cycle. In this paper, we pursue the origin and the structure of these fluctuations using an ensemble of experiments generated by the National Centers for Environmental Prediction, medium range forecast model version 9. In the control experiments, where the observed sea surface temperatures (SSTs) were used as the lower boundary conditions, the model captures the characteristic V-like structure in time-latitude plots of zonally averaged AAM, while experiments with climatological SSTs and those with either perpetual warm or cold ENSO conditions superimposed on the climatological SSTs failed to reproduce this structure. The numerical results indicate that these AAM structures are related to SST variations associated with transitions between different phases of the ENSO cycle and have both propagating and standing components. The largest zonal wind contribution from the levels studied (850, 500, and 200 hPa) is at 200 hPa, where the tropical convective outflow is the strongest. Composites of zonal wind and geopotential height show a clear relationship between the stages of the global AAM oscillation and the ENSO cycle. The strong similarity between the simulated and observed AAM series attests to the model's ability to realistically simulate the interannual response of the atmosphere to ENSO SST anomalies.

Mo, Kingtse C.↗
NASA NTRS2002

On-Board Generation of Three-Dimensional Constrained Entry Trajectories

A methodology for very fast design of 3DOF entry trajectories subject to all common inequality and equality constraints is developed. The approach make novel use of the well known quasi-equilibrium glide phenomenon in lifting entry as a center piece for conveniently enforcing the inequality constraints which are otherwise difficulty to handle. The algorithm is able to generate a complete feasible 3DOF entry trajectory, given the entry conditions, values of constraint parameters, and final conditions in about 2 seconds on a PC. Numerical simulations with the X-33 vehicle model for various entry missions to land at Kennedy Space Center will be presented.

Shen, Zuojun↗
NASA NTRS2002

Thrust Augmentation with Mixer/Ejector Systems

Older commercial aircraft often exceed FAA (Federal Aviation Administration) sideline noise regulations. The major problem is the jet noise associated with the high exhaust velocities of the low bypass ratio engines on such aircraft. Mixer/ejector exhaust systems can provide a simple means of reducing the jet noise on these aircraft by mixing cool ambient air with the high velocity engine gases before they are exhausted to ambient. This paper presents new information on thrust performance predictions, and thrust augmentation capabilities of mixer/ejectors. Results are presented from the recent development program of the patented Alternating Lobe Mixer Ejector Concept (ALMEC) suppressor system for the Gulfstream GII, GIIB and GIII aircraft. Mixer/ejector performance procedures are presented which include classical control volume analyses, compound compressible flow theory, lobed nozzle loss correlations and state of the art computational fluid dynamic predictions. The mixer/ejector thrust predictions are compared to subscale wind tunnel test model data and actual aircraft flight test measurements. The results demonstrate that a properly designed mixer/ejector noise suppressor can increase effective engine bypass ratio and generate large thrust gains at takeoff conditions with little or no thrust loss at cruise conditions. The cruise performance obtained for such noise suppressor systems is shown to be a strong function of installation effects on the aircraft.

Presz, Walter M., Jr.↗
NASA NTRS2012

HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis

Hybrid Diagnosis Engine (HyDE) is a general framework for stochastic and hybrid model-based diagnosis that offers flexibility to the diagnosis application designer. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. Several alternative algorithms are available for the various steps in diagnostic reasoning. This approach is extensible, with support for the addition of new modeling paradigms as well as diagnostic reasoning algorithms for existing or new modeling paradigms. HyDE is a general framework for stochastic hybrid model-based diagnosis of discrete faults; that is, spontaneous changes in operating modes of components. HyDE combines ideas from consistency-based and stochastic approaches to model- based diagnosis using discrete and continuous models to create a flexible and extensible architecture for stochastic and hybrid diagnosis. HyDE supports the use of multiple paradigms and is extensible to support new paradigms. HyDE generates candidate diagnoses and checks them for consistency with the observations. It uses hybrid models built by the users and sensor data from the system to deduce the state of the system over time, including changes in state indicative of faults. At each time step when observations are available, HyDE checks each existing candidate for continued consistency with the new observations. If the candidate is consistent, it continues to remain in the candidate set. If it is not consistent, then the information about the inconsistency is used to generate successor candidates while discarding the candidate that was inconsistent. The models used by HyDE are similar to simulation models. They describe the expected behavior of the system under nominal and fault conditions. The model can be constructed in modular and hierarchical fashion by building component/subsystem models (which may themselves contain component/ subsystem models) and linking them through shared variables/parameters. The component model is expressed as operating modes of the component and conditions for transitions between these various modes. Faults are modeled as transitions whose conditions for transitions are unknown (and have to be inferred through the reasoning process). Finally, the behavior of the components is expressed as a set of variables/ parameters and relations governing the interaction between the variables. The hybrid nature of the systems being modeled is captured by a combination of the above transitional model and behavioral model. Stochasticity is captured as probabilities associated with transitions (indicating the likelihood of that transition being taken), as well as noise on the sensed variables.

Narasimhan, Sriram↗
NASA NTRS2018

Impact of Aquarius and SMAP Sea Surface Salinity Observations on Seasonal Predictions of the 2015 El Nino

We assess the impact of satellite sea surface salinity (SSS) observations on dynamical ENSO forecasts for the big 2015 El Nino event. From March to June 2015, the availability of two overlapping satellite SSS instruments, Aquarius and SMAP, allows a unique opportunity to compare and contrast coupled forecasts generated with the benefit of these two satellite SSS observation types. Four distinct experiments are presented that include 1) freely evolving model SSS (i.e. no satellite SSS), relaxation to 2) climatological SSS (i.e. WOA13 (World Ocean Atlas 2013) SSS), 3) Aquarius and 4) SMAP initialization. Coupled hindcasts are generated from these initial conditions for March 2015. These forecasts are then validated against observations and evaluated with respect to the observed El Nino development.

Kovach, R.↗
NASA NTRSDate not supplied

Physics Informed Neural Nets for Systems Health Management

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Development in data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. The research work presents application of physics-informed neural nets application to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived and empirical equations, integrated with connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage.

Physics Informed↗
NASA NTRS1988

Fatigue life prediction modeling for turbine hot section materials

This paper presents a summary of the life prediction methods developed under the NASA Lewis Research Center's Hot Section Technology (HOST) program. A major objective of the fatigue and fracture efforts under the HOST program was to significantly improve the analytic life prediction tools used by the aeronautical gas turbine engine industry. This has been achieved in the areas of high-temperature thermal and mechanical fatigue of bare and coated high-temperature superalloys. Such technical improvements will eventually reduce life cycle costs. The cyclic crack initiation and propagation resistance of nominally isotropic polycrystalline alloys and highly anisotropic single crystal alloys has been addressed. A sizeable data base has been generated for three alloys [cast PWA 1455 (B-1900 + Hf), wrought Inconel 718, and cast single crystal PWA 1480] in bare and coated conditions. Two coatings systems, diffusion aluminide (PWA 273) and plasma sprayed MCrAIY overlay (PWA 286) were employed. Life prediction modeling efforts were devoted to creep-fatigue interaction, oxidation, coatings interactions, multiaxiality of stress-strain states, mean stress effects, cumulative damage, and thermomechanical fatigue. The fatigue crack initiation life models developed to date include the Cyclic Damage Accumulation (CDA) Model of Pratt & Whitney and the Total Strain Version of Strainrange Partitioning (TS-SRP) of NASA Lewis for nominally isotropic materials, and the Tensile Hysteretic Energy Model of Pratt & Whitney for anisotropic superalloys. The fatigue model being developed by the General Electric Company is based upon the concepts of Path-lndependent Integrals (PII) for describing cyclic crack growth under complex nonlinear response at the crack tip due to thermomechanical loading conditions. A micromechanistic oxidation crack extension model has been derived by researchers at Syracuse University. The models are described and discussed in the paper. Only limited verification has been achieved to-date as several of the technical programs are still in progress and the verification tasks are scheduled, quite naturally, near the conclusion of the program. To-date, efforts have concentrated on development of independent models for cyclic constitutive behavior, cyclic crack initiation, and cyclic crack propagation. The transition between crack initiation and crack propagation has not been thoroughly researched as yet, and the integration of these models into a unified life prediction method has not been addressed.

Metal fatigue↗
NASA NTRSDate not supplied

Artificial Intelligence (AI) Methods for Automating the Impact Tool Evidence Library

INTRODUCTION: The development of the Evidence Library for use with the IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) probability risk assessment tool involved a multilayered, time intensive process of data collection and analysis by subject matter experts from the Exploration Medical Capability (ExMC) Element Clinical and Science Team to produce clinical findings forms (CliFFs) for 120 medical conditions. Artificial Intelligence Large Language Models (LLMs) can be leveraged to facilitate this process, thus reducing labor and time. TOPIC: CliFFs contain information about medical conditions as they pertain to spaceflight. This includes condition definitions, incidence data, crew task impairment estimates caused by conditions, treatment protocols and references to literature used for gathering condition evidence. Guided by the Evidence Library Methods document and the CliFF development instructions, a team has leveraged Microsoft Azure AI services and open-source documentation to construct an AI-assisted automated pipeline for CliFF development. This process is designed to search, retrieve, and evaluate the applicable data, and ultimately generate a completed CliFF. The LLM evaluates the relevance of each of the source materials to spaceflight, either as direct evidence or as an analog. The model extracts keywords and generates brief summaries to enhance search and retrieval in later stages of CliFF development. For instance, it can calculate epidemiological statistical data, such as incidence rates and the likelihood of best or worst-case scenarios. APPLICATION: Large Language Models (LLMs) can efficiently summarize large amounts of text. Leveraging this technology will automate data retrieval and evidence gathering for medical databases, like the IMPACT tool, by aiding in the labor-intensive process of analyzing large bodies of literature and organizing it into a formatted document like a CliFF. This added efficiency will enable expeditious expansion of the Evidence Library with additional medical conditions and update previous CLiFFs as new technology becomes available.

Ali Al↗
NASA NTRS1990

Efficient parametric analysis of performance measures for communication networks

Efficient techniques for estimating performance measures in communication networks in a steady-state or transient setting are developed. These techniques may be used in a simulation environment or in connection with real-time observations. For Markov chain models, the recently proposed standard clock approach is extended, and a class of real-time algorithms for simultaneously generating multiple sample paths under different parameter sets is presented. Attention is focused on the link crash time estimation problem, where a 'crash' is defined as the first time a buffer overflows, given some initial conditions. An algorithm for estimating crash times under various traffic shocks is derived, where all estimates are obtained in parallel to an actual network's normal operation. An algorithm for crash time estimation of a G/D/1 link model is also derived using a different (perturbation-analysis-based) approach. Finally, extensive simulation results are provided to validate the proposed algorithms and compare them to brute-force simulation.

Cassandras, Christos G.↗
NASA NTRS2019

Scenario Complexity for Unmanned Aircraft System Traffic

This work introduces an approach to estimate the complexity of a low-altitude air traffic scenario involving multiple UASs using mathematical programming. Given a set of multi-point UAS flight trajectories, vehicle dynamics, and a conflict resolution algorithm, an abstract model is developed such that it can be solved quickly using a mathematical programming optimization software without running high-fidelity simulations that can be computationally expensive and may not suit real-time apA quick and accurate assessment of complexity for a given traffic scenario can help plan and schedule flights to alleviate traffic bottleneck and mitigate operation risks, especially for unmanned aerial system traffic management where high traffic density or complexity is expected. This work introduces a traffic scenario complexity metric that was constructed based on the number of potential conflicts weighted by the conflict resolution cost associated. The cost associated with a conflict is calculated based on the corresponding conflict resolution maneuvers. To obtain the conflict resolution maneuvers, a MILP-based optimization was formulated with the vehicle model and conflict management parameters incorporated. To evaluate the complexity metrics, an approach of using measurements from high-fidelity simulations was proposed. The scenario complexity measurements for 920 random-generated scenarios were obtained through high-fidelity simulations and treated as the ground truth. Two statistics methods: Pearson and Alternative Conditional Expectations were applied for analysis. The results showed that the number of flights has low correlation with the scenario complexity according to the correlation coefficients calculated by both methods. The Alternative Conditional Expectations method shows that the proposed scenario complexity metric has better correlation with the ground truth than the number of potential conflicts.plications. In the abstract model, each vehicle is represented by a time-varied vector associated with position, speed, and heading information. The total extra distance that aircraft need to divert from their original routes to avoid collisions is computed and used to setup a quadratic programming formula. The metrics including the number of conflicts and extra distances travelled by all vehicles are then utilized to estimate the complexity of a given UAS flight scenario. Results and verification against high-fidelity simulations will be provided in the final draft.

traffic complexity↗
NASA NTRS1998

Study of Boundary Layer Development in a Two-Stage Low-Pressure Turbine

Experimental data from jet-engine tests have indicated that unsteady blade row (wake) interactions and separation can have a significant impact on the efficiency of turbine stages. The effects of these interactions can be intensified in low-pressure turbine stages because of the low Reynolds number operating environment. Measured turbine efficiencies at takeoff can be as much as two points higher than those at cruise conditions. Thus, during the last decade a significant amount of effort has been put into determining the effects of transition and turbulence on the performance of low pressure turbine stages. Experimental investigations have been performed, for example, by Hodson et al. and Halstead et al. These investigations have helped identify/clarify the roles that factors such as the Reynolds number, free stream turbulence intensity, pressure gradient and curvature have in the generation of losses. In parallel to the experimental investigations, there have been significant analytical efforts to improve the modeling of transition. Examples of such efforts include the works of Mayle and Gostelow et al. These newer models show promise of providing accurate transition predictions over a wide range of flow conditions, although they have yet to be implemented into the numerical flow analyses used by the turbine design community. Some recent computational investigations of interest include the works of Chernobrovkin and Lakshminarayana and Eulitz and Engel. The focus of the current effort has been to -use a viscous, unsteady quasi-three-dimensional Navier-Stokes analysis to study boundary layer development in a two-stage low-pressure turbine. A two-layer algebraic turbulence model, along with a natural transition model and a bubble transition model, have been used, The geometry used in the simulations has been the subject of extensive experiments. The predicted results have been compared with experimental data, including airfoil loadings and time-averaged/unsteady integral boundary layer quantities.

Dorney, Daniel J.↗
NASA NTRS1983

The influence of the tropics on the prediction of ultralong waves. I - Tropical wind field

The effects of tropical wind data from the FGGE and tropical latent heating on numerical modeling of ultralong waves are considered in a two-part study. The model studied is the global fourth-order GLAS general circulation model, an energy-conserving format with horizontal differences calculated with fourth-order accuracy. Data assimilation experiments were performed with and without the wind data, with account taken of eastward and northward wind components, the geopotential height, and the relative humidity, all over pressure surfaces. The initial conditions were used to generate six pairs of forecasts, and the tropical wind error decreased after two days of prediction when the initial conditions contained the wind data. The deviations from the measured planetary wave data were attributed to differences in the initial rotational wind field, which varied on a three-day basis. The latent heat initial data had a five-day period and extended its influence beyond the tropical zone. The tropical heat sources sustained the tropical westerlies in the GLAS model, and removal of the tropical heat sources reversed the wind to easterlies.

Baker, W. E.↗
NASA NTRS1968

A second-generation /high-speed/ maximum power tracker for space applications.

During the past few years, considerable effort has been exerted by both industry and government to improve the performance of space power systems. One of the significant advances has been the development of practical Maximum Power-Point Tracking (MPPT) systems. This paper presents the background and evolution of a second-generation (high-speed) MPPT system capable of operation with solar arrays with rapidly fluctuating parameters due to mission operation (e.g., spin-stabilized spacecraft). An experimental model of the high-speed MPPT system has been constructed and tested. Results from these tests are presented herein. The second-generation MPPT system provides a means of efficient power conditioning that can result in significant increases over conventional systems in space-power system capability. Of additional importance is the applicability of the basic technology to all types of spacecraft, and the wide variety of power-system configurations with which the high-speed MPPT system concept may be used.

Clement A. Berard, Jr.↗
NASA NTRS1977

An empirical model for inverted-velocity-profile jet noise prediction

It is known that the noise generated by inverted-velocity-profile coaxial (without center plug) and coannular (with center plug) nozzles should be modeled as the combined contributions of various source regions and noise generation mechanisms. In this paper, an empirical noise-prediction model is described which considers the noise generated by two jet-mixing regions and two potential regions of shock/turbulence interaction. Results calculated from the empirical model are compared with model-scale experimental data for static and simulated flight conditions. These comparisons are made for cases where both streams are subsonic, where the outer stream is supersonic with the inner stream subsonic, and where both streams are supersonic. The cases considered cover a range of inner-to-outer-stream area ratios and include both coaxial and coannular nozzles. It is shown that the model gives reasonable predictions of absolute noise spectra and even better predictions of incremental changes.

Stone, J. R.↗