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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 343 records · Page 19

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NASA NTRS2006

Chill Down Process of Hydrogen Transport Pipelines

A pseudo-steady model has been developed to predict the chilldown history of pipe wall temperature in the horizontal transport pipeline for cryogenic fluids. A new film boiling heat transfer model is developed by incorporating the stratified flow structure for cryogenic chilldown. A modified nucleate boiling heat transfer correlation for cryogenic chilldown process inside a horizontal pipe is proposed. The efficacy of the correlations is assessed by comparing the model predictions with measured values of wall temperature in several azimuthal positions in a well controlled experiment by Chung et al. (2004). The computed pipe wall temperature histories match well with the measured results. The present model captures important features of thermal interaction between the pipe wall and the cryogenic fluid, provides a simple and robust platform for predicting pipe wall chilldown history in long horizontal pipe at relatively low computational cost, and builds a foundation to incorporate the two-phase hydrodynamic interaction in the chilldown process.

Mei, Renwei↗

NASA NTRS2016

Prediction of Weather Impacts on Airport Arrival Meter Fix Capacity

This paper introduces a data driven model for predicting airport arrival capacity with a look-ahead time 2-8 hour forecast. The model is suitable for air traffic flow management by explicitly investigating the impact of convective weather on airport arrival meter fix throughput. Estimation of the arrival airport capacity under arrival meter fix flow constraints due to severe weather is an important part of Air Traffic Management (ATM). Airport arrival capacity can be reduced if one or more airport arrival meter fixes are partially or completely blocked by convective weather. When the predicted airport arrival demands exceed the predicted available airport's arrival capacity for a sustained period, Ground Delay Program (GDP) operations will be triggered by ATM system. Serious imbalances between demand and capacity occur most frequently when the airport capacity is severely degraded due to either bad airport terminal surface weather or inclement convective weather around airport arrival fixes. A model that predicts the weather-impacted airport arrival meter fix throughput may help ATM personnel to plan GDP operations more efficiently. This paper identifies the characteristics of air traffic flow across arrival meter fixes at Newark Liberty International Airport (EWR). The proposed approach, based on machine-learning methods, is developed to predict the weather impacted EWR arrival Meter Fix (MF) throughput. Sector forecast coverage is used to envision the weather impact on airport arrival MF flow, and the validation is accomplished by using Convective Weather Avoidance Model (CWAM) 0.5 to 2-hour and Collaborative Convective Forecast Product (CCFP) 4 to 8-hour look-ahead forecast data for the period of April-September in 2014. Furthermore, the regression tree ensemble learning of random forests approach for translating a sector forecast coverage model to an EWR arrival meter fix throughput model is examined. The results suggest that ATM decision makers in charge of MF flow control and GDP planning may benefit from adopting the airport arrival meter capacity prediction models to estimate the inclement weather impacts.

Wang, Yao X.↗

NASA NTRS2000

Active Control of Wind-Tunnel Model Aeroelastic Response Using Neural Networks

NASA Langley Research Center, Hampton, VA 23681 Under a joint research and development effort conducted by the National Aeronautics and Space Administration and The Boeing Company (formerly McDonnell Douglas) three neural-network based control systems were developed and tested. The control systems were experimentally evaluated using a transonic wind-tunnel model in the Langley Transonic Dynamics Tunnel. One system used a neural network to schedule flutter suppression control laws, another employed a neural network in a predictive control scheme, and the third employed a neural network in an inverse model control scheme. All three of these control schemes successfully suppressed flutter to or near the limits of the testing apparatus, and represent the first experimental applications of neural networks to flutter suppression. This paper will summarize the findings of this project.

Scott, Robert C.↗

NASA NTRS1994

Object-oriented model-driven control

A monitoring and control subsystem architecture has been developed that capitalizes on the use of modeldriven monitoring and predictive control, knowledge-based data representation, and artificial reasoning in an operator support mode. We have developed an object-oriented model of a Controlled Ecological Life Support System (CELSS). The model based on the NASA Kennedy Space Center CELSS breadboard data, tracks carbon, hydrogen, and oxygen, carbodioxide, and water. It estimates and tracks resorce-related parameters such as mass, energy, and manpower measurements such as growing area required for balance. We are developing an interface with the breadboard systems that is compatible with artificial reasoning. Initial work is being done on use of expert systems and user interface development. This paper presents an approach to defining universally applicable CELSS monitor and control issues, and implementing appropriate monitor and control capability for a particular instance: the KSC CELSS Breadboard Facility.

Drysdale, A.↗

NASA NTRS2015

Numerical Investigation of Microgravity Tank Pressure Rise Due to Boiling

The ability to control self-pressurization in cryogenic storage tanks is essential for NASAs long-term space exploration missions. Predictions of the tank pressure rise in Space are needed in order to inform the microgravity design and optimization process. Due to the fact that natural convection is very weak in microgravity, heat leaks into the tank can create superheated regions in the liquid. The superheated regions can instigate microgravity boiling, giving rise to pressure spikes during self-pressurization. In this work, a CFD model is developed to predict the magnitude and duration of the microgravity pressure spikes. The model uses the Schrage equation to calculate the mass transfer, with a different accommodation coefficient for evaporation at the interface, condensation at the interface, and boiling in the bulk liquid. The implicit VOF model was used to account for the moving interface, with bounded second order time discretization. Validation of the models predictions was carried out using microgravity data from the Tank Pressure Control Experiment, which flew aboard the Space Shuttle Mission STS-52. Although this experiment was meant to study pressurization and pressure control, it underwent boiling during several tests. The pressure rise predicted by the CFD model compared well with the experimental data. The ZBOT microgravity experiment is scheduled to fly on February 2016 aboard the ISS. The CFD model was also used to perform simulations for setting parametric limits for the Zero-Boil-Off Tank (ZBOT) Experiments Test Matrix in an attempt to avoid boiling in the majority of the test runs that are aimed to study pressure increase rates during self-pressurization. *Supported in part by NASA ISS Physical Sciences Research Program, NASA HQ, USA

pressure rise↗

NASA NTRS2000

Results From F-18B Stability and Control Parameter Estimation Flight Tests at High Dynamic Pressures

A maximum-likelihood output-error parameter estimation technique has been used to obtain stability and control derivatives for the NASA F-18B Systems Research Aircraft. This work has been performed to support flight testing of the active aeroelastic wing (AAW) F-18A project. The goal of this research is to obtain baseline F-18 stability and control derivatives that will form the foundation of the aerodynamic model for the AAW aircraft configuration. Flight data have been obtained at Mach numbers between 0.85 and 1.30 and at dynamic pressures ranging between 600 and 1500 lbf/sq ft. At each test condition, longitudinal and lateral-directional doublets have been performed using an automated onboard excitation system. The doublet maneuver consists of a series of single-surface inputs so that individual control-surface motions cannot be correlated with other control-surface motions. Flight test results have shown that several stability and control derivatives are significantly different than prescribed by the F-18B aerodynamic model. This report defines the parameter estimation technique used, presents stability and control derivative results, compares the results with predictions based on the current F-18B aerodynamic model, and shows improvements to the nonlinear simulation using updated derivatives from this research.

Moes, Timothy R.↗

NASA NTRS1977

Theory for passive microwave remote sensing of near-surface soil moisture

The theory of microwave thermal emission from a nonscattering half-space medium is developed for application to regions with nonuniform subsurface soil-moisture and temperature variations. A coherent stratified model is presented which is valid for nonuniform temperature profiles and rapidly varying moisture profiles, under which conditions the commonly used emissivity and radiative-transfer approaches become inaccurate. For naturally occurring profiles the stratified model gives more accurate results than the other approaches at frequencies below about 4 GHz. Experimental results from ground-based radiometric observations of a controlled target area compare systematically with brightness temperatures predicted from the theoretical model to within approximately 10 K. Results of dielectric-constant measurements of the sand are given at seven frequencies in the microwave range and for moisture contents in the range from 0% to 30% by volume. By using this model, the thermal microwave emission spectrum is computed for a number of representative moisture and temperature profiles in the frequency range from 0.25 to 25 GHz.

Njoku, E. G.↗

NASA NTRS1998

Predicting lettuce canopy photosynthesis with statistical and neural network models

An artificial neural network (NN) and a statistical regression model were developed to predict canopy photosynthetic rates (Pn) for 'Waldman's Green' leaf lettuce (Latuca sativa L.). All data used to develop and test the models were collected for crop stands grown hydroponically and under controlled-environment conditions. In the NN and regression models, canopy Pn was predicted as a function of three independent variables: shootzone CO2 concentration (600 to 1500 micromoles mol-1), photosynthetic photon flux (PPF) (600 to 1100 micromoles m-2 s-1), and canopy age (10 to 20 days after planting). The models were used to determine the combinations of CO2 and PPF setpoints required each day to maintain maximum canopy Pn. The statistical model (a third-order polynomial) predicted Pn more accurately than the simple NN (a three-layer, fully connected net). Over an 11-day validation period, average percent difference between predicted and actual Pn was 12.3% and 24.6% for the statistical and NN models, respectively. Both models lost considerable accuracy when used to determine relatively long-range Pn predictions (> or = 6 days into the future).

Non-NASA Center↗

NASA NTRS1981

Experimental validation of a numerical model predicting the charging characteristics of Teflon and Kapton under electron beam irradiation

The effect differential charging of spacecraft thermal control surfaces is assessed by studying the dynamics of the charging process. A program to experimentally validate a computer model of the charging process was established. Time resolved measurements of the surface potential were obtained for samples of Kapton and Teflon irradiated with a monoenergetic electron beam. Results indicate that the computer model and experimental measurements agree well and that for Teflon, secondary emission is the governing factor. Experimental data indicate that bulk conductivities play a significant role in the charging of Kapton.

Hazelton, R. C.↗

NASA NTRS2000

Soil Moisture Memory in Climate Models

Water balance considerations at the soil surface lead to an equation that relates the autocorrelation of soil moisture in climate models to (1) seasonality in the statistics of the atmospheric forcing, (2) the variation of evaporation with soil moisture, (3) the variation of runoff with soil moisture, and (4) persistence in the atmospheric forcing, as perhaps induced by land atmosphere feedback. Geographical variations in the relative strengths of these factors, which can be established through analysis of model diagnostics and which can be validated to a certain extent against observations, lead to geographical variations in simulated soil moisture memory and thus, in effect, to geographical variations in seasonal precipitation predictability associated with soil moisture. The use of the equation to characterize controls on soil moisture memory is demonstrated with data from the modeling system of the NASA Seasonal-to-Interannual Prediction Project.

Koster, Randal D.↗

NASA NTRS2020

Autonomous Real-Time Global Aerodynamic Modeling in the Frequency Domain

A method for autonomous real-time global aerodynamic modeling is developed and explained. Local real-time frequency-domain estimates of stability and control derivatives are assembled over the flight envelope as a function of nominal flight condition, accounting for uncertainty in the individual local model parameter estimates. Combining this with real-time estimates of low-frequency aerodynamics in the time domain produces a real-time global aerodynamic model with good prediction capability, simple evaluation of local stability and control derivatives, insight into the aerodynamic dependencies, and the ability to capture local variations in the aerodynamic dependencies throughout the flight envelope. The technique is demonstrated using data from an F-16 nonlinear simulation and flight test data from a subscale aircraft.

Eugene A Morelli↗

NASA NTRS1972

Control theory for random systems

A survey is presented of the current knowledge available for designing and predicting the effectiveness of controllers for dynamic systems which can be modeled by ordinary differential equations. A short discussion of feedback control is followed by a description of deterministic controller design and the concept of system state. The need for more realistic disturbance models led to the use of stochastic process concepts, in particular the Gauss-Markov process. A compensator controlled system, with random forcing functions, random errors in the measurements, and random initial conditions, is treated as constituting a Gauss-Markov random process; hence the mean-square behavior of the controlled system is readily predicted. As an example, a compensator is designed for a helicopter to maintain it in hover in a gusty wind over a point on the ground.

Bryson, A. E., Jr.↗

NASA NTRS2006

Dependence of Microelastic-plastic Nonlinearity of Martensitic Stainless Steel on Fatigue Damage Accumulation

Self-organized substructural arrangements of dislocations formed in wavy slip metals during cyclic stress-induced fatigue produce substantial changes in the material microelastic-plastic nonlinearity, a quantitative measure of which is the nonlinearity parameter Beta extracted from acoustic harmonic generation measurements. The contributions to Beta from the substructural evolution of dislocations and crack growth for fatigued martensitic 410Cb stainless steel are calculated from the Cantrell model as a function of percent full fatigue life to fracture. A wave interaction factor f(sub WI) is introduced into the model to account experimentally for the relative volume of material fatigue damage included in the volume of material swept out by an interrogating acoustic wave. For cyclic stress-controlled loading at 551 MPa and f(sub WI) = 0.013 the model predicts a monotonic increase in Beta from dislocation substructures of almost 100 percent from the virgin state to roughly 95 percent full life. Negligible contributions from cracks are predicted in this range of fatigue life. However, over the last five percent of fatigue life the model predicts a rapid monotonic increase of Beta by several thousand percent that is dominated by crack growth. The theoretical predictions are in good agreement with experimental measurements of 410Cb stainless steel samples fatigued in uniaxial, stress-controlled cyclic loading at 551 MPa from zero to full tensile load with a measured f(sub WI) of 0.013.

Cantrell, John H.↗

NASA NTRS2017

Novel Estimation of Pilot Performance Characteristics

Two mechanisms internal to the pilot that affect performance during a tracking task are: 1) Pilot equalization (i.e. lead/lag); and 2) Pilot gain (i.e. sensitivity to the error signal). For some applications McRuer's Crossover Model can be used to anticipate what equalization will be employed to control a vehicle's dynamics. McRuer also established approximate time delays associated with different types of equalization - the more cognitive processing that is required due to equalization difficulty, the larger the time delay. However, the Crossover Model does not predict what the pilot gain will be. A nonlinear pilot control technique, observed and coined by the authors as 'amplitude clipping', is shown to improve stability, performance, and reduce workload when employed with vehicle dynamics that require high lead compensation by the pilot. Combining linear and nonlinear methods a novel approach is used to measure the pilot control parameters when amplitude clipping is present, allowing precise measurement in real time of key pilot control parameters. Based on the results of an experiment which was designed to probe workload primary drivers, a method is developed that estimates pilot spare capacity from readily observable measures and is tested for generality using multi-axis flight data. This paper documents the initial steps to developing a novel, simple objective metric for assessing pilot workload and its variation over time across a wide variety of tasks. Additionally, it offers a tangible, easily implementable methodology for anticipating a pilot's operating parameters and workload, and an effective design tool. The model shows promise in being able to precisely predict the actual pilot settings and workload, and observed tolerance of pilot parameter variation over the course of operation. Finally, an approach is proposed for generating Cooper-Harper ratings based on the workload and parameter estimation methodology.

Human pilot models↗

NASA NTRS2017

Impact of a Regional Drought on Terrestrial Carbon Fluxes and Atmospheric Carbon: Results from a Coupled Carbon Cycle Model

Understanding the underlying processes that control the carbon cycle is key to predicting future global change. Much of the uncertainty in the magnitude and variability of the atmospheric carbon dioxide (CO2) stems from uncertainty in terrestrial carbon fluxes, and the relative impacts of temperature and moisture variations on regional and global scales are poorly understood. Here we investigate the impact of a regional drought on terrestrial carbon fluxes and CO2 mixing ratios over North America using the NASA Goddard Earth Observing System (GEOS) Model. Results show a sequence of changes in carbon fluxes and atmospheric CO2, induced by the drought. The relative contributions of meteorological changes to the neighboring carbon dynamics are also presented. The coupled modeling approach allows a direct quantification of the impact of the regional drought on local and proximate carbon exchange at the land surface via the carbon-water feedback processes.

CO↗

NASA NTRS1986

Effects of wing modification on an aircraft's aerodynamic parameters as determined from flight data

A study of the effects of four wing-leading-edge modifications on a general aviation aircraft's stability and control parameters is presented. Flight data from the basic aircraft configuration and configurations with wing modifications are analyzed to determine each wing geometry's stability and control parameters. The parameter estimates and aerodynamic model forms are obtained using the stepwise regression and maximum likelihood techniques. The resulting parameter estimates and aerodynamic models are verified using vortex-lattice theory and by analysis of each model's ability to predict aircraft behavior. Comparisons of the stability and control derivative estimates from the basic wing and the four leading-edge modifications are accomplished so that the effects of each modification on aircraft stability and control derivatives can be determined.

Hess, R. A.↗

NASA NTRS1989

Dynamic analysis of space structures including elastic, multibody, and control behavior

The problem is to develop analysis methods, modeling stategies, and simulation tools to predict with assurance the on-orbit performance and integrity of large complex space structures that cannot be verified on the ground. The problem must incorporate large reliable structural models, multi-body flexible dynamics, multi-tier controller interaction, environmental models including 1g and atmosphere, various on-board disturbances, and linkage to mission-level performance codes. All areas are in serious need of work, but the weakest link is multi-body flexible dynamics.

Pinson, Larry↗

NASA NTRS1972

Manual control models of industrial management

The industrial engineer is often required to design and implement control systems and organization for manufacturing and service facilities, to optimize quality, delivery, and yield, and minimize cost. Despite progress in computer science most such systems still employ human operators and managers as real-time control elements. Manual control theory should therefore be applicable to at least some aspects of industrial system design and operations. Formulation of adequate model structures is an essential prerequisite to progress in this area; since real-world production systems invariably include multilevel and multiloop control, and are implemented by timeshared human effort. A modular structure incorporating certain new types of functional element, has been developed. This forms the basis for analysis of an industrial process operation. In this case it appears that managerial controllers operate in a discrete predictive mode based on fast time modelling, with sampling interval related to plant dynamics. Successive aggregation causes reduced response bandwidth and hence increased sampling interval as a function of level.

Crossman, E. R. F. W.↗