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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Controlled environment life support system: Calcium-related leaf injuries on plants

A calcium related injury in lettuce termed tipburn was the focus of this study. It affects the young developing leaves as they become enclosed during head formation. It is a good model system to study because the injury can be induced with good predictability and lettuce is one of the crops chosen by the CELSS program for concentrated study. Investigations were undertaken to study a number of different procedures, that would have the potential for encouraging movement of calcium into the young developing leaves and to study the time course and pattern of calcium accumulation in developing leaves to provide a basis for developing effective control procedures for this injury.

Tibbitts, T. W.↗
NASA NTRS2020

Model Based Diagnostics and Prognostics Framework for Systems Health Management

In order to tackle and solve the system health prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. This presentation will cover a physics based-modeling approach implemented for case-studies in battery and composite structures for prognostics. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.

Banerjee, Portia↗
NASA NTRSDate not supplied

Predicting Thermal Response in a Li-ion Cell on a UAV Fight Profile

As the energy storage devices continue to "pack" more energy in a small space, any damage, battery component failure, manufacturing defect, or electrically abusing the battery can lead to catastrophic thermal runaway events. A catastrophic thermal event in a cell leads to high temperature, in some instances spewing of battery materials due to gas development from side reactions initiated due to high internal temperatures. Also, a thermal runaway event can propagate from a single "failed" cell to the pack in a battery pack, leading to a more significant event. Mitigating a thermal runaway event is important in the commercial and automotive sectors. However, preventing such events in an electric aircraft (or air taxis) is paramount due to the lack of alternatives in the event of a failure. Battery prognostics algorithms allow the prediction of state-of-charge (SOC) and end-of-life (EOL) of a Li-ion battery in a UAV (unmanned air vehicle) [1]. For this presentation, we will extend this two-level battery predictive algorithm to predict SOC, EOL, and estimated maximum temperature during a simulated flight. The model is extended by integrating a lumped physics-driven thermal model for high current densities [2]. The parameters used to control SOC and EOL are maximum storable charge, time constant for Li-ion diffusivity in the carbon particles, and internal cell resistance. Cycling leads to an increase in the heat generated by an aged Li-ion cell with a LiyCoO2 (LCO) cathode and a LixC6 (MCMB) anode. The aging of a cell leads to increase in SEI layer thickness, the diffusion time for the lithium ions inside the electrodes, and the local reaction rates, in addition to the thermodynamic abuse caused by fixed cycling voltages controlled by a Battery Management System. As the battery ages, the cell resistance increases, while the onset temperature of the thermal runaway decreases (depends on the cell chemistry and cell abuse history). Any large deviation of the cell temperature from the estimated (expected) value can identify a faulty cell. Since SEI decomposition has the lowest onset temperature in the series of reactions leading to thermal runaway, the model considers the self-heating rate of the SEI decomposition as onset temperature (similar to Ref. [3]). The parameters in the Arrhenius equation for the SEI heating rate depend on the number of cycles, the cell's operating temperature, and the cell's abuse history [4,5]. Coupling the electrochemical, thermal, and aging model allow the prognostic algorithm to estimate a typical cell voltage and temperature as a function of age (cycling and calendar), whose departure from measured values from the BMS is used to identify a safety event. In addition, we will present the results from two simulated flight scenarios for a UAV: typical and extreme, since the power requirements vary significantly during take-off, landing, and changing altitudes, while the power requirements remain low during the cruise. For this presentation, the power requirement for a battery pack in a UAV is scaled to a single cell. This cell is cycled through a simulated profile, and the data is collected and used to predict a safety event.

Li-ion↗
NASA NTRS2013

Modeling Weather Impact on Airport Arrival Miles-in-Trail Restrictions

When the demand for either a region of airspace or an airport approaches or exceeds the available capacity, miles-in-trail (MIT) restrictions are the most frequently issued traffic management initiatives (TMIs) that are used to mitigate these imbalances. Miles-intrail operations require aircraft in a traffic stream to meet a specific inter-aircraft separation in exchange for maintaining a safe and orderly flow within the stream. This stream of aircraft can be departing an airport, over a common fix, through a sector, on a specific route or arriving at an airport. This study begins by providing a high-level overview of the distribution and causes of arrival MIT restrictions for the top ten airports in the United States. This is followed by an in-depth analysis of the frequency, duration and cause of MIT restrictions impacting the Hartsfield-Jackson Atlanta International Airport (ATL) from 2009 through 2011. Then, machine-learning methods for predicting (1) situations in which MIT restrictions for ATL arrivals are implemented under low demand scenarios, and (2) days in which a large number of MIT restrictions are required to properly manage and control ATL arrivals are presented. More specifically, these predictions were accomplished by using an ensemble of decision trees with Bootstrap aggregation (BDT) and supervised machine learning was used to train the BDT binary classification models. The models were subsequently validated using data cross validation methods. When predicting the occurrence of arrival MIT restrictions under low demand situations, the model was able to achieve over all accuracy rates ranging from 84% to 90%, with false alarm ratios ranging from 10% to 15%. In the second set of studies designed to predict days on which a high number of MIT restrictions were required, overall accuracy rates of 80% were achieved with false alarm ratios of 20%. Overall, the predictions proposed by the model give better MIT usage information than what has been currently provided under current day operations. Traffic flow managers can use these predictions to identify potential MIT restrictions to eliminate (e.g., those occurring during low arrival demand periods), and to determine the days in which a significant number of restrictions may be required

Operation↗
NASA NTRS2005

Dynamics Modeling and Simulation of Large Transport Airplanes in Upset Conditions

As part of NASA's Aviation Safety and Security Program, research has been in progress to develop aerodynamic modeling methods for simulations that accurately predict the flight dynamics characteristics of large transport airplanes in upset conditions. The motivation for this research stems from the recognition that simulation is a vital tool for addressing loss-of-control accidents, including applications to pilot training, accident reconstruction, and advanced control system analysis. The ultimate goal of this effort is to contribute to the reduction of the fatal accident rate due to loss-of-control. Research activities have involved accident analyses, wind tunnel testing, and piloted simulation. Results have shown that significant improvements in simulation fidelity for upset conditions, compared to current training simulations, can be achieved using state-of-the-art wind tunnel testing and aerodynamic modeling methods. This paper provides a summary of research completed to date and includes discussion on key technical results, lessons learned, and future research needs.

Foster, John V.↗
NASA NTRS2014

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

aerosol optical depth↗
NASA NTRS1972

Low speed aerodynamic characteristics of a large scale model with a thin, highly swept, 2.67 aspect ratio wing having a cranked leading edge

The low speed aerodynamic characteristics of a large-scale model intended to represent advanced fixed-wing fighters have been investigated in the Ames 40 by 80 foot wind tunnel. The model possessed positive static longitudinal stability to nearly 28 deg angle of attack, the maximum tested, both with and without leading-edge flaps deflected. Lateral control with differentially deflected ailerons and a right wing spoiler simultaneously deployed as combined controls was only slightly greater than that with the differentially deflected ailerons deployed as a separate control without the spoiler. Measured lift and drag were in close agreement with that predicted by theory to about 14 deg angle of attack, including the prediction of lift due to 30 deg of trailing edge flap deflection. Estimated takeoff performance of an aircraft 4/3 the scale of the test model showed takeoff distances of less than 2000 ft.

Giulianetti, D. J.↗
NASA NTRS1971

Measurements, modeling, control and simulation - as applied to the human left ventricle for purposeful physiological monitoring.

Interdisciplinary engineering research effort in studying the intact human left ventricle has been employed to physiologically monitor the heart and to obtain its 'state-of-health' characteristics. The left ventricle was selected for this purpose because it plays a key role in supplying energy to the body cells. The techniques for measurement of the left ventricular geometry are described; the geometry is effectively displayed to bring out the abnormalities in cardiac function. Methods of mathematical modeling, which make it possible to determine the performance of the intact left ventricular muscle, are also described. Finally, features of a control system for the left ventricle for predicting the effect of certain physiological stress situations on the ventricle performance are discussed.

Ghista, D. N.↗
NASA NTRS1978

Some modern control techniques for human operator modeling and identification

Some recent results in quantitative modeling of the human operator are reviewed as well as a method for processing his input-output data. Modern control techniques are applied to the pilot operating in a dynamic compensatory tracking task. Trained pilots are known to behave in an optimal manner under fully stressed conditions. This has led to the development of an optimal control model of the human operator which takes his limitations into account. A rationale for determining the appropriate cost functions is determined. Experimental results indicate that the model can closely predict pilot performance in one- or two-axis tracking tasks. The model predicts pilot remnant (noise), error scores, and frequency response in both single-axis and multi-axis tracking tasks.

Shirley, R. S.↗
NASA NTRS1978

Prediction of plasma properties in mercury ion thrusters

A simplified theoretical model was developed which obtains to first order the plasma properties in the discharge chamber of a mercury ion thruster from basic thruster design and controllable operating parameters. The basic operation and design of ion thrusters is discussed, and the important processes which influence the plasma properties are described in terms of the design and control parameters. The conservation for mass, charge and energy were applied to the ion production region, which was defined as the region of the discharge chamber having as its outer boundary the surface of revolution of the innermost field line to intersect the anode. Mass conservation and the equations describing the various processes involved with mass addition and removal from the ion production region are satisfied by a Maxwellian electron density spatial distribution in that region.

Longhurst, G. R.↗
NASA NTRS1992

Mechanisms resulting in accreted ice roughness

Icing tests conducted on rotating cylinders in the BF Goodrich's Icing Research Facility indicate that a regular, deterministic, icing roughness pattern is typical. The roughness pattern is similar to kernels of corn on a cob for cylinders of diameter typical of a cob. An analysis is undertaken to determine the mechanisms which result in this roughness to ascertain surface scale and amplitude of roughness. Since roughness and the resulting augmentation of the convected heat transfer coefficient has been determined to most strongly control the accreted ice in ice prediction codes, the ability to predict a priori, location, amplitude and surface scale of roughness would greatly augment the capabilities of current ice accretion models.

Bilanin, Alan J.↗
NASA NTRS2004

Injection Induced Mixing in Flows Separating From Smooth Surfaces

An analytic model for predicting the effect of unsteady local surface injection on the flow separating from a streamlined body at angle of attack is proposed. The model uses the premise that separation control results from enhanced mixing along the shear layer that develops between the main stream and the fluid in the underlying recirculation zone. High-Reynolds-number asymptotic methods are used to connect the unsteady surface injection to an instability wave propagating on the separating shear layer and then to the large-scale coherent structures that produce the increased mixing. The results is a tool that can guide the choice of fluid-actuator parameters to maximize flow-control effectiveness and may also facilitate computer-based numerical experiments.

Adamczyk, John J.↗
NASA NTRS2008

ACCESS - A Science and Engineering Assessment of Space Coronagraph Concepts for the Direct Imaging and Spectroscopy of Exoplanetary Systems

Topics include and overview, science objectives, study objectives, coronagraph types, metrics, ACCESS observatory, laboratory validations, and summary. Individual slides examine ACCESS engineering approach, ACCESS gamut of coronagraph types, coronagraph metrics, ACCESS Discovery Space, coronagraph optical layout, wavefront control on the "level playing field", deformable mirror development for HCIT, laboratory testbed demonstrations, high contract imaging with the HCIT, laboratory coronagraph contrast and stability, model validation and performance predictions, HCIT coronagraph optical layout, Lyot coronagraph on the HCIT, pupil mapping (PIAA), shaped pupils, and vortex phase mask experiments on the HCIT.

exoplanets↗
NASA NTRS2011

Rocket Plume Scaling for Orion Wind Tunnel Testing

A wind tunnel test program was undertaken to assess the jet interaction effects caused by the various solid rocket motors used on the Orion Launch Abort Vehicle (LAV). These interactions of the external flowfield and the various rocket plumes can cause localized aerodynamic disturbances yielding significant and highly non-linear control amplifications and attenuations. This paper discusses the scaling methodologies used to model the flight plumes in the wind tunnel using cold air as the simulant gas. Comparisons of predicted flight, predicted wind tunnel, and measured wind tunnel forces-and-moments and plume flowfields are made to assess the effectiveness of the selected scaling methodologies.

Brauckmann, Gregory J.↗
NASA NTRS2011

Impact of Optimized land Surface Parameters on the Land-Atmosphere Coupling in WRF Simulations of Dry and Wet Extremes

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty module in NASA's Land Information System (LIS-OPT), whereby parameter sets are calibrated in the Noah land surface model and classified according to the land cover and soil type mapping of the observations and the full domain. The impact of the calibrated parameters on the a) spin up of land surface states used as initial conditions, and b) heat and moisture fluxes of the coupled (LIS-WRF) simulations are then assessed in terms of ambient weather, PBL budgets, and precipitation along with L-A coupling diagnostics. In addition, the sensitivity of this approach to the period of calibration (dry, wet, normal) is investigated. Finally, tradeoffs of computational tractability and scientific validity (e.g.,. relating to the representation of the spatial dependence of parameters) and the feasibility of calibrating to multiple observational datasets are also discussed.

Kumar, Sujay↗
NASA NTRS2012

Mars Science Laboratory Orbit Determination

Mars Science Laboratory (MSL) Orbit Determination (OD) met all requirements with considerable margin, MSL OD team developed spin signature removal tool and successfully used the tool during cruise, A novel approach was used for the MSL solar radiation pressure model and resulted in a very accurate model during the approach phase, The change in velocity for Attitude Control System (ACS) turns was successfully calibrated and with appropriate scale factor resulted in improved change in velocity prediction for future turns, All Trajectory Correction Maneuvers were successfully reconstructed and execution errors were well below the assumed pre-fight execution errors, The official OD solutions were statistically consistent throughout cruise and for OD solutions with different arc lengths as well, Only EPU-1 was sent to MSL. All other Entry Parameter Updates were waived, EPU-1 solution was only 200 m separated from final trajectory reconstruction in the B-plane

Mars Science Laboratory (MSL)↗
NASA NTRS2016

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account risks attributable to manufacturing, assembly, and process controls. These sources often dominate component level reliability or risk of failure probability. While consequences of failure is often understood in assessing risk, using predicted values in a risk model to estimate the probability of occurrence will likely underestimate the risk. Managers and decision makers often use the probability of occurrence in determining whether to accept the risk or require a design modification. Due to the absence of system level test and operational data inherent in aerospace applications, the actual risk threshold for acceptance may not be appropriately characterized for decision making purposes. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Hatfield, Glen S.↗
NASA NTRS2004

A Simulation Model of Carbon Cycling and Methane Emissions in Amazon Wetlands

An integrative carbon study is investigating the hypothesis that measured fluxes of methane from wetlands in the Amazon region can be predicted accurately using a combination of process modeling of ecosystem carbon cycles and remote sensing of regional floodplain dynamics. A new simulation model has been build using the NASA- CASA concept for predicting methane production and emission fluxes in Amazon river and floodplain ecosystems. Numerous innovations area being made to model Amazon wetland ecosystems, including: (1) prediction of wetland net primary production (NPP) as the source for plant litter decomposition and accumulation of sediment organic matter in two major vegetation classes - flooded forests (varzea or igapo) and floating macrophytes, (2) representation of controls on carbon processing and methane evasion at the diffusive boundary layer, through the lake water column, and in wetland sediments as a function of changes in floodplain water level, (3) inclusion of surface emissions controls on wetland methane fluxes, including variations in daily surface temperature and of hydrostatic pressure linked to water level fluctuations. A model design overview and early simulation results are presented.

Potter, Christopher↗