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At least 1,297 records · Page 72

Ponderomotive Force and Lower Hybrid Turbulence Effects in Space Plasmas Subjected to Large-Amplitude Low-Frequency Waves

In the auroral region, simultaneous occurrences of upward-flowing ions and field-aligned electrons have been observed by the Viking satellite. The occurrence is strongly correlated with large amplitude low frequency fluctuations of the electric field. Large-amplitude shear Alfven waves have also been observed by sounding rockets in the auroral ionosphere. When such LF waves are propagating in a plasma, a ponderomotive force and other types of waves are produced which may lead to significant effects on the plasma. This force is directed toward decreasing density, providing the electromagnetic lift of the background plasma and an increase of collisionless plasma expansion. We find that even for modest wave strengths, the influence on the outflowing oxygen ions can be dramatic, increasing the high-altitude density by orders of magnitude. It is also demonstrated that large-amplitude low-frequency waves (LFW) may generate lower hybrid waves (LHW) in the auroral zone. The excitation of LHW by a LF wave may lead to the appearance of an additional channel of energy transfer from, for example, Alfven or fast magnetosonic waves, to particles. This process then influences the formation of the plasma distribution function at the expense of acceleration in the tail of the distribution during the collapse of the LHW. The ion energization due to the LHW can be comparable with that produced by the ponderomotive force of the LFW. It is shown that the LH turbulence leads to equalization of the ponderomotive acceleration of the different ion species. The mechanism of LHW excitation due to the oxygen ion relative drift in a plasma subjected to low-frequency waves is used for analysis of Viking satellite data for events in the cusp/cleft region. It is found that, in some cases, such a mechanism leads to LHW energy densities and ion distribution functions close to those observed.

Khazanov, G. V.↗

Space Shuttle Transportation (Roll-Out) Loads Diagnostics

The Space Transportation System (STS) consists of three primary components; an Orbiter Vehicle, an External Fuel Tank, and two Solid Rocket Boosters. The Orbiter Vehicle and Solid Rocket Boosters are reusable components, and as such, they are susceptible to durability issues. Recently, the fatigue load spectra for these components have been updated to include load histories acquired during the rollout phase of the STS processing for flight. Using traditional program life assessment techniques, the incorporation of these "rollout" loads produced unacceptable life estimates for certain Orbiter structural members. As a result, the Space Shuttle System Engineering and Integration Office has initiated a program to re-assess the method used for developing the "rollout" loads and performing the life assessments. In the fall of 2003 a set of tests were preformed to provide information to either validate existing load spectra estimation techniques or generate new load spectra estimation methods. Acceleration and strain data were collected from two rollouts of a partial-stack configuration of the Space Shuttle. The partial stack configuration consists of two Solid Rocket Boosters tied together at the upper External Tank attachment locations mounted on the Mobile Launch Platform carried by a Crawler Transporter (CT). In the current analysis, the data collected from this test is examined for consistency in speed, surface condition effects, and the characterization of the forcing function. It is observed that the speed of the CT is relatively stable. The dynamic response acceleration of the partial-stack is slightly sensitive to the surface condition of the road used for transport, and the dynamic response acceleration of the partial-stack generally increases as the transport speed increases. However, the speed sensitivity is dependent on the measurement location. Finally, the character of the forcing function is narrow-banded with the primary drivers being harmonics of two CT speed dependent excitations. One source is an excitation due to the CT treads striking the road surface, and the second is unknown.

Elliott, Kenny B.↗

Probability Distribution Estimated From the Minimum, Maximum, and Most Likely Values: Applied to Turbine Inlet Temperature Uncertainty

Modern engineering design practices are tending more toward the treatment of design parameters as random variables as opposed to fixed, or deterministic, values. The probabilistic design approach attempts to account for the uncertainty in design parameters by representing them as a distribution of values rather than as a single value. The motivations for this effort include preventing excessive overdesign as well as assessing and assuring reliability, both of which are important for aerospace applications. However, the determination of the probability distribution is a fundamental problem in reliability analysis. A random variable is often defined by the parameters of the theoretical distribution function that gives the best fit to experimental data. In many cases the distribution must be assumed from very limited information or data. Often the types of information that are available or reasonably estimated are the minimum, maximum, and most likely values of the design parameter. For these situations the beta distribution model is very convenient because the parameters that define the distribution can be easily determined from these three pieces of information. Widely used in the field of operations research, the beta model is very flexible and is also useful for estimating the mean and standard deviation of a random variable given only the aforementioned three values. However, an assumption is required to determine the four parameters of the beta distribution from only these three pieces of information (some of the more common distributions, like the normal, lognormal, gamma, and Weibull distributions, have two or three parameters). The conventional method assumes that the standard deviation is a certain fraction of the range. The beta parameters are then determined by solving a set of equations simultaneously. A new method developed in-house at the NASA Glenn Research Center assumes a value for one of the beta shape parameters based on an analogy with the normal distribution (ref.1). This new approach allows for a very simple and direct algebraic solution without restricting the standard deviation. The beta parameters obtained by the new method are comparable to the conventional method (and identical when the distribution is symmetrical). However, the proposed method generally produces a less peaked distribution with a slightly larger standard deviation (up to 7 percent) than the conventional method in cases where the distribution is asymmetric or skewed. The beta distribution model has now been implemented into the Fast Probability Integration (FPI) module used in the NESSUS computer code for probabilistic analyses of structures (ref. 2).

Holland, Frederic A., Jr.↗

NASA Langley's AirSTAR Testbed: A Subscale Flight Test Capability for Flight Dynamics and Control System Experiments

As part of the Airborne Subscale Transport Aircraft Research (AirSTAR) project, NASA Langley Research Center (LaRC) has developed a subscaled flying testbed in order to conduct research experiments in support of the goals of NASA s Aviation Safety Program. This research capability consists of three distinct components. The first of these is the research aircraft, of which there are several in the AirSTAR stable. These aircraft range from a dynamically-scaled, twin turbine vehicle to a propeller driven, off-the-shelf airframe. Each of these airframes carves out its own niche in the research test program. All of the airplanes have sophisticated on-board data acquisition and actuation systems, recording, telemetering, processing, and/or receiving data from research control systems. The second piece of the testbed is the ground facilities, which encompass the hardware and software infrastructure necessary to provide comprehensive support services for conducting flight research using the subscale aircraft, including: subsystem development, integrated testing, remote piloting of the subscale aircraft, telemetry processing, experimental flight control law implementation and evaluation, flight simulation, data recording/archiving, and communications. The ground facilities are comprised of two major components: (1) The Base Research Station (BRS), a LaRC laboratory facility for system development, testing and data analysis, and (2) The Mobile Operations Station (MOS), a self-contained, motorized vehicle serving as a mobile research command/operations center, functionally equivalent to the BRS, capable of deployment to remote sites for supporting flight tests. The third piece of the testbed is the test facility itself. Research flights carried out by the AirSTAR team are conducted at NASA Wallops Flight Facility (WFF) on the Eastern Shore of Virginia. The UAV Island runway is a 50 x 1500 paved runway that lies within restricted airspace at Wallops Flight Facility. The facility provides all the necessary infrastructure to conduct the research flights in a safe and efficient manner. This paper gives a comprehensive overview of the development of the AirSTAR testbed.

Jordan, Thomas L.↗

Validation of Procedures for Monitoring Crewmember Immune Function

There is ample evidence to suggest that space flight leads to immune system dysregulation, however the nature of the phenomenon as it equilibrates over longer flights has not been determined. This dysregulation may be a result of microgravity, confinement, physiological stress, radiation, environment or other mission-associated factors. The clinical risk (if any) for exploration-class space flight is unknown, but may include increased incidence of infection, allergy, hypersensitivity, hematological malignancy or altered wound healing. The objective of this Supplemental Medical Objective (SMO) is to determine the status of the immune system, physiological stress and latent viral reactivation (a clinical outcome that can be measured) during both short and long-duration spaceflight. In addition, this study will develop and validate an immune monitoring strategy consistent with operational flight requirements and constraints. Pre-mission, in-flight and post-flight blood and saliva samples will be obtained from participating crewmembers. Assays included peripheral immunophenotype, T cell function, cytokine profiles (RNA, intracellular, secreted), viral-specific immunity, latent viral reactivation (EBV, CMV, VZV), and stress hormone measurements. This study is currently ongoing. To date, 10 short duration and 5 long-duration crewmembers have completed the study. Technically, the study is progressing well. In-flight blood samples are being collected, and returned for analysis, including functional assays that require live cells. For all in-flight samples to date, sample viability has been acceptable. Preliminary data (n = 4/7; long/short duration, respectively) indicate that distribution of most peripheral leukocyte subsets is largely unaltered during flight. Exceptions include elevated T cells, reduced B/NK cells, increased memory T cells and increased central memory CD8+ T cells. General T cell function, early blastogenesis response to mitogenic stimulation, is markedly reduced in-flight. In-vivo cytokine production profiles are altered, with in-flight dysregulation observed in the Th1/Th2/Treg equilibrium. EBV specific T cell levels are increased during flight, whereas their function is reduced. VZV reactivation was observed inflight and several days post flight with highest levels measured later during long-duration flight. The shedding of CMV in the urine was detected of 4/5 long duration and 4/7 short duration crewmembers. Plasma cortisol was not elevated during flight. Further data will be required to validate the initial observations.

Crucian, Brian↗

Updates of Land Surface and Air Quality Products in NASA MAIRS and NEESPI Data Portals

Following successful support of the Northern Eurasia Earth Sciences Partner Initiative (NEESPI) project with NASA satellite remote sensing data, from Spring 2009 the NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has been working on collecting more satellite and model data to support the Monsoon Asia Integrated Regional Study (MAIRS) project. The established data management and service infrastructure developed for NEESPI has been used and improved for MAIRS support.Data search, subsetting, and download functions are available through a single system. A customized Giovanni system has been created for MAIRS.The Web-based on line data analysis and visualization system, Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) allows scientists to explore, quickly analyze, and download data easily without learning the original data structure and format. Giovanni MAIRS includes satellite observations from multiple sensors and model output from the NASA Global Land Data Assimilation System (GLDAS), and from the NASA atmospheric reanalysis project, MERRA. Currently, we are working on processing and integrating higher resolution land data in to Giovanni, such as vegetation index, land surface temperature, and active fire at 5km or 1km from the standard MODIS products. For data that are not archived at the GESDISC,a product metadata portal is under development to serve as a gateway for providing product level information and data access links, which include both satellite, model products and ground-based measurements information collected from MAIRS scientists.Due to the large overlap of geographic coverage and many similar scientific interests of NEESPI and MAIRS, these data and tools will serve both projects.

Shen, Suhung↗

Unusual ISS Rate Signature

On November 23, 2011 International Space Station Guidance, Navigation, and Control reported unusual pitch rate disturbance. These disturbances were an order of magnitude greater than nominal rates. The Loads and Dynamics team was asked to review and analyze current accelerometer data to investigate this disturbance. This paper will cover the investigation process under taken by the Loads and Dynamics group. It will detail the accelerometers used and analysis performed. The analysis included performing Frequency Fourier Transform of the data to identify the mode of interest. This frequency data is then reviewed with modal analysis of the ISS system model. Once this analysis is complete and the disturbance quantified, a forcing function was produced to replicate the disturbance. This allows the Loads and Dynamics team to report the load limit values for the 100's of interfaces on the ISS.

Laible, Michael R.↗

Flight Mechanics Analysis Tools Interoperability and Component Sharing

As multiple flight mechanics (FM) analysis tools are developed to meet the unique scientific and operational requirements of NASA missions, sharing data, transferring models and trajectory information between tools can be complicated. The NESC recently explored ways that increase interoperability of three mission analysis tools: Copernicus, General Mission Analysis Tool (GMAT), and Mission-Analysis Operations Navigation Toolkit Environment (MONTE). These tools are used to generate a variety of products throughout all phases of a mission including: maneuver planning, trajectory optimization and design, orbit determination, performance and error analysis, trade studies and sizing. Establishing a framework to share models, component data and trajectory information is an efficient way to leverage the benefits of an analysis tool without expending development costs to duplicate functionality.

Flight Mechanics Simulation↗

Operation and Process Control Development for a Pilot-Scale Leaching and Solvent Extraction Circuit Recovering Rare Earth Elements From Coal-Based Sources

The US Department of Energy in 2010 has identified several rare earth elements as critical materials to enable clean technologies. As part of ongoing research in REEs (rare earth elements) recovery from coal sources, the University of Kentucky has designed, developed and is demonstrating a ¼ ton/hour pilot-scale processing plant to produce high-grade REEs from coal sources. Due to the need to control critical variables (e.g. pH, tank level, etc.), process control is required. To ensure adequate process control, a study was conducted on leaching and solvent extraction control to evaluate the potential of achieving low-cost REE recovery in addition to developing a process control PLC system. The overall operational design and utilization of Six Sigma methodologies is discussed. Further, the application of the controls design, both procedural and electronic for the control of process variables such as pH is discussed. Variations in output parameters were quantified as a function of time. Data trends show that the mean process variable was maintained within prescribed limits. Future work for the utilization of data analysis and integration for data-based decision-making will be discussed.

coal, rare earth elements, pilot plant, automation↗

Geosat crossover analysis in the tropical Pacific. II - Verification analysis of altimetric sea level maps with expendable bathythermograph and island sea level data

Altimetric sea level time series for the tropical Pacific have been generated from the Geosat crossover differences during the classified era of the Geosat mission from April 1985 to September 1986. These are compared with the expendable bathythermograph (XBT)-derived dynamic height and island sea level observations, yielding good agreement. A complex empirical orthogonal function analysis is also applied to the altimetric and XBT results. The analysis demonstrates the dominance of the annual signal in this relatively short time series and the westward propagation of major features away from the equator.

Tai, Chang-Kou↗

Forced Response Aeromechanics Analysis in MATLAB®-Based Environment Code With Application to Distortion-Tolerant Fan R24 Blade Geometry

Researchers at the NASA Glenn Research Center have developed a research-level code for forced response analysis for turbomachinery that provides a streamlined framework for aeromechanics analysis, as well as for generating Goodman diagrams. The Forced Response Aeromechanics Analysis in a MATLAB-Based Environment (FRAAME, Version 1) code is designed to accept blade surface unsteady pressure time histories generated by three-dimensional (3D) Unsteady Reynolds-Averaged Navier-Stokes (URANS) code TURBO and modal displacements, modal stresses, and static stresses generated via expanded ANSYS® (Ansys, Inc.) cyclic symmetry analysis. The code’s looping structure allows for largescale analyses, including many blade surface pressure files, modal displacements, and modal stress files for full annulus forced response analysis, including a modal summation method for multiple engine orders and modes. This code is applied to the R24 fan geometry for the Boundary Layer Ingesting Inlet/Distortion-Tolerant Fan (BLI2DTF) project, a propulsion system being developed to increase the fuel efficiency of future aircraft, to serve as validation of experimental data as well as external simulation results. This tool’s functional, modular form is intended to allow users to make modifications easily. Those modifications can include requests for information for any step in the analysis process, as well as adding various functions to compute additional information of interest. It is also written, given sufficient input information, as a general blade geometry forced response solver that is not necessarily specific to the R24 geometry but is used here for verification of code functionality and accuracy. Although forced response analysis tools are also available in commercially available code packages, the post-processing FRAAME code offers reliable, fast, and scalable forced response analysis and Goodman diagram generation for large cases utilizing, specifically, TURBO and ANSYS® results information in an effort to streamline forced response and high cycle fatigue analyses.

Aeromechanics↗

Engineering Complex Embedded Systems with State Analysis and the Mission Data System

It has become clear that spacecraft system complexity is reaching a threshold where customary methods of control are no longer affordable or sufficiently reliable. At the heart of this problem are the conventional approaches to systems and software engineering based on subsystem-level functional decomposition, which fail to scale in the tangled web of interactions typically encountered in complex spacecraft designs. Furthermore, there is a fundamental gap between the requirements on software specified by systems engineers and the implementation of these requirements by software engineers. Software engineers must perform the translation of requirements into software code, hoping to accurately capture the systems engineer's understanding of the system behavior, which is not always explicitly specified. This gap opens up the possibility for misinterpretation of the systems engineer s intent, potentially leading to software errors. This problem is addressed by a systems engineering methodology called State Analysis, which provides a process for capturing system and software requirements in the form of explicit models. This paper describes how requirements for complex aerospace systems can be developed using State Analysis and how these requirements inform the design of the system software, using representative spacecraft examples.

mission data systems↗

Analysis of Doppler lidar wind measurements

New analysis methods were developed and refined for the synthesis of wind fields from multiple Doppler radar data. Considerable software was written and debugged for wind field synthesis. The analysis methods were applied to radar data collected during the CCOPE experiment in which lidar wind measurements were also made. The analysis method differs from existing methods in that interpolation (using filters with assigned weights) and advection of data, to account for time differential between data acquisition at different points, are not used. Instead, functional fits were used in space and time coordinates to transfer radial velocity data to a space-time grid. Subsequently the wind synthesis is performed. This method gives better space resolution in the synthesized winds, compared to other methods in common use, by better preserving the gradients of velocities. The wind fields show the cellular structure characteristic of boundary-layer convection. Also evident in the analysis are the sharp transitions and gradients in the wind field which were preserved by the synthesis.

Srivastava, R. C.↗

Computations involving differential operators and their actions on functions

The algorithms derived by Grossmann and Larson (1989) are further developed for rewriting expressions involving differential operators. The differential operators involved arise in the local analysis of nonlinear dynamical systems. These algorithms are extended in two different directions: the algorithms are generalized so that they apply to differential operators on groups and the data structures and algorithms are developed to compute symbolically the action of differential operators on functions. Both of these generalizations are needed for applications.

Crouch, Peter E.↗

Developing a Graphical User Interface for the ALSS Crop Planning Tool

The goal of my project was to create a graphical user interface for a prototype crop scheduler. The crop scheduler was developed by Dr. Jorge Leon and Laura Whitaker for the ALSS (Advanced Life Support System) program. The addition of a system-independent graphical user interface to the crop planning tool will make the application more accessible to a wider range of users and enhance its value as an analysis, design, and planning tool. My presentation will demonstrate the form and functionality of this interface. This graphical user interface allows users to edit system parameters stored in the file system. Data on the interaction of the crew, crops, and waste processing system with the available system resources is organized and labeled. Program output, which is stored in the file system, is also presented to the user in performance-time plots and organized charts. The menu system is designed to guide the user through analysis and decision making tasks, providing some help if necessary. The Java programming language was used to develop this interface in hopes of providing portability and remote operation.

Koehlert, Erik↗

Uncertainty Quantification of a Rotorcraft Conceptual Sizing Toolsuite

A computational framework to support the quantification of system uncertainties and sensitivities for rotorcraft applications is presented using the NASA Design and Analysis of Rotorcraft (NDARC) conceptual sizing tool. A 90 passenger conceptual tiltrotor configuration was used for case demonstration in the modeling of uncertainties in NDARCs emission module. A non-intrusive forward propagation uncertainty quantification approach was applied to ensemble simulations using a Monte Carlo methodology with stratified Latin hypercube sampling. An off-the-shelf software, DAKOTA, which supports trade studies and design space exploration, including optimization, surrogate modeling and uncertainty analysis was used to address the research goals. A toolsuite was further developed incorporating DAKOTA with automated design processes and methods using function wrappers to execute program routines including support for data post-processing. Uncertainties in rotorcraft emissions modeling using the Average Temperature Response metric for a set mission profile were studied. It was shown that for the current study, using the base-line best estimate modeling parameters for the Average Temperature Response metric, NDARC under-estimates the effects of emissions when compared with results from Monte Carlo simulations. A global sensitivity analysis was further undertaken to quantify the contribution of the various emission species on output sensitivity, hence uncertainty. The work demonstrates that the developed toolsuite is robust and will support the quantification of system uncertainties and sensitivities in future rotorcraft design efforts.

Rotorcraft↗

Analysis/forecast experiments with a multivariate statistical analysis scheme using FGGE data

A three-dimensional, multivariate, statistical analysis method, optimal interpolation (OI) is described for modeling meteorological data from widely dispersed sites. The model was developed to analyze FGGE data at the NASA-Goddard Laboratory of Atmospherics. The model features a multivariate surface analysis over the oceans, including maintenance of the Ekman balance and a geographically dependent correlation function. Preliminary comparisons are made between the OI model and similar schemes employed at the European Center for Medium Range Weather Forecasts and the National Meteorological Center. The OI scheme is used to provide input to a GCM, and model error correlations are calculated for forecasts of 500 mb vertical water mixing ratios and the wind profiles. Comparisons are made between the predictions and measured data. The model is shown to be as accurate as a successive corrections model out to 4.5 days.

Baker, W. E.↗

Machine Learning-Assisted Recovery of Delicate Kinetic Information from Transient Reactor Experiments

Identifying active sites and their roles in chemical reaction steps remains a vital challenge in heterogeneous catalysis. Transient experiments offer a unique way to probe active sites and distinguish subtle kinetic features. Although physics-based analysis methods may be well-developed, they can be highly susceptible to experimental noise, and smoothing methods may erase or even distort important features; a smooth curve is not always the best curve. We demonstrate a new workflow for the direct interpretation of intrinsic kinetic information from exit flux curves measured in transient reactor experiments. This workflow contains three artificial neural networks (ANNs), including a noise reducer, a concentration predictor, and a rate predictor to analyze experimental data, followed by the virtual TAP (VTAP) physics-based reactor model and density functional theory (DFT) calculations of adsorption energies on specific sites. We use this workflow to analyze the data from experiments titrating Pt/Al 2 O 3 and Pt/SiO 2 catalysts with carbon monoxide (CO) in the temporal analysis of products (TAP) reactor. Our workflow separates the time-evolving chemical reaction and mass transfer information contained in the TAP pulse response. The existence of strong- and weak-binding sites on the Pt/Al 2 O 3 catalyst is observed in the catalyst titration experiment in the transient reactor. The structures of the strong- and weak-binding sites are then identified by using DFT calculations. We find that the Pt/SiO 2 catalyst has only strong-binding sites, which aligns with the inactive support effect of SiO 2 . We demonstrate how machine learning methods provide unique insights with high-resolution data analysis that cannot be achieved by using state-of-the-art physics-based methods.

Adsorption↗