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At least 253 records · Page 14

Flood-plain delineation using multispectral data analysis

The paper explores the application of a remote sensing technique that may permit the determination of flood-plain areas without the extensive work associated with existing techniques. Multispectral scanner data were simulated by utilizing the density differences in a color-infrared transparency for a section of the Navasota River, Texas. The transparency was taken from a low-flying aircraft and covered an area approximating a square mile. The simulated data were processed by an automatic classification technique previously developed in the remote sensing field. The technique used involves the application of the maximum likelihood rule in order to categorize the data being processed. An attempt was made to distinguish between areas known to be in the flood plain and those outside. A reasonabke correlation was found between boundaries based on computer-processed multispectral data and those produced by techniques currently in use.

Harker, G. R.↗

Simulation replay - Implementation and flight simulation applications

Throughout the aircraft development process flight simulators are used to evaluate design concepts, 'handling' qualities, and operational procedures. A modern flight research simulator comprises a cockpit equipped with flight instruments and controls, subsystems to provide visual, motion, and other flight cues, and a digital computer. REPLAY is a computer program which enables a user to reproduce the multidimensional flight cues for an entire simulation 'run'. Attention is given to simulation fidelity improvement, simulation data recovery, simulation quality assurance, and aircraft systems research. It is pointed out that each of the applications discussed supports aircraft systems research by improving the realism, efficiency, or reliability of the simulation facility.

Crane, D. F.↗

Reduction of rotor-turbulence interaction noise in static fan noise testing

Three effective inlet cleanup methods are described. A flared reverse cone inlet is used to eliminate wakes from the fan casings and/or probe supports. Boundary layer suction is employed ahead of the fan rotor and on the outer flare of the cone to reduce the boundary layer turbulence and remove any residual wakes. To reduce the midstream turbulent intensity and length scales, a turbulence control structure is used which is constructed with both a layer of honeycomb and a fine mesh screen. The effects of these cleanup methods are quantified by measuring the far-field noise in an anechoic chamber, using a high-speed 20-in.-diam fan of the current high passband type. The changes in the turbulent field impinging on this rotor are quantified by mapping the streamwise and transverse turbulent properties (spectra, intensity and length scale) with crossed hot film probes. It is convincingly shown that it is possible to clean up the inlet flow of a static fan noise test facility to a point where the static acoustic data simulate flight data.

Kantola, R. A.↗

On the use of off-nadir pointing for increased temporal resolution of Earth observing satellite systems

The change in radiance expected at a satellite in a LANDSAT type orbit by pointing the sensor across track was examined with simulated data. The simulation incorporated the bidirectional reflectance distribution function of a spherical geometry grass canopy and scattering under clear, light haze and heavy haze atmospheric conditions. The results indicate that if the sensor pointed up to + or - 37 deg off nadir (up to three tracks east and west) through a clear atmosphere, between 50% and 75% of the orbital path between 60 deg N and 60 deg S would have two or more off-nadir views within + or - 5% of nadir. Although increased atmospheric scattering causes large variations in across track radiance, it appears possible, using various combinations of views depending on atmospheric conditions, that at least two views could be obtained with radiances within + or - 5% of each other over atmospheric visibilities from 23 km to 4 km.

Schnetzler, C. C.↗

Information Management Workflow and Tools Enabling Multiscale Modeling Within ICME Paradigm

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Fortunately, material information management systems and physics-based multiscale modeling methods have kept pace with the growing user demands. Herein, recent efforts to establish workflow for and demonstrate a unique set of web application tools for linking NASA GRC's Integrated Computational Materials Engineering (ICME) Granta MI database schema and NASA GRC's Integrated multiscale Micromechanics Analysis Code (ImMAC) software toolset are presented. The goal is to enable seamless coupling between both test data and simulation data, which is captured and tracked automatically within Granta MI®, with full model pedigree information. These tools, and this type of linkage, are foundational to realizing the full potential of ICME, in which materials processing, microstructure, properties, and performance are coupled to enable application-driven design and optimization of materials and structures.

Materials Engineering↗

Integration of Information Management System, Workflow and Computational Tools Enabling Multiscale Modeling Within an ICME Paradigm

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Fortunately, material information management systems and physics-based multiscale modeling methods have kept pace with the growing user demands. Herein, recent efforts to develop a set of Python functions that exchange information between NASA GRC's Integrated multiscale Micromechanics Analysis Code (ImMAC) software toolset and its Integrated Computational Materials Engineering (ICME), Granta MI® database schema is presented. The goal is to enable seamless coupling between both test data and simulation data, which is captured and tracked automatically within Granta MI®, with full model pedigree information. These tools, and this type of linkage, are foundational to realizing the full potential of ICME, in which materials processing, microstructure, properties, and performance are coupled to enable application-driven design and optimization of materials and structures.

multiscale modeling; Micromechanics; Computational↗

Expansion of Check-Cases for 6DOF Simulation

This effort expands upon a previous NASA activity that developed flight simulation benchmark check-cases to include new check-cases for the Cislunar domain, comparing multiple NASA simulation tools. The results of this effort describe the benefits of standardizing inputs, simulation comparisons and describe an interactive website that enables comparison of externally provided simulation data. Participating simulations improved their software and identified implementation errors. This activity elevated simulation credibility and provided a measure of validation for the simulations actively in use for NASA’s Human Landing Systems (HLS).

Modeling↗

Methane Emissions Produced by Pneumatic Devices and Produced Water Tanks on Natural Gas Wellsites

In recent years, more scrutiny has been placed on the release of greenhouse gasses (GHGs) by the oil and gas industry in North America as climate concerns increase. In the coming years, stricter regulations proposed by the Environmental Protection Agency (EPA) concerning the release of GHGs will further direct attention to GHG emissions quantification, modeling, and overall reduction. Active natural gas wellsites employ production equipment that routinely emits methane during normal operation. Production equipment often includes, but is not limited to, gas production units (GPUs), pneumatic controllers (PCs) and actuators powered by produced natural gas, and produced water storage tanks. This work details direct methane emission measurements taken at active natural gas wellsites originating from intermittent pneumatic controllers and produced water storage tanks. Efforts to model methane flows originating from these sources are also detailed, and those results are compared to direct measurement. The direct methane emissions measurement campaign collected flow data from two active dry wellsites in the Marcellus shale region. These measurement campaigns captured, in total, several weeks of continuous data from these sites. Data included multiple pneumatic device vent flowrate channels, a single channel monitoring total emissions vented from the produced water storage tanks, and corresponding site weather data. Periodic composition measurements were taken from flows vented from produced water tanks. Computational modeling efforts attempted to mimic a given site’s methane emissions behavior given limited input parameters. Direct measurement data and simulation data yielded, through reduction and analysis, apparent methane emissions factors, statistics on pneumatic device actuation events, important relationships between GPU parameters and pneumatic device actuation events, produced water storage tank vent flows and flow compositions, and parameters most contributing to the magnitude and frequency of these fugitive methane emissions. Measurements, considering data from a 72hr period, produced PC emissions factors from 0.008 to 0.03 SCFH per device with an average device emitting 0.026 SCFH at the first site. The second site produced PC emissions factors spanning from 0.05 to 25.47 SCFH with an average device emitting 1.93 SCFH not including the 25.47 SCFH device, which was assumed to be malfunctioning. Two unique water tank emission measurements were made, 618 g CH4 per hour and 32.6 g CH4 per hour. On a water basis, the water tank emissions factors were 0.66 and 0.042 kg CH4 per bbl of water, respectively.

03 NATURAL GAS↗

Fuzzy Modeling and Parallel Distributed Compensation for Aircraft Flight Control from Simulated Flight Data

A method is described that combines fuzzy system identification techniques with Parallel Distributed Compensation (PDC) to develop nonlinear control methods for aircraft using minimal a priori knowledge, as part of NASA’s Learn-to-Fly initiative. A fuzzy model was generated with simulated flight data, and consisted of a weighted average of multiple linear time invariant state-space cells having parameters estimated using the equation-error approach and a least-squares estimator. A compensator was designed for each subsystem using Linear Matrix Inequalities (LMI) to guarantee closed-loop stability and performance requirements. This approach is demonstrated using simulated flight data to automatically develop a fuzzy model and design control laws for a simplified longitudinal approximation of the F-16 nonlinear flight dynamics simulation. Results include a comparison of flight data with the estimated fuzzy models and simulations that illustrate the feasibility and utility of the combined fuzzy modeling and control approach.

Weinstein, Rose↗

Simulation process and data flow for a large system dynamics model

This paper documents the workflow and supporting technologies that a large system dynamics model, the biomass scenario model, employs to streamline the data preparation, simulation, quality control, and analysis process at the National Renewable Energy Laboratory. The workflow centers on automation of routine aspects of the flow of data between data stores, simulations, and visualizations. It enforces quality checks on data, reproducibility of computations, and traceability of results, while maintaining complete archives of modeling and analysis artifacts. The resulting frictionless simulation/analysis environment supports large-scale sensitivity analysis, interactive creation of ensembles of simulations, and rapid visualization-based exploration of simulation results.

09 BIOMASS FUELS↗

Low altitude wind shear statistics derived from measured and FAA proposed standard wind profiles

Wind shear statistics were calculated for a simulated data set using wind profiles proposed as a standard and compared to statistics derived from measured wind profile data. Wind shear values were grouped in altitude bands of 100 ft between 100 and 1400 ft, and in wind shear increments of 0.025 kt/ft between + or - 0.600 kt/ft for the simulated data set and between + or - 0.200 kt/ft for the measured set. No values existed outside the + or - 0.200 kt/ft boundaries for the measured data. Frequency distributions, means, and standard deviations were derived for each altitude band for both data sets, and compared. Also, frequency distributions were derived for the total sample for both data sets and compared. Frequency of occurrence of a given wind shear was about the same for both data sets for wind shears, but less than + or 0.10 kt/ft, but the simulated data set had larger values outside these boundaries. Neglecting the vertical wind component did not significantly affect the statistics for these data sets. The frequency of occurrence of wind shears for the flight measured data was essentially the same for each altitude band and the total sample, but the simulated data distributions were different for each altitude band. The larger wind shears for the flight measured data were found to have short durations.

Dunham, R. E., Jr.↗

On Fast Post-Processing of Global Positioning System Simulator Truth Data and Receiver Measurements and Solutions Data

Post-processing of data, related to a GPS receiver test in a GPS simulator and test facility, is an important step towards qualifying a receiver for space flight. Although the GPS simulator provides all the parameters needed to analyze a simulation, as well as excellent analysis tools on the simulator workstation, post-processing is not a GPS simulator or receiver function alone, and it must be planned as a separate pre-flight test program requirement. A GPS simulator is a critical resource, and it is desirable to move off the pertinent test data from the simulator as soon as a test is completed. The receiver and simulator databases are used to extract the test data files for postprocessing. These files are then usually moved from the simulator and receiver systems to a personal computer (PC) platform, where post-processing is done typically using PC-based commercial software languages and tools. Because of commercial software systems generality their functions are notoriously slow and more than often are the bottleneck even for short duration simulator-based tests. There is a need to do post-processing faster and within an hour after test completion, including all required operations on the simulator and receiver to prepare and move off the post-processing files. This is especially significant in order to use the previous test feedback for the next simulation setup or to run near back-to-back simulation scenarios. Solving the post-processing timing problem is critical for a pre-flight test program success. Towards this goal an approach was developed that allows to speed-up post-processing by an order of a magnitude. It is based on improving the post-processing bottleneck function algorithm using a priory information that is specific to a GPS simulation application and using only the necessary volume of truth data. The presented postprocessing scheme was used in support of a few successful space flight missions carrying GPS receivers.

Kizhner, Semion↗

A flight investigation of simulated data-link communications during single-pilot IFR flight. Volume 2: Flight evaluations

Key problems in single pilot instrument flight operations are in the management of flight data and the processing of cockpit information during conditions of heavy workload. A flight data console was developed to allow simulation of a digital data link to replace the current voice communications stem used in air traffic control. This is a human factors evaluation of a data link communications system to determine how such a system might reduce cockpit workload, improve flight proficiency, and be accepted by general aviation pilots. The need for a voice channel as backup to a digital link is examined. The evaluations cover both airport terminal area operations and full mission instrument flight. Results show that general aviation pilots operate well with a digital data link communications system. The findings indicate that a data link system for pilot/ATC communications, with a backup voice channel, is well accepted by general aviation pilots and is considered to be safer, more efficient, and result in less workload than the current voice system.

Parker, J. F., Jr.↗

Efficient scatter distribution estimation and correction in CBCT using concurrent Monte Carlo fitting

Purpose: X-ray scatter is a significant impediment to image quality improvements in cone-beam CT (CBCT). The authors present and demonstrate a novel scatter correction algorithm using a scatter estimation method that simultaneously combines multiple Monte Carlo (MC) CBCT simulations through the use of a concurrently evaluated fitting function, referred to as concurrent MC fitting (CMCF). Methods: The CMCF method uses concurrently run MC CBCT scatter projection simulations that are a subset of the projection angles used in the projection set, P, to be corrected. The scattered photons reaching the detector in each MC simulation are simultaneously aggregated by an algorithm which computes the scatter detector response, S{sub MC}. S{sub MC} is fit to a function, S{sub F}, and if the fit of S{sub F} is within a specified goodness of fit (GOF), the simulations are terminated. The fit, S{sub F}, is then used to interpolate the scatter distribution over all pixel locations for every projection angle in the set P. The CMCF algorithm was tested using a frequency limited sum of sines and cosines as the fitting function on both simulated and measured data. The simulated data consisted of an anthropomorphic head and a pelvis phantom created from CT data, simulated with and without the use of a compensator. The measured data were a pelvis scan of a phantom and patient taken on an Elekta Synergy platform. The simulated data were used to evaluate various GOF metrics as well as determine a suitable fitness value. The simulated data were also used to quantitatively evaluate the image quality improvements provided by the CMCF method. A qualitative analysis was performed on the measured data by comparing the CMCF scatter corrected reconstruction to the original uncorrected and corrected by a constant scatter correction reconstruction, as well as a reconstruction created using a set of projections taken with a small cone angle. Results: Pearson’s correlation, r, proved to be a suitable GOF metric with strong correlation with the actual error of the scatter fit, S{sub F}. Fitting the scatter distribution to a limited sum of sine and cosine functions using a low-pass filtered fast Fourier transform provided a computationally efficient and accurate fit. The CMCF algorithm reduces the number of photon histories required by over four orders of magnitude. The simulated experiments showed that using a compensator reduced the computational time by a factor between 1.5 and 1.75. The scatter estimates for the simulated and measured data were computed between 35–93 s and 114–122 s, respectively, using 16 Intel Xeon cores (3.0 GHz). The CMCF scatter correction improved the contrast-to-noise ratio by 10%–50% and reduced the reconstruction error to under 3% for the simulated phantoms. Conclusions: The novel CMCF algorithm significantly reduces the computation time required to estimate the scatter distribution by reducing the statistical noise in the MC scatter estimate and limiting the number of projection angles that must be simulated. Using the scatter estimate provided by the CMCF algorithm to correct both simulated and real projection data showed improved reconstruction image quality.

60 APPLIED LIFE SCIENCES↗

Error coding simulations in C

When data is transmitted through a noisy channel, errors are produced within the data rendering it indecipherable. Through the use of error control coding techniques, the bit error rate can be reduced to any desired level without sacrificing the transmission data rate. The Astrionics Laboratory at Marshall Space Flight Center has decided to use a modular, end-to-end telemetry data simulator to simulate the transmission of data from flight to ground and various methods of error control. The simulator includes modules for random data generation, data compression, Consultative Committee for Space Data Systems (CCSDS) transfer frame formation, error correction/detection, error generation and error statistics. The simulator utilizes a concatenated coding scheme which includes CCSDS standard (255,223) Reed-Solomon (RS) code over GF(2(exp 8)) with interleave depth of 5 as the outermost code, (7, 1/2) convolutional code as an inner code and CCSDS recommended (n, n-16) cyclic redundancy check (CRC) code as the innermost code, where n is the number of information bits plus 16 parity bits. The received signal-to-noise for a desired bit error rate is greatly reduced through the use of forward error correction techniques. Even greater coding gain is provided through the use of a concatenated coding scheme. Interleaving/deinterleaving is necessary to randomize burst errors which may appear at the input of the RS decoder. The burst correction capability length is increased in proportion to the interleave depth. The modular nature of the simulator allows for inclusion or exclusion of modules as needed. This paper describes the development and operation of the simulator, the verification of a C-language Reed-Solomon code, and the possibility of using Comdisco SPW(tm) as a tool for determining optimal error control schemes.

Noble, Viveca K.↗

Studying marine stratus with large eddy simulation

Data sets from field experiments over the stratocumulus regime may include complications from larger scale variations, decoupled cloud layers, diurnal cycle, or entrainment instability, etc. On top of the already complicated turbulence-radiation-condensation processes within the cloud-topped boundary layer (CTBL), these complexities may sometimes make interpretation of the data sets difficult. To study these processes, a better understanding is needed of the basic processes involved in the prototype CTBL. For example, is cloud top radiative cooling the primary source of the turbulent kinetic energy (TKE) within the CTBL. Historically, laboratory measurements have played an important role in addressing the turbulence problems. The CTBL is a turbulent field which is probably impossible to generate in laboratories. Large eddy simulation (LES) is an alternative way of 'measuring' the turbulent structure under controlled environments, which allows the systematic examination of the basic physical processes involved. However, there are problems with the LES approach for the CTBL. The LES data need to be consistent with the observed data. The LES approach is discussed, and results are given which provide some insights into the simulated turbulent flow field. Problems with this approach for the CTBL and information from the FIRE experiment needed to justify the LES results are discussed.

Moeng, Chin-Hoh↗

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗