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NASA NTRS2012

Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing

Geospatial resource assessments frequently require timely geospatial data processing that involves large multivariate remote sensing data sets. In particular, for disasters, response requires rapid access to large data volumes, substantial storage space and high performance processing capability. The processing and distribution of this data into usable information products requires a processing pipeline that can efficiently manage the required storage, computing utilities, and data handling requirements. In recent years, with the availability of cloud computing technology, cloud processing platforms have made available a powerful new computing infrastructure resource that can meet this need. To assess the utility of this resource, this project investigates cloud computing platforms for bulk, automated geoprocessing capabilities with respect to data handling and application development requirements. This presentation is of work being conducted by Applied Sciences Program Office at NASA-Stennis Space Center. A prototypical set of image manipulation and transformation processes that incorporate sample Unmanned Airborne System data were developed to create value-added products and tested for implementation on the "cloud". This project outlines the steps involved in creating and testing of open source software developed process code on a local prototype platform, and then transitioning this code with associated environment requirements into an analogous, but memory and processor enhanced cloud platform. A data processing cloud was used to store both standard digital camera panchromatic and multi-band image data, which were subsequently subjected to standard image processing functions such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), band stacking, reprojection, and other similar type data processes. Cloud infrastructure service providers were evaluated by taking these locally tested processing functions, and then applying them to a given cloud-enabled infrastructure to assesses and compare environment setup options and enabled technologies. This project reviews findings that were observed when cloud platforms were evaluated for bulk geoprocessing capabilities based on data handling and application development requirements.

Brown, Richard B.↗

NASA NTRS2014

Combined Uncertainty and A-Posteriori Error Bound Estimates for CFD Calculations: Theory and Implementation

Simulation codes often utilize finite-dimensional approximation resulting in numerical error. Some examples include, numerical methods utilizing grids and finite-dimensional basis functions, particle methods using a finite number of particles. These same simulation codes also often contain sources of uncertainty, for example, uncertain parameters and fields associated with the imposition of initial and boundary data,uncertain physical model parameters such as chemical reaction rates, mixture model parameters, material property parameters, etc.

CFD↗

NASA NTRS2015

Verification of a Viscous Computational Aeroacoustics Code Using External Verification Analysis

The External Verification Analysis approach to code verification is extended to solve the three-dimensional Navier-Stokes equations with constant properties, and is used to verify a high-order computational aeroacoustics (CAA) code. After a brief review of the relevant literature, the details of the EVA approach are presented and compared to the similar Method of Manufactured Solutions (MMS). Pseudocode representations of EVA's algorithms are included, along with the recurrence relations needed to construct the EVA solution. The code verification results show that EVA was able to convincingly verify a high-order, viscous CAA code without the addition of MMS-style source terms, or any other modifications to the code.

Computational↗

NASA NTRS2015

Verification of a Viscous Computational Aeroacoustics Code using External Verification Analysis

Computational↗

NASA NTRS2018

Combined Error and Uncertainty Estimates for CFD Problems

Given input sources of uncertainty, non-intrusive uncertainty propagation methods quantify the uncertainty in output quantities of interest (QoI) by performing a nite number of CFD (Computational Fluid Dynamics) instance realizations needed in the calculation of output statistics. It is well known that this introduces multiple sources of error. CFD codes often utilize finite-dimensional approximation (grids, basis functions, etc.) thus incurring CFD numerical errors often approximately reinterpreted as a statistical bias. Uncertainty propagation methods calculate uncertainty statistics for output quantities of interest using a numerical method (e.g. deterministic quadrature, sampling, etc.) thus incurring UQ (Uncertainty Quantification) numerical errors. Importance of quantifying these errors in large scale scientific computing: How accurate is an output statistic?; How should additional computational resources be invested to further reduce the error in a statistic?

Posteriori↗

NASA NTRSDate not supplied

TPSAS-NF1676L-14428-DND

Test executed from June 6 through July 3, 2011. Objectives - Understand maneuver acoustics - Validate ground footprint acoustic codes - Incorporate maneuvers into acoustic ground footprint prediction codes Acoustic measurement of - Source noise - Steady and transient maneuvers - Approach profiles Large test crew: 23 people from 7 organizations. Acquired 410 individual data points over 10 testing days and 30.6 flight hours. All “Priority One” and “Priority Two” test conditions measured.

Michael Watts↗

NASA NTRS2020

Charged Particle Dynamics in the Lunar Environment

As the Artemis Program streams forward, organizations of scientists and engineers across the country have been coming together to solve the complex network of problems to once again achieve the milestone of successfully touching down on the moon. This project is no exception, and it has been an honor to work with the Electrostatics and Surface Physics Laboratory (ESPL), a lab within the Exploration Research and Technology Programs’ Spaceport Technologies Office (UB-G) located at the National Aeronautics and Space Administration at Kennedy Space Center (NASA KSC). The authors and their mentor James R. Phillips III3, in tandem with researchers from the Astrodynamics and Space Robotics Laboratory (ASRL) at the University of Central Florida (UCF), have been working on creating a state-of-the-art (SOA) granular gas dynamics model for particulate contamination prevention and mitigation purposes. In essence, the underlying objective for this project is to more accurately model the resulting electrodynamic interactions between lunar regolith grains with applications to dust mitigation and rocket engine plume surface interactions. To achieve this goal, the team has been expanding upon existing open source classical molecular dynamics code developed by Sandia National Laboratories (SNL). The following reports on the details of the problem at hand as well as the contributions that the authors have made towards resolution, including but not limited to the encoding of physical attributes and interactions for non-spherical polydisperse particle distributions within various bed geometries and preemptive data analysis implementations. Significant data analysis processes were utilized, and several original algorithms were created to perform critical evaluations, resulting in only a 0.006% error in discrepancy.

Annelisa B Esparza↗

NASA NTRS2021

Aircraft Flaps Modeling in OpenMDAO

The goal of this project was to develop a model for a single subsystem in the aerodynamics discipline, in this case the flaps of an aircraft. Flaps are high-lift devices used by planes to allow for quicker takeoffs, and slower landings. A computer-based aircraft model of the flaps of an aircraft was developed using the Python based open-source framework OpenMDAO. OpenMDAO is used to develop multi-disciplinary aircraft models using gradient-based optimization; design optimization (MDO) is concerned with solving design problems involving numerical models of complex engineering systems. There were 4 components in the model; each has input values, output variables, and equations to calculate said outputs. The variables and equations are sourced from NASA Fortran code from the 1970s, in a project called the General Aviation Synthesis Program (GASP). These variables and equations which create the model are being converted to Python for ease of use. The flaps model developed will be integrated into a larger model of a conventional aircraft’s flight phases. All subsystems of the model will first be built using the parameters of a Boeing 737 MAX-8, to validate its functionality and accuracy. Then, the aircraft model will be used for hybrid-electric research; running optimizations to improve efficiency, minimize fuel burn, and advance hybrid-electric technology in the aerospace field.

Computer-based aircraft modeling↗

NASA NTRSDate not supplied

Direct Simulation Monte Carlo Studies of the Gas Sampling for the VATMOS-SR Mission Concept

VATMOS-SR (Venus ATMOSpheric - Sample Return) is a small spacecraft mission concept which would return a gas sample from the upper atmosphere of Venus to Earth for scientific analysis. This could be the first sample return mission for an extra-terrestrial atmosphere, and potentially the first sample return from an Earth-sized planet. The VATMOS-SR mission concept consists of a SmallSat atmospheric sampling probe (45 deg. sphere/cone geometry, <1 m diameter) that is designed to skim through the Venus upper atmosphere and acquire gas samples below the homopause altitude (around ~110 km altitude), where the different atmospheric gases are mixed. The velocity of the spacecraft where sampling would occur is expected to be between ~10.5 km/s and ~13.1 km/s, depending on the trajectory chosen. This presentation will discuss hypervelocity sampling in the upper atmosphere of Venus, with respect to the VATMOS-SR mission concept. VATMOS-SR would enable critical atmospheric measurements to form a full picture of how, why, and when Venus evolved to be so different from Earth and Mars. The abundances and isotopic compositions of volatile elements (such as N, C, S, O and the noble gases) in planetary atmospheres record volatile delivery during accretion, outgassing from planetary interiors, and atmospheric loss to space. Precise and accurate determinations of atmospheric volatile signatures are the key to understanding the origins and geodynamical evolution of Venus compared to the other terrestrial planets. Hypersonic sampling poses unique technical and scientific challenges. To ensure it is possible to relate the composition of the sampled gases to the free stream atmospheric composition, large-scale numerical simulations are employed to model the flow through the VATMOS-SR sampling system. In particular, an emphasis is placed on quantifying noble gas isotopic fractionation that occurs during the sample acquisition and transfer process in order to determine how measured isotopic ratios of noble gases in the sample compare to actual isotopic ratios in the Venusian atmosphere. The Direct Simulation Monte Carlo (DSMC) code SPARTA, an open source software package developed by Sandia National Laboratories, is used in this work. SPARTA, based on Bird’s DSMC method, is a molecular-level gas-kinetic technique. As SPARTA is able to model hypervelocity reacting flows in strong chemical and thermal non-equilibrium, this software package is well suited to determine relevant flow properties for the VATMOS-SR mission concept, and to numerically quantify the expected level of elemental and/or isotopic fractionation in the sample acquired by VATMOS-SR. This presentation will show results from 3D simulations correlating the noble gas isotopic fractionation in the gas acquired at hypervelocity speeds to its ambient atmosphere value. In particular, emphasis will be placed at Xenon isotopes of masses 128 and 130, as precise measurements of that ratio would yield a comparison to Earth’s atmosphere. Additionally, sensitivity studies that quantify the uncertainties due to the freestream parameters as well as the modeling parameters will be performed.

direct simulation Monte Carlo↗

NASA NTRS2021

3D Cloud Tomography and Droplet Size Retrieval from Multi-Angle Polarimetric Imaging of Scattered Sunlight from Above

Tomography aims to recover a three-dimensional (3D) density map of a medium or an object. In medical imaging,it is extensively used for diagnostics via X-ray computed tomography (CT). We define and derive a tomographyof cloud droplet distributions via passive remote sensing. We use multi-view polarimetric images to fit a 3Dpolarized radiative transfer (RT) forward model. Our motivation is 3D volumetric probing of vertically-developedconvectively-driven clouds that are ill-served by current methods in operational passive remote sensing. Currenttechniques are indeed based on strictly 1D RT modeling and applied to a single cloudy pixel, where cloud geometrydefaults to that of a plane-parallel slab. Incident unpolarized sunlight, once scattered by cloud droplets, changesits polarization state according to droplet size. Therefore, polarimetric measurements in the rainbow and gloryangular regions can be used to infer the droplet size distribution. This work defines and derives a framework for afull 3D tomography of cloud droplets for both their mass concentration in space and their distribution across arange of sizes. This gridded 3D retrieval of key microphysical properties is made tractable by our novel approachthat involves a restructuring and partial linearization of an open-source polarized 3D RT code to accommodate aspecial two-step iterative optimization technique. Physically-realistic synthetic clouds are used to demonstrate themethodology with rigorous uncertainty quantification, while a real-world cloud imaged by AirMSPI is processedto illustrate the new remote sensing capability

Schechner, Yoav Y.↗

NASA NTRS2010

Establishing Consensus Turbulence Statistics for Hot Subsonic Jets

Many tasks in fluids engineering require knowledge of the turbulence in jets. There is a strong, although fragmented, literature base for low order statistics, such as jet spread and other meanvelocity field characteristics. Some sources, particularly for low speed cold jets, also provide turbulence intensities that are required for validating Reynolds-averaged Navier-Stokes (RANS) Computational Fluid Dynamics (CFD) codes. There are far fewer sources for jet spectra and for space-time correlations of turbulent velocity required for aeroacoustics applications, although there have been many singular publications with various unique statistics, such as Proper Orthogonal Decomposition, designed to uncover an underlying low-order dynamical description of turbulent jet flow. As the complexity of the statistic increases, the number of flows for which the data has been categorized and assembled decreases, making it difficult to systematically validate prediction codes that require high-level statistics over a broad range of jet flow conditions. For several years, researchers at NASA have worked on developing and validating jet noise prediction codes. One such class of codes, loosely called CFD-based or statistical methods, uses RANS CFD to predict jet mean and turbulent intensities in velocity and temperature. These flow quantities serve as the input to the acoustic source models and flow-sound interaction calculations that yield predictions of far-field jet noise. To develop this capability, a catalog of turbulent jet flows has been created with statistics ranging from mean velocity to space-time correlations of Reynolds stresses. The present document aims to document this catalog and to assess the accuracies of the data, e.g. establish uncertainties for the data. This paper covers the following five tasks: Document acquisition and processing procedures used to create the particle image velocimetry (PIV) datasets. Compare PIV data with hotwire and laser Doppler velocimetry (LDV) data published in the open literature. Compare different datasets acquired at roughly the same flow conditions to establish uncertainties. Create a consensus dataset for a range of hot jet flows, including uncertainty bands. Analyze this consensus dataset for self-consistency and compare jet characteristics to those of the open literature. One final objective fulfilled by this work was the demonstration of a universal scaling for the jet flow fields, at least within the region of interest to aeroacoustics. The potential core length and the spread rate of the half-velocity radius were used to collapse of the mean and turbulent velocity fields over the first 20 jet diameters in a highly satisfying manner.

Bridges, James↗

NASA NTRS2000

Hybrid concatenated codes and iterative decoding

Several improved turbo code apparatuses and methods. The invention encompasses several classes: (1) A data source is applied to two or more encoders with an interleaver between the source and each of the second and subsequent encoders. Each encoder outputs a code element which may be transmitted or stored. A parallel decoder provides the ability to decode the code elements to derive the original source information d without use of a received data signal corresponding to d. The output may be coupled to a multilevel trellis-coded modulator (TCM). (2) A data source d is applied to two or more encoders with an interleaver between the source and each of the second and subsequent encoders. Each of the encoders outputs a code element. In addition, the original data source d is output from the encoder. All of the output elements are coupled to a TCM. (3) At least two data sources are applied to two or more encoders with an interleaver between each source and each of the second and subsequent encoders. The output may be coupled to a TCM. (4) At least two data sources are applied to two or more encoders with at least two interleavers between each source and each of the second and subsequent encoders. (5) At least one data source is applied to one or more serially linked encoders through at least one interleaver. The output may be coupled to a TCM. The invention includes a novel way of terminating a turbo coder.

Divsalar, Dariush↗

NASA NTRS2004

Swift Burst Alert Telescope (BAT) Instrument Response

The Burst Alert Telescope (BAT), a large coded aperture instrument with a wide field-of-view (FOV), provides the gamma-ray burst triggers and locations for the Swift Gamma-Ray Burst Explorer. In addition to providing this imaging information, BAT will perform a 15 keV - 150 keV all-sky hard x-ray survey based on the serendipitous pointings resulting from the study of gamma-ray bursts and will also monitor the sky for transient hard x-ray sources. For BAT to provide spectral and photometric information for the gamma-ray bursts, the transient sources and the all-sky survey, the BAT instrument response must be determined to an increasingly greater accuracy. In this talk, we describe the BAT instrument response as determined to an accuracy suitable for gamma-ray burst studies. We will also discuss the public data analysis tools developed to calculate the BAT response to sources at different energies and locations in the FOV. The level of accuracy required for the BAT instrument response used for the hard x-ray survey is significantly higher because this response must be used in the iterative clean algorithm for finding fainter sources. Because the bright sources add a lot of coding noise to the BAT sky image, fainter sources can be seen only after the counts due to the bright sources are removed. The better we know the BAT response, the lower the noise in the cleaned spectrum and thus the more sensitive the survey. Since the BAT detector plane consists of 32768 individual, 4 mm square CZT gamma-ray detectors, the most accurate BAT response would include 32768 individual detector response functions to separate mask modulation effects from differences in detector efficiencies! We describe OUT continuing work to improve the accuracy of the BAT instrument response and will present the current results of Monte Carlo simulations as well as BAT ground calibration data.

Parsons, A.↗

NASA NTRS1999

Exploration of Uncertainty in Glacier Modelling

There are procedures and methods for verification of coding algebra and for validations of models and calculations that are in use in the aerospace computational fluid dynamics (CFD) community. These methods would be efficacious if used by the glacier dynamics modelling community. This paper is a presentation of some of those methods, and how they might be applied to uncertainty management supporting code verification and model validation for glacier dynamics. The similarities and differences between their use in CFD analysis and the proposed application of these methods to glacier modelling are discussed. After establishing sources of uncertainty and methods for code verification, the paper looks at a representative sampling of verification and validation efforts that are underway in the glacier modelling community, and establishes a context for these within overall solution quality assessment. Finally, an information architecture and interactive interface is introduced and advocated. This Integrated Cryospheric Exploration (ICE) Environment is proposed for exploring and managing sources of uncertainty in glacier modelling codes and methods, and for supporting scientific numerical exploration and verification. The details and functionality of this Environment are described based on modifications of a system already developed for CFD modelling and analysis.

Thompson, David E.↗

NASA NTRS1982

Algorithms for software development version control and change detection

Simple computer algorithms for processing source program and text data files in order to extract change detection, version control, version history, and current status information are described. These algorithms presuppose that it is possible to attach to each record of the source files a 6-character code, placed within delimiters that will cause the compiler, or other using program, to ignore this code field. The code contains a 2-character code for a character-by-character position-sensitive checksum of the record, another for the record number in the file, and a third for the data on which the encoding took place. Once the source file has been thus encoded, it is possible to detect the following transactions on the file since the most recent version coding; (1) addition of new records (having no version code), (2) modification of existing records, (3) deletion of a number of records, (4) movement and/or duplication of existing records, and (5) modification and duplication of records. In addition, it is possible to extract a version history of the number of records created or modified by date. A special file listing program is described which prints the file records without showing the version codes, but places a "change bar" at the right margin whenever a change is detected. The program also provides a list of changed pages and a version history.

Tausworthe, R. C.↗

NASA NTRS2019

An Automated Detection Methodology for Dry Well-Mixed Layers

The intense surface heating over arid land surfaces produces dry well-mixed layers (WML) via dry convection. These layers are characterized by nearly constant potential temperature and low, nearly constant water vapor mixing ratio. To further the study of dry WMLs, we created a detection methodology and supporting software to automate the identification and characterization of dry WMLs from multiple data sources including rawinsondes, remote sensing platforms, and model products. The software is a modular code written in Python, an open source language. Radiosondes from a network of synoptic stations in North Africa were used to develop and test the WML detection process. The detection involves an iterative decision tree that ingests a vertical profile from an input data file, performs a quality check for sufficient data density, and then searches upward through the column for successive points where the simultaneous changes in water vapor mixing ratio and potential temperature are less than the specified maxima. If points in the vertical profile meet the dry WML identification criteria, statistics are generated detailing the characteristics of each layer in the profile. At the end of the vertical profile analysis, there is an option to plot analyzed profiles in a variety of file formats. Initial results show that the detection methodology can be successfully applied across a wide variety of input data and North African environments and for all seasons. It is sensitive enough to identify dry WMLs from other types of isentropic phenomena such as subsidence layers and distinguish the current day’s dry WML from previous days.

Stephen D. Nicholls↗

NASA NTRS2014

A Mode Propagation Database Suitable for Code Validation Utilizing the NASA Glenn Advanced Noise Control Fan and Artificial Sources

The NASA Glenn Research Center's Advanced Noise Control Fan (ANCF) was developed in the early 1990s to provide a convenient test bed to measure and understand fan-generated acoustics, duct propagation, and radiation to the farfield. A series of tests were performed primarily for the use of code validation and tool validation. Rotating Rake mode measurements were acquired for parametric sets of: (i) mode blockage, (ii) liner insertion loss, (iii) short ducts, and (iv) mode reflection.

Sutliff, Daniel L.↗

NASA NTRS2014

A Mode Propagation Database Suitable for Code Validation Utilizing the NASA Glenn Advanced Noise Control Fan and Artificial Sources

The NASA Glenn Research Center's Advanced Noise Control Fan (ANCF) was developed in the early 1990s to provide a convenient test bed to measure and understand fan-generated acoustics, duct propagation, and radiation to the farfield. A series of tests were performed primarily for the use of code validation and tool validation. Rotating Rake mode measurements were acquired for parametric sets of: (1) mode blockage, (2) liner insertion loss, (3) short ducts, and (4) mode reflection.

Sutliff, Daniel L.↗